,kernel_id,rank,kaggle_score,kaggle_comments,kaggle_upvotes,kernel_link,comp_name
0,28356656,1.0,,11,52,/danofer/wids-2020-starter-catboost-0-9045-lb,WiDS Datathon 2020
1,29140873,33.0,0.911996384905402,6,12,/teamanalitycs34/lgbm-baseline,WiDS Datathon 2020
2,28710497,62.0,0.9080227497400212,1,13,/ggxgboostgg/wids2020-lgbm-starter,WiDS Datathon 2020
3,28985739,105.0,,16,10,/krrai77/wids2020-fancyimpute-lgb,WiDS Datathon 2020
4,34088724,107.0,,0,0,/saurabh7/predict-patient-survival,WiDS Datathon 2020
5,29070286,45.0,,3,4,/jessicacc/wids2020-lgb-model,WiDS Datathon 2020
6,27795188,175.0,,6,13,/abofficial444/simple-univariate-insight-1-wids-2020,WiDS Datathon 2020
7,28727928,129.0,0.907994558635358,8,12,/tejashshah/wids-eda-lgbm,WiDS Datathon 2020
8,27606681,144.0,,2,10,/antorsae/ecuador-guayaquil,WiDS Datathon 2020
9,27654742,165.0,0.8905814294976313,4,7,/binaicrai/wd-v2-0,WiDS Datathon 2020
10,29099590,170.0,0.906885102258284,1,8,/khulapkosv/lgbm-baseline-wids-2020,WiDS Datathon 2020
11,29099590,170.0,0.906885102258284,1,8,/khulapkosv/lgbm-baseline-wids-2020,WiDS Datathon 2020
12,28312981,620.0,,2,1,/pedrohsrrano/ids-baseline-wids-ln,WiDS Datathon 2020
13,82247998,700.0,,18,20,/sonmou/decision-tree-wids-datathon-2020,WiDS Datathon 2020
14,27625781,667.0,,17,60,/mpwolke/women-in-data-science,WiDS Datathon 2020
15,29148454,691.0,0.8999537548197695,2,2,/tanee94uit2010/wids-challenge,WiDS Datathon 2020
16,28395914,713.0,,2,4,/olofjens/wids2020-fillingheight-weightwithlinearregression,WiDS Datathon 2020
17,28577122,751.0,0.8900373465269843,7,4,/vaibhavsxn/wids-data-v2,WiDS Datathon 2020
18,28722761,769.0,,4,1,/kajalgupta2605/kernel-1,WiDS Datathon 2020
19,29100312,830.0,,0,0,/sindu88/wids-2020-final,WiDS Datathon 2020
20,35177928,850.0,,0,1,/arwa1551/datathon-psuteam,WiDS Datathon 2020
21,29626958,877.0,,0,1,/ranjanir/wids-2020-xgboost,WiDS Datathon 2020
23,28537757,17.0,,0,0,/maxpopken/ensemble-model,High Frequency Price Prediction of Index Futures
24,29007121,2.0,,0,0,/nravishankar/2016b3a70184g-nnfl,Multi-Class Classification
25,32052230,77.0,,0,0,/chauminhnguyenhec/second-homework-final-version-chau-minh-nguyen,Deep Learning and Applications
26,30296882,50.0,,1,18,/yasufuminakama/herbarium-2020-pytorch-resnet18-train,Herbarium 2020 - FGVC7
27,33188284,109.0,0.0,0,11,/khotijahs1/identify-plant-species-from-herbarium-specimens,Herbarium 2020 - FGVC7
28,30313596,115.0,5.008100101103524e-09,9,83,/seraphwedd18/herbarium-consolidating-the-details,Herbarium 2020 - FGVC7
29,30042790,111.0,2.768549280177188e-05,1,7,/jagannathrk/herbarium-2020,Herbarium 2020 - FGVC7
30,30646081,134.0,,1,6,/drobchak1988/herbarium-2020-fgvc7-create-tfrecords-tensorflow,Herbarium 2020 - FGVC7
31,34782705,120.0,,0,0,/hungwenchen0306/herbarium-classifier-resnet,Herbarium 2020 - FGVC7
32,34373570,138.0,4.6968917285670034e-09,1,2,/gb00000/herb-nn,Herbarium 2020 - FGVC7
33,31847564,144.0,,1,5,/tathagatbanerjee/herbarium,Herbarium 2020 - FGVC7
34,30800274,189.0,,1,4,/sagaramu/analysis-by-moving-average-with-differencing,COVID19 Local US-CA Forecasting (Week 1)
35,30568127,75.0,0.810866337154972,0,0,/luonganhtuan93/signmoid-predict,COVID19 Local US-CA Forecasting (Week 1)
36,30790194,109.0,0.0164441198246766,0,3,/seshurajup/ca-prediction-linearregression-constant-growthrate,COVID19 Local US-CA Forecasting (Week 1)
37,30840463,55.0,0.0123814282603849,0,1,/jeploretizo/covid19-ts-ca,COVID19 Local US-CA Forecasting (Week 1)
38,30810228,3.0,,3,13,/abhijithchandradas/caprediction-linearregression-multiple-growth-rate,COVID19 Local US-CA Forecasting (Week 1)
39,30845748,60.0,0.0178361060285154,2,5,/rvadlam2/identifying-spread-of-coronavirus-in-california,COVID19 Local US-CA Forecasting (Week 1)
40,32669954,6.0,,21,41,/mdmahmudferdous/covid-19-us-ca-forecasting-top-4-notebook-6th,COVID19 Local US-CA Forecasting (Week 1)
41,30831873,12.0,0.0473562900434699,0,0,/wjburns/covid-max,COVID19 Local US-CA Forecasting (Week 1)
42,30790196,13.0,,0,1,/anatidae/kernel7413bd457a,COVID19 Local US-CA Forecasting (Week 1)
43,30898457,44.0,,0,1,/peterkent/california-wk-1,COVID19 Local US-CA Forecasting (Week 1)
44,30801003,124.0,0.0546539377759452,0,3,/hugorosen/covid-ca-logarithm-interpolation,COVID19 Local US-CA Forecasting (Week 1)
45,30848066,146.0,,2,6,/nickteim/covid19-california-model-1,COVID19 Local US-CA Forecasting (Week 1)
46,30823052,5.0,,0,0,/michaelnissan/fill-missing-data-with-other-us-states-exp-or-pol,COVID19 Local US-CA Forecasting (Week 1)
47,30844920,100.0,,0,0,/danevans/covid-19-ca-modeling-v1,COVID19 Local US-CA Forecasting (Week 1)
48,30919301,85.0,,4,8,/ceshine/plotly-eda-example,COVID19 Local US-CA Forecasting (Week 1)
49,30842974,135.0,0.1139666991320028,0,0,/patricolee/covid19-us-ca-week1,COVID19 Local US-CA Forecasting (Week 1)
50,30776229,143.0,,0,0,/vjshinde04/data-transformation-forecasting,COVID19 Local US-CA Forecasting (Week 1)
51,30772485,61.0,,2,20,/panosc/california-curves-vs-other-world-regions,COVID19 Local US-CA Forecasting (Week 1)
52,30902241,34.0,,0,0,/asimjalis/covid-19-california-prediction-model,COVID19 Local US-CA Forecasting (Week 1)
53,30633398,65.0,0.4251258370942242,4,3,/rnglol/simple-taylor-series-model,COVID19 Local US-CA Forecasting (Week 1)
54,41203950,160.0,,58,109,/dferhadi/covid-19-predictions-growth-factor-and-calculus,COVID19 Local US-CA Forecasting (Week 1)
55,30799422,102.0,0.3482737830288064,0,1,/anindabhattacharjee/covid-us-kernel-fbprophet-bayesian-sampling,COVID19 Local US-CA Forecasting (Week 1)
56,30755960,169.0,0.2365015949837249,0,5,/esotericazzo/basic-eda-and-model-of-covid-19-for-us-ca,COVID19 Local US-CA Forecasting (Week 1)
57,30592516,131.0,,0,1,/shaoqianchen/kernel55aa012d32,COVID19 Local US-CA Forecasting (Week 1)
58,30715869,171.0,0.3621557102703991,0,0,/mehernan/covid-19-forecast-mehernandez,COVID19 Local US-CA Forecasting (Week 1)
59,30827911,154.0,0.5081086138851307,1,1,/wjholst/covid-19-growth-prediction-logistic-curve,COVID19 Local US-CA Forecasting (Week 1)
60,30725465,59.0,0.6237171159455813,0,0,/chriscc/covid-19-starter,COVID19 Local US-CA Forecasting (Week 1)
61,30696294,137.0,0.3988318967671671,0,0,/guidiandrea/quick-stuff-with-prophet-with-data-up-to-03-11,COVID19 Local US-CA Forecasting (Week 1)
62,30846479,9.0,,0,0,/sanjaymaurya/covid-analysis-with-polynomialfeaturelr,COVID19 Local US-CA Forecasting (Week 1)
63,30544538,175.0,0.4704874134071447,1,7,/akihisayamakawa/covid-19-ca-seir-with-parameter-optimization,COVID19 Local US-CA Forecasting (Week 1)
64,30636382,89.0,0.4897384605154209,0,0,/rajoriyas/covid19-local-us-ca-forecasting-week-1,COVID19 Local US-CA Forecasting (Week 1)
65,30487343,183.0,0.7019708944417535,2,12,/kmatsuyama/covid-19-ca-by-simple-seir,COVID19 Local US-CA Forecasting (Week 1)
66,30834836,176.0,0.7504396619329492,0,1,/khanalkiran/covid19-ca-sir-model,COVID19 Local US-CA Forecasting (Week 1)
67,30835008,184.0,1.7330738032779232,1,1,/jprachir/eda-differencing-fails-the-forecasting,COVID19 Local US-CA Forecasting (Week 1)
68,30700486,157.0,1.901833271534606,0,0,/egalinkin/kernel5c99f9fa63,COVID19 Local US-CA Forecasting (Week 1)
69,31316040,1.0,,0,0,/oytrik/2017a3ps0222g-lab2,NNFL Lab2-CNN
70,32592428,7.0,0.6991960603524168,0,23,/alimbekovkz/yandex-praktikum-pytorch-resnet50-inference,iMet Collection 2020 - FGVC7
71,34360968,1.0,,0,4,/mika30/nyc-taxi-trip-duration-prediction,IEOR 242 Spring 2020 HW 4
72,32617166,58.0,,0,0,/ivanrudenko/kernel6ec8b9a357,Explicit content detection
73,32985411,2.0,415376.0,13,28,/group16/greedy-solution-lb-400k,Hash Code Archive - Photo Slideshow Optimization
74,33450719,1.0,,0,2,/gaborfodor/covid-19-w4-a-few-charts,COVID19 Global Forecasting (Week 5)
76,36234681,65.0,0.00081111229897,0,2,/plarmuseau/wm-recommend-purecosim,WM 2020 - Personalized Item Recommendation
78,41034990,24.0,,0,2,/akhilauppuluri/mobilepriceprediction,Mobile Price Range Prediction IS2020 V2
79,40629572,25.0,,0,0,/sriharsha8/mobile-price-range-prediction,Mobile Price Range Prediction IS2020 V2
80,40629982,26.0,,0,0,/anumagallapreethi/mobile-price-range-prediction,Mobile Price Range Prediction IS2020 V2
81,40630451,27.0,,0,2,/yaminireddysama/kernel152931a17f,Mobile Price Range Prediction IS2020 V2
82,41060706,36.0,,0,0,/yelchuriaakanksha/notebook012cc2a9f9,Mobile Price Range Prediction IS2020 V2
83,41062064,37.0,,0,0,/rahulkumar152/notebook83ba8a35bb,Mobile Price Range Prediction IS2020 V2
84,39999420,78.0,,0,0,/jaikishan52/logistic-csvjk,Mobile Price Range Prediction IS2020 V2
85,41079129,88.0,,1,0,/subhamnandy/mobile-price-pediction-subham-nandy,Mobile Price Range Prediction IS2020 V2
86,41952353,108.0,,0,0,/rohinsrikumar/week-4-assignment,Mobile Price Range Prediction IS2020 V2
87,44285437,118.0,,0,0,/tejanagadattu/dattu,Mobile Price Range Prediction IS2020 V2
88,41038003,129.0,,0,0,/sowmya1120/mobile-price-prediction,Mobile Price Range Prediction IS2020 V2
89,44284275,131.0,,0,0,/saihemanthkumar/notebook674b3c5912,Mobile Price Range Prediction IS2020 V2
90,41954265,147.0,,0,0,/praneethravikanti/notebookd7fece6f2a,Mobile Price Range Prediction IS2020 V2
91,39858539,152.0,,0,0,/vikasvikky2020/kernel14cca4c070,Mobile Price Range Prediction IS2020 V2
92,43372368,181.0,,0,0,/jhansimullapudi/jhansimullapudi-ml,Mobile Price Range Prediction IS2020 V2
93,43430221,182.0,,0,0,/samhithaveeramaneni/notebook-samhitha,Mobile Price Range Prediction IS2020 V2
94,43431036,183.0,,0,0,/pichikalapranathi/pichikala-pranathi-ml,Mobile Price Range Prediction IS2020 V2
95,43474743,184.0,0.89,0,0,/ramyapravallika/ramyapravallika,Mobile Price Range Prediction IS2020 V2
96,43443958,185.0,,0,0,/saisrigayathri/notebookbca9db5a0c,Mobile Price Range Prediction IS2020 V2
97,44229684,194.0,,0,0,/tummalatejasri/teju-week5,Mobile Price Range Prediction IS2020 V2
98,44221495,207.0,,0,0,/charaniveerla/charanimobilepriceprediction,Mobile Price Range Prediction IS2020 V2
99,44242087,211.0,0.875,2,2,/muraliravuri/my-first-kaggle,Mobile Price Range Prediction IS2020 V2
100,44230862,216.0,,0,0,/likhitatulimilli/likhita9,Mobile Price Range Prediction IS2020 V2
101,44270080,226.0,,0,0,/eshwarj/eshwar,Mobile Price Range Prediction IS2020 V2
102,44272600,227.0,,0,0,/chandukancharla/chandu,Mobile Price Range Prediction IS2020 V2
103,42014625,234.0,,0,0,/brajesh419/notebookfca1e38efb,Mobile Price Range Prediction IS2020 V2
104,39816524,252.0,,0,7,/hemanthkumarpatnala1/mobile-price-rangepredictio,Mobile Price Range Prediction IS2020 V2
105,43694573,1.0,,2,12,/artemglazunov1990/stacking,MegaFon Accelerator
144,44888618,6.0,,0,2,/ashish12350/emnist-using-cnn-87-15-test-accuracy,109-1 NTUT Building Deep Learning Applications HW1
145,44439640,9.0,,0,0,/mahathes1232/kaggle-heart-disease-prediction,Machine Learning Challenge
146,45365843,5.0,0.9333076045990252,0,0,/jillwang87/xgboost,UWaterloo STAT441/841 Data Challenge 1
147,46662684,82.0,,0,1,,TAU Ethiopic Digit Recognition
148,46558391,5.0,,0,1,/ashish12350/image-hashtag-recommendation,109-1 NTUT DL APP HW2 Image Hashtag Recommendation
149,46860845,6.0,,0,5,/sergemsu/direct-0-643,MADE HW-2
150,46854948,13.0,0.6394224924012225,0,1,/holyketzer/ml-hw1-movie-genres-tfidf-tune-merge-dialog-0-639,MADE HW-2
151,46809863,9.0,0.6056982438365467,0,3,/mornie/logreg-0-64prlb-v-6,MADE HW-2
152,46849493,53.0,,0,2,/astarikov/movie-genre-logregression-0-62,MADE HW-2
153,46836974,73.0,0.6200284250816223,0,10,/langsys/simple-baseline-0-619-plb-0-62prlb,MADE HW-2
154,45849957,69.0,0.6156129685916973,0,1,/natiaris/whatever,MADE HW-2
155,52554063,211.0,,0,0,/xluttiy/made-ml-hw2-ekh-ds12,MADE HW-2
156,46475612,26.0,,0,3,/yonseieomjihwan/randomforest-baseline-public-score-0-04940,Financial Engineering Competition (1/3)
157,50003068,87.0,,0,0,/windowheejae2001/notebooke2,Financial Engineering Competition (1/3)
158,49954153,273.0,0.045710133404806,0,0,/jeongsujeong/notebook7e6667b40d-cp1,Financial Engineering Competition (1/3)
159,49954153,273.0,0.045710133404806,0,0,/jeongsujeong/notebook7e6667b40d-cp1,Financial Engineering Competition (1/3)
160,45953632,48.0,,0,0,/ebinjohny/ai-club-inductions-1,AI CLUB INDUCTIONS
161,105355728,2.0,,6,3,/sunnydial/extratreesclassifier-optuna,2020 Classification Data Challenge
162,89973714,134.0,0.6679566563467493,0,2,/rocklen/2020-classification-data-challenge,2020 Classification Data Challenge
163,126870101,138.0,,0,0,/pradeepsapparapu/umass-dartmouth,2020 Classification Data Challenge
164,47863294,147.0,,1,2,/adityarc19/2020-clf-data-challenge,2020 Classification Data Challenge
165,52310409,202.0,,0,0,/suramrk/2020dataclass-challenge,2020 Classification Data Challenge
166,47987786,26.0,0.0459720711847309,0,5,/yonseieomjihwan/just-drop-baseline-pb-0-04597,Financial Engineering Competition (2/3)
167,49887218,167.0,0.0334438286797625,1,3,/wooyungkim/notebooke29513743f,Financial Engineering Competition (2/3)
168,47383420,233.0,,0,0,/kimhyoungminhass20/notebookcecd5dfd13,Financial Engineering Competition (2/3)
169,48075724,28.0,,0,4,/yonseieomjihwan/build-two-models-baseline-pb-0-29165,Financial Engineering Competition (3/3)
170,48387161,57.0,,0,0,/jillwang87/fashion-cnn,UWaterloo STAT441/841 Data Challenge 2
171,53112403,110.0,,0,1,/cs18b060vaibhav/unbiased2,PRML-Data Contest-Nov 2020
172,53248724,145.0,,0,0,/gowttham123pan/notebooka6475e9c2a,PRML-Data Contest-Nov 2020
173,52635904,105.0,,0,1,/pablodingianna/notebooka9c365ac3e,Datathon Internacional Interbank 2020
174,53863976,112.0,,0,0,/fotrino/benchmark-interbank,Datathon Internacional Interbank 2020
175,55172688,200.0,,0,0,/kisiro55/10-preprocessing,Datathon Internacional Interbank 2020
176,59688544,7.0,29898.93199401117,2,5,/bernhardklinger/actuarial-loss-prediction-automl,Actuarial loss prediction
177,57815554,17.0,30103.77750646757,3,9,/docxian/actuarial-loss-prediction-eda-and-baseline-in-r,Actuarial loss prediction
178,52031523,29.0,,10,22,/floser/workers-compensation-explore-and-predict,Actuarial loss prediction
179,106681978,9.0,,0,0,/mskoubani/for-starters,Actuarial loss prediction
180,59328024,25.0,,1,19,/louise2001/rapids-pca-for-sentenceembeddings,Actuarial loss prediction
181,58440934,77.0,30133.045374948284,1,7,/alexryzhkov/lightautoml-starter,Actuarial loss prediction
182,51250845,92.0,,6,16,/tanguypledel/topic-modeling-lda-implementation,Actuarial loss prediction
183,59425407,104.0,,0,0,/jerrytutttle/notebook402ef18ab3,Actuarial loss prediction
184,50099168,117.0,,1,3,/matteocondelli/actuarial-eda,Actuarial loss prediction
186,53327325,6.0,,0,11,/schopenhacker75/lgb-frequency-encoding-target-encoding,WiDS Datathon 2021
187,52258985,10.0,0.8551891268485672,0,2,/kingabzpro/lgbm-ds-for-women-2021,WiDS Datathon 2021
188,55627612,16.0,0.8723827767717333,2,8,/fatihozturk/2stage-modeling-trick-and-psuedo-labeling-0-873,WiDS Datathon 2021
189,51944738,47.0,0.8564323058984675,4,5,/nasere/wids2021-using-lightgbm-encoding,WiDS Datathon 2021
190,58070899,29.0,0.8723323793365438,5,3,/mzsmkmok/29th-place-wids2021-lgb0-87-japanese,WiDS Datathon 2021
191,57523652,44.0,0.8477821002782014,45,188,/ruchi798/wids-datathon-2021-rapids-xgb-lightgbm,WiDS Datathon 2021
192,52701539,90.0,0.8605588021913363,9,33,/dkaing/tips-tricks,WiDS Datathon 2021
193,51578326,23.0,0.8588346259577259,9,15,/hamzafarooq50/lightgbm-encoding-0-85883-score,WiDS Datathon 2021
194,55385916,30.0,0.8508863030053755,0,13,/shrutisaxena/catboost-algorithm,WiDS Datathon 2021
195,59378608,34.0,,0,0,/noviapermatasari4/shafvia-via-modelling,WiDS Datathon 2021
196,55966733,107.0,,4,11,/adityajha1504/wids2021-nn-solution,WiDS Datathon 2021
197,54064661,61.0,0.8454647068792499,1,3,/obougacha/wids2021-h2o-automl,WiDS Datathon 2021
198,55070626,144.0,,14,38,/celniker/wids2021-initial-eda-and-tuned-lgbm-0-86293,WiDS Datathon 2021
199,52398596,129.0,0.8592426293751035,1,2,/darynarr/optimized-lgbm-wids2021,WiDS Datathon 2021
200,51327385,128.0,,29,42,/hackspyder/faster-eda-for-data-understanding,WiDS Datathon 2021
201,51330583,130.0,,10,41,/saurabhshahane/data-is-your-weapon-understand-it-first,WiDS Datathon 2021
202,53250619,175.0,0.8580549255876156,6,40,/louise2001/rapids-complete-gpu-pipeline-for-beginners,WiDS Datathon 2021
203,53485887,237.0,0.8546501154888329,7,9,/sreejaej/eda-prediction,WiDS Datathon 2021
204,55505455,196.0,0.8256481053039809,0,1,/trisha09/wids-modeling,WiDS Datathon 2021
205,53059057,209.0,,4,3,/kumaraselva/wids-lda-analysis,WiDS Datathon 2021
206,55133693,198.0,,5,12,/afafathar3007/wids-datathon-2021-analysis-modelling,WiDS Datathon 2021
207,53932744,269.0,,0,5,/liagaetano/eda-merged-notebook,WiDS Datathon 2021
208,117487499,168.0,,0,1,/ishutrivedi/xgboost-with-hyper-parameter-tuning,WiDS Datathon 2021
209,51856852,190.0,,15,18,/reverie5/statistical-analysis-univariate-multivariate,WiDS Datathon 2021
210,54126220,264.0,,3,4,/akashkirodiwal/is-insulin-required-lets-find-it-out,WiDS Datathon 2021
211,51394683,292.0,0.836729320707316,1,7,/danofer/wids-21-tabnet-simple-baseline,WiDS Datathon 2021
212,52081637,210.0,0.8581036727289576,0,6,/uozcan12/lightgbm-encoding-0-8581,WiDS Datathon 2021
213,53414382,213.0,0.8581668916778855,15,21,/hyperbeam/starter-s-notebook-with-lgbm-classifier,WiDS Datathon 2021
214,56039059,277.0,0.8584257339205841,29,82,/andradaolteanu/wids-datathon-rapids-ensembles-w-b,WiDS Datathon 2021
215,52829241,232.0,,4,4,/msafi04/wids-diabetes-prediction-eda,WiDS Datathon 2021
216,53053255,323.0,,35,35,/salmaeng/statistical-analysis-eda,WiDS Datathon 2021
217,52623006,297.0,,17,21,/atulyaatul1999/wids-datathon-2021-data-cleaning-and-model,WiDS Datathon 2021
218,55574676,274.0,,2,4,/julianapassos/wids-2021-diabetes-mellitus-xgb,WiDS Datathon 2021
219,53030580,267.0,,3,12,/rsesha/wids-score-85-5-using-featurewiz-auto-viml,WiDS Datathon 2021
220,51405128,324.0,,5,9,/krrai77/extensive-eda-for-model-prediction,WiDS Datathon 2021
221,55651704,370.0,,29,28,/khanalkiran/wids-xgboost-pca,WiDS Datathon 2021
222,53313962,400.0,,9,10,/aiswaryaramachandran/predicting-diabetes-using-lightgbm-and-shap,WiDS Datathon 2021
223,55460152,353.0,0.8474078644118574,4,12,/vaishnavipatil4848/wids-datathon-2021-diabetes-analysis,WiDS Datathon 2021
224,55481511,414.0,,5,3,/manimec2007/wells-army-wids-dathathon-2021,WiDS Datathon 2021
225,52101184,391.0,,5,21,/thedatabeast/wids-2021-tutorial,WiDS Datathon 2021
226,54579164,396.0,,1,3,/manideepteambvrit/it-group,WiDS Datathon 2021
227,55509086,450.0,,5,11,/rashmiranu/wids-datathon-eda-model-building,WiDS Datathon 2021
228,51364152,360.0,,2,9,/mpwolke/hematocrit-wids-2021,WiDS Datathon 2021
229,54399481,472.0,,8,17,/rxsraghavagrawal/eda-feature-engineering-imputation-for-beginners,WiDS Datathon 2021
230,53582723,423.0,,2,3,/nikitakirpa/wids-2021-nickkirpa,WiDS Datathon 2021
231,53689805,437.0,,1,2,/pfarzana1313/wids-eda-trail1,WiDS Datathon 2021
232,55571941,438.0,,0,1,/sreevanijarugula/wids21-xgboost,WiDS Datathon 2021
233,53465358,470.0,,1,4,/yh3206/clinical-analytics-predicting-diabetes-in-icus,WiDS Datathon 2021
234,53886498,443.0,,0,5,/letianyu/wids-2021-notebook,WiDS Datathon 2021
235,53114349,464.0,,4,6,/akan27/wids-datathon-2021-akanksha,WiDS Datathon 2021
236,51373111,529.0,,7,9,/amr009/tabnet-simple-baseline,WiDS Datathon 2021
237,53169142,513.0,,1,4,/itokianarafidinarivo/wids-datathon-2021-target-analysis,WiDS Datathon 2021
238,53541082,522.0,,4,10,/changsun1025/wids-maastricht-for-beginners,WiDS Datathon 2021
239,52774097,560.0,,4,15,/paolagasp/wids-eda-building-models-save,WiDS Datathon 2021
240,61349602,550.0,,0,0,/salonimishra/widsdatathon2021,WiDS Datathon 2021
241,55059788,536.0,0.8003805196775325,3,5,/saranyakm/wids-datathon-2021-deep-learning-inprogress,WiDS Datathon 2021
242,55564504,554.0,0.8246291123259812,0,4,/elrayah/wids-datamation-2021-diabetics-prediction,WiDS Datathon 2021
243,52030145,574.0,,4,8,/danielefm/wids-datathon-2021-eda,WiDS Datathon 2021
244,55415271,528.0,,3,2,/divyamehta/eda-data-cleaning,WiDS Datathon 2021
245,73093052,591.0,,1,15,/kalilurrahman/wids-datathon-kr-submission-file,WiDS Datathon 2021
246,55282863,577.0,0.8179938520206896,0,5,/nishantkumar61988/widsdatathon2021-diabetes-mellitus-prediction,WiDS Datathon 2021
247,55469489,614.0,,1,4,/truptikadam/notebook0a762dd159,WiDS Datathon 2021
248,51804446,628.0,,1,7,/shyambhu/wids-datathon-intro-and-analysis,WiDS Datathon 2021
249,55501365,661.0,,9,7,/darknez/nulls-analysis-and-eda,WiDS Datathon 2021
250,52002872,655.0,,1,6,/praveenmaripeti/wids-datathon-2021-challenge-eda-model-submission,WiDS Datathon 2021
251,54905915,726.0,,1,7,/aliyaadav/wids-2021-seaborn,WiDS Datathon 2021
252,55340284,761.0,,1,3,/rethavathij/diabetes-model,WiDS Datathon 2021
253,54845435,3.0,28.249114570415728,11,9,/vishallobhe/ipl-2020-performance-prediction,IPL 2020 Player Performance
254,54797343,29.0,,0,0,/candyflossdentist/wells-fargo-shehacks-21-lgbm-version,<She/Hacks> - Shaastra'21 and Wells Fargo
255,55243640,20.0,4410177.0,4,30,/azaky003/hashcode-2021-cpp,Hash Code 2021 - Traffic Signaling
256,61672491,23.0,4031175.0,0,4,/jazivxt/hash-code-2021-fun,Hash Code 2021 - Traffic Signaling
257,58783237,40.0,4024411.0,0,1,/marcoisajoke/hash-code-traffic-light-optimal,Hash Code 2021 - Traffic Signaling
258,55438978,49.0,,2,15,/batzner/simulation-and-grading-in-python,Hash Code 2021 - Traffic Signaling
259,55242009,96.0,4020533.0,2,22,/huikang/sample-submission-with-green-light-duration-of-one,Hash Code 2021 - Traffic Signaling
260,56694267,125.0,4008896.0,0,0,/simonplatonov/hash-code-platonov,Hash Code 2021 - Traffic Signaling
261,55619474,134.0,,0,1,/chiragjn101/remove-unused-streets-1-sec-open-by-tlcq,Hash Code 2021 - Traffic Signaling
262,56714159,135.0,3988763.0,0,5,/bkhamdeev/simpletrafficlights,Hash Code 2021 - Traffic Signaling
263,55798626,151.0,,1,2,/rianlee/simple-submission-code,Hash Code 2021 - Traffic Signaling
264,58412974,158.0,,2,1,/pasithan/traffic-light-optimization,Hash Code 2021 - Traffic Signaling
265,55608046,170.0,0.0,0,3,/giraycoskun/googhashcode-trivial-solution,Hash Code 2021 - Traffic Signaling
302,56574649,1.0,,1,32,/davidedwards1/tabularmarch21-dae-starter,Tabular Playground Series - Mar 2021
303,55577586,8.0,,2,9,/gcspkmdr/tabular-playground-mar-adversarial-validation,Tabular Playground Series - Mar 2021
304,57770271,16.0,,0,2,/elvinagammed/fast-ai-tabular-classification-with-dice-metrics,Tabular Playground Series - Mar 2021
305,55624831,17.0,0.8920237097949082,10,19,/pradeepboopathy/lightgbm-10-folds,Tabular Playground Series - Mar 2021
306,55667984,20.0,,3,10,/kyakovlev/tps-mar-adversarial-validation,Tabular Playground Series - Mar 2021
307,56323758,15.0,,5,25,/alexryzhkov/lightautoml-starter-for-tabulardatamarch,Tabular Playground Series - Mar 2021
308,55829961,12.0,,0,8,/delai50/visualize-numerical-features-with-chernoff-faces,Tabular Playground Series - Mar 2021
309,57532541,93.0,,0,15,/somayyehgholami/tps-mar-part-1-kernels,Tabular Playground Series - Mar 2021
310,57691281,32.0,,5,13,/dhawan123/quick-start-to-be-in-top-30-1,Tabular Playground Series - Mar 2021
311,56995534,29.0,,6,32,/saurabhshahane/h2oautoml-template,Tabular Playground Series - Mar 2021
312,57062860,35.0,,3,17,/santoshd3/tabular-playground-march,Tabular Playground Series - Mar 2021
313,55563912,85.0,0.8863348096573559,0,2,/avisoori1x/lightgbm-optuna-cv-and-gotchas,Tabular Playground Series - Mar 2021
314,55567636,97.0,0.8909464653155912,0,1,/zaefir/tps-mar-2021-auto-starter-with-and,Tabular Playground Series - Mar 2021
315,57679358,41.0,,0,1,/sozy20/march-tabular-playground-competition,Tabular Playground Series - Mar 2021
316,55733518,181.0,0.8858471889249594,4,22,/caesarlupum/starter-here-ensemble-stacknetclassifier,Tabular Playground Series - Mar 2021
317,57368979,59.0,0.8802868507958534,12,73,/ruchi798/tps-march-2021-eda-rapids,Tabular Playground Series - Mar 2021
318,58178463,50.0,0.8916583657331411,0,7,/kalashnimov/xgb-and-lgbm-baseline,Tabular Playground Series - Mar 2021
319,58232075,57.0,0.8923435379644282,23,64,/hamzaghanmi/tps-mar-2021-eda-5folds-lgbm,Tabular Playground Series - Mar 2021
320,56517926,66.0,,11,14,/madquer/tbs-mar-modeling-stratifykfold-and-ensemble,Tabular Playground Series - Mar 2021
321,57870442,86.0,0.8846030629992829,1,6,/manwithaflower/tps-march2021-xgb-baseline,Tabular Playground Series - Mar 2021
322,56077501,103.0,0.8908533454243854,12,16,/manabendrarout/lb-0-89-easy-approach-for-beginners-starter-code,Tabular Playground Series - Mar 2021
323,57493586,104.0,0.8836809615909007,1,5,/kilimannejaro/get-started-mar-tabular-playground-competition,Tabular Playground Series - Mar 2021
324,57007771,106.0,,2,6,/pourchot/keras-sequential-wins-against-tabnet,Tabular Playground Series - Mar 2021
325,55818475,110.0,0.8926855061602196,44,131,/craigmthomas/tps-mar-2021-stacked-starter,Tabular Playground Series - Mar 2021
326,57868520,115.0,,0,5,/celniker/tps-lgbm-with-hpo-0-88,Tabular Playground Series - Mar 2021
327,56004573,120.0,0.8763545444200933,11,10,/rapela/tps-03-21-tabnet-classifier,Tabular Playground Series - Mar 2021
328,56004573,120.0,0.8763545444200933,11,10,/rapela/tps-03-21-tabnet-classifier,Tabular Playground Series - Mar 2021
329,58337622,123.0,,0,1,/coder247/mar-2021-stacking-and-optuna,Tabular Playground Series - Mar 2021
330,57814672,125.0,0.8929118455782139,22,70,/rmiperrier/tps-mar-lgbm-optuna,Tabular Playground Series - Mar 2021
331,56345422,128.0,0.8924687844335312,9,32,/tunguz/tps-mar-2021-eda,Tabular Playground Series - Mar 2021
332,55609635,136.0,0.8907934881167917,0,4,/obougacha/marchtab-xgb-baseline,Tabular Playground Series - Mar 2021
333,55702074,146.0,,6,7,/mamun18/march-tps-ensemble-modelling,Tabular Playground Series - Mar 2021
334,56576510,152.0,0.8914633531702421,0,5,/kengofujii/tabular-mar-lightgbm,Tabular Playground Series - Mar 2021
335,57296849,157.0,0.8865314805153687,1,6,/vcaquilpan/lightgbm-in-action-tabular-competition,Tabular Playground Series - Mar 2021
336,56178866,161.0,,9,26,/gvyshnya/mar-21-tpc-express-eda-with-autoviz,Tabular Playground Series - Mar 2021
337,55961180,169.0,0.8855898442224053,1,8,/docxian/tabular-playground-3-here-we-go-again,Tabular Playground Series - Mar 2021
338,55662918,165.0,,10,11,/maostack/tps-mar-baseline,Tabular Playground Series - Mar 2021
339,57823505,197.0,0.8854898105646892,0,3,/gangadher/tps-mar2021-gaussiannb-tpot,Tabular Playground Series - Mar 2021
340,58100254,196.0,0.8928050736516326,2,9,/nishantdhingra/tps-march-lgbm-with-optuna,Tabular Playground Series - Mar 2021
341,58100254,196.0,0.8928050736516326,2,9,/nishantdhingra/tps-march-lgbm-with-optuna,Tabular Playground Series - Mar 2021
342,57078671,210.0,,0,4,/urstrulysai/tps-march-stacking,Tabular Playground Series - Mar 2021
343,56458833,180.0,0.8848515876315649,5,10,/gomes555/tps-mar2021-tree-baselines-catboost-bayesopt,Tabular Playground Series - Mar 2021
344,55893902,194.0,0.8922433760988517,8,39,/dmitryuarov/catboost-vs-xgb-vs-lgbm-tps-mar-21,Tabular Playground Series - Mar 2021
345,56330604,214.0,,12,15,/sayantansadhu/lgbm-with-hyper-parameter-tuning-using-optuna,Tabular Playground Series - Mar 2021
346,56891106,186.0,0.8914963278116099,8,11,/haichaoshang/tps-mar2021-xgboost-optuna,Tabular Playground Series - Mar 2021
347,58461461,187.0,,14,32,/sureshmecad/tabular-playground,Tabular Playground Series - Mar 2021
348,57579051,215.0,,0,2,/jmargni/tabular-mar-lightgbm-hyperopt,Tabular Playground Series - Mar 2021
349,55905950,223.0,,1,15,/ritesh2000/dae-denoising-transformer-autoencoder,Tabular Playground Series - Mar 2021
350,55558094,252.0,,7,14,/atharvaingle/trust-your-cv-how-to-properly-split-folds,Tabular Playground Series - Mar 2021
351,56249629,220.0,0.8925751549223853,9,15,/svyatoslavsokolov/tps-mar-2021-lgbm,Tabular Playground Series - Mar 2021
352,58033115,284.0,,0,5,/herwinvw/cat-boost-parameter-tuning,Tabular Playground Series - Mar 2021
353,58285323,212.0,0.8926231403922732,8,20,/ekozyreff/tps-2021-03-lightgbm-optuna-10-folds,Tabular Playground Series - Mar 2021
354,55889569,198.0,,0,8,/luigisaetta/tab-playground-nb2,Tabular Playground Series - Mar 2021
355,84245394,209.0,,10,67,/hasanbasriakcay/tps-mar21-eda-feature-engineering,Tabular Playground Series - Mar 2021
356,56663001,282.0,,5,9,/cahidarda/tabular-playground-march-2021,Tabular Playground Series - Mar 2021
357,56562209,265.0,0.8917407550467763,2,9,/calebyenusah/lgbm-and-optuna-tps-march-2021,Tabular Playground Series - Mar 2021
358,55721435,249.0,,0,3,/mayasakaguchi/tps-mar-21-labelencoder-vs-onehotencoder,Tabular Playground Series - Mar 2021
359,56390939,254.0,,3,11,/marychin/2d-flood-maps-feature-importances-borutashap,Tabular Playground Series - Mar 2021
360,57485018,317.0,,8,26,/gaetanlopez/tps-complete-eda-single-lgb-tuning-strategy,Tabular Playground Series - Mar 2021
361,56037825,318.0,,0,2,/aakash90/mar-tabular-fun,Tabular Playground Series - Mar 2021
362,58511838,302.0,0.8923119084547115,0,1,/pelagial/tps-march-21-stacking-ensemble,Tabular Playground Series - Mar 2021
363,56566191,262.0,0.7645297075057463,0,2,/academy4440/forth,Tabular Playground Series - Mar 2021
364,56175633,322.0,0.8899797444191013,2,5,/harshitt21/tps-march-2021-catboost-script,Tabular Playground Series - Mar 2021
365,58390195,331.0,0.8919702282011642,0,0,/antonellomartiello/tabular-v7,Tabular Playground Series - Mar 2021
366,55569292,328.0,,0,1,/sebastjancizel/tabular-playground-mar-eda-and-dataviz,Tabular Playground Series - Mar 2021
367,58014595,380.0,,18,39,/desalegngeb/march-tps-eda-visualizations,Tabular Playground Series - Mar 2021
368,57399555,376.0,0.8917348879608321,8,7,/theawm/0-8917-stratified-kfold-xgboost-eda,Tabular Playground Series - Mar 2021
369,55745507,563.0,,0,5,/ricopue/tps-march-2021-ordinal-encoding-and-ugly-plots,Tabular Playground Series - Mar 2021
370,55568350,387.0,,1,4,/joolousada/tps-march-2021,Tabular Playground Series - Mar 2021
371,58313769,360.0,0.8914654570402152,4,7,/bhavikjain/xgb-lgbm-tabular-playground-series-march,Tabular Playground Series - Mar 2021
372,58313769,360.0,0.8916681746853538,4,7,/bhavikjain/xgb-lgbm-tabular-playground-series-march,Tabular Playground Series - Mar 2021
373,58313769,360.0,0.8914715563715461,4,7,/bhavikjain/xgb-lgbm-tabular-playground-series-march,Tabular Playground Series - Mar 2021
374,58108730,396.0,0.8908369442761979,0,3,/hiroshi0530/tpg-mar2021-optuna-xgb,Tabular Playground Series - Mar 2021
375,58367557,351.0,,0,1,/tmitanitky/tabular-compe-lightgbm-optunacv,Tabular Playground Series - Mar 2021
376,66448503,401.0,,7,25,/tomwarrens/tps-march-2021-lgbm-optuna,Tabular Playground Series - Mar 2021
377,57704169,363.0,0.8906133760395818,0,10,/onielg/simplecatboostandlgbmwithrankblend,Tabular Playground Series - Mar 2021
378,57704169,363.0,0.8906133760395818,0,10,/onielg/simplecatboostandlgbmwithrankblend,Tabular Playground Series - Mar 2021
379,57745778,407.0,0.8914135139407973,17,22,/rajgandhi/tps-march-lgbm-7-fold-cv,Tabular Playground Series - Mar 2021
380,57745778,407.0,0.8912536912829542,17,22,/rajgandhi/tps-march-lgbm-7-fold-cv,Tabular Playground Series - Mar 2021
381,56068624,481.0,0.8910155861665484,0,4,/jeanpierrrerio/march-tabular-playground-competition,Tabular Playground Series - Mar 2021
382,57678050,442.0,0.6863596672699162,3,9,/franckepeixoto/tabular-playground-mutual-information-pca,Tabular Playground Series - Mar 2021
383,56146207,479.0,0.8909657070035079,2,6,/ccollado7/tps-mar-2021-eda-models,Tabular Playground Series - Mar 2021
384,58050665,469.0,0.8908492480272698,1,9,/tessytessy/teresia-mar-tabular-playground-competition,Tabular Playground Series - Mar 2021
385,57915487,462.0,0.8819268510682426,6,8,/akioonodera/tps-mar2021-sk-learn,Tabular Playground Series - Mar 2021
386,56542313,438.0,0.8825187531318973,3,12,/josephchan524/tabularplaygroundclassifier-using-lightgbm-mar2021,Tabular Playground Series - Mar 2021
387,56542313,438.0,0.8892792671117455,3,12,/josephchan524/tabularplaygroundclassifier-using-lightgbm-mar2021,Tabular Playground Series - Mar 2021
388,59631826,414.0,,1,5,/naimur978/insurance-s-tabular-data-optuna,Tabular Playground Series - Mar 2021
389,56257573,474.0,0.8905357051955668,6,5,/riyajm/dealing-with-cats-xgb,Tabular Playground Series - Mar 2021
390,55573069,428.0,0.8901102390034121,0,1,/drscarlat/tps-mar-2021-automl-for-the-lazy,Tabular Playground Series - Mar 2021
391,55545979,472.0,,0,1,/akashkr/tabular-playground,Tabular Playground Series - Mar 2021
392,56114475,519.0,,2,7,/lucapianta/tpgmarch-eda,Tabular Playground Series - Mar 2021
393,56936480,503.0,,4,7,/haticekocaosmanlar/tps-march-2021-eda-ml-comparisons,Tabular Playground Series - Mar 2021
394,57807205,518.0,,1,5,/mustang007/tabular-playground-series,Tabular Playground Series - Mar 2021
395,56356792,486.0,0.8898459300919107,7,16,/optimo/tabnet-baseline,Tabular Playground Series - Mar 2021
396,56457348,525.0,,0,3,/munumbutt/thus-he-cried-ensembles-its-alive-75-tile,Tabular Playground Series - Mar 2021
397,60128751,557.0,,0,1,/shamblesean/march-competition,Tabular Playground Series - Mar 2021
398,56619458,576.0,0.8894113359204419,2,5,/muneeb2405/boosting,Tabular Playground Series - Mar 2021
399,56674660,508.0,0.8887002720066376,0,0,/tthien/20210412-complex-drop-c10-c2,Tabular Playground Series - Mar 2021
400,56527151,596.0,0.8891051702951382,13,30,/ksvmuralidhar/eda-fe-with-mi-xgb-optcv-tps-mar-2021,Tabular Playground Series - Mar 2021
401,55613495,611.0,0.888797613299283,0,1,/standpr2019/catboost-baseline-tps-2021mar,Tabular Playground Series - Mar 2021
402,58024728,609.0,0.88052482034821,0,0,/jackday0/tabular-playground-march-2021,Tabular Playground Series - Mar 2021
403,56636411,562.0,0.8886971067437208,0,7,/innixma/tps-march-autogluon,Tabular Playground Series - Mar 2021
404,57332596,607.0,,6,20,/godzill22/blending-with-optimal-weights-tps-march2021,Tabular Playground Series - Mar 2021
405,57185804,672.0,0.8886565300067555,0,3,/muntakim/gridsearch-with-lightgbm-approach,Tabular Playground Series - Mar 2021
406,58351821,610.0,,1,4,/hamzaadnan/catboost-baseline-achieve-88-8-auc-with-0-effort,Tabular Playground Series - Mar 2021
407,56374261,619.0,0.8883122036270382,0,3,/pornthepkoo/xgboost-in-r-for-starter,Tabular Playground Series - Mar 2021
408,55871128,648.0,0.8750462504602347,0,3,/barteksadlej123/eda-and-sklearn-models,Tabular Playground Series - Mar 2021
409,55871128,648.0,0.8846576679881324,0,3,/barteksadlej123/eda-and-sklearn-models,Tabular Playground Series - Mar 2021
410,57556574,667.0,,3,6,/abhishekkumar61999/tabular-playground-series,Tabular Playground Series - Mar 2021
411,56343623,677.0,0.8808117695068155,2,6,/saztorralba/tabulardata-pytorchmlp,Tabular Playground Series - Mar 2021
412,58460149,744.0,,0,0,/ctlockhart3/tps-mar21-binary-xgb-clf,Tabular Playground Series - Mar 2021
413,55582977,695.0,0.887431804452495,0,0,/sanjay147/lightgbm-baseline,Tabular Playground Series - Mar 2021
414,56398381,722.0,,0,3,/dazzpool/tps-march-2021,Tabular Playground Series - Mar 2021
415,58373649,708.0,0.8842832400841834,3,3,/wuuthraad/team-4-star,Tabular Playground Series - Mar 2021
416,59208330,743.0,,0,1,/natthasit/practice,Tabular Playground Series - Mar 2021
417,56068280,711.0,0.8701093482740468,0,5,/harsh484/first-blend-xbg-lgbm,Tabular Playground Series - Mar 2021
418,55613342,716.0,0.8717949789850502,2,10,,Tabular Playground Series - Mar 2021
419,56624827,735.0,,0,1,/rafanovello/teste-bla,Tabular Playground Series - Mar 2021
420,57991115,775.0,,2,3,/valtintin/formation-argus,Tabular Playground Series - Mar 2021
421,55851923,793.0,,0,3,/danieladif/tps-march-2021-learning-stratifiedkfold,Tabular Playground Series - Mar 2021
422,58402248,812.0,0.886950441734929,1,2,/petregriscenco/tabular-beginners-competition-march-2021-pipeline,Tabular Playground Series - Mar 2021
423,58405450,819.0,0.8859485845284722,1,1,/nacmarino/tps202103-mlp-embedding,Tabular Playground Series - Mar 2021
424,58405450,819.0,0.8859485845284722,1,1,/nacmarino/tps202103-mlp-embedding,Tabular Playground Series - Mar 2021
425,66400334,857.0,,0,3,/rsesha/keras-model-march-tps-accuracy-88-8,Tabular Playground Series - Mar 2021
426,57104600,826.0,0.8845726399045158,0,1,/thomaspmcg/ml-comp,Tabular Playground Series - Mar 2021
427,57235257,779.0,,0,0,/lanle793/tps-mar-2021-fastai-tabular-learner,Tabular Playground Series - Mar 2021
428,55552663,837.0,0.8843383421412133,0,1,/bhimantoros/tps-march-2021-lgbm,Tabular Playground Series - Mar 2021
429,55851960,816.0,0.8839982371629358,2,4,/slm37102/tabular-mar-using-neural-network-fastai-starter,Tabular Playground Series - Mar 2021
430,55786124,853.0,0.8839562585465777,2,4,/manujosephv/tps-march-pytorch-tabular-starter-notebook,Tabular Playground Series - Mar 2021
431,55786124,853.0,0.8839562585465777,2,4,/manujosephv/tps-march-pytorch-tabular-starter-notebook,Tabular Playground Series - Mar 2021
432,55562729,860.0,,9,11,/halilakkaynak/tab-march-eda,Tabular Playground Series - Mar 2021
433,58083712,856.0,0.883900030992674,0,0,/fanbyprinciple/fastai-neural-net-tabular-mar21,Tabular Playground Series - Mar 2021
434,88453963,858.0,,2,4,/ranjeetshrivastav/tabular-playground-series-mar-2021,Tabular Playground Series - Mar 2021
435,58398660,879.0,,0,0,/daood911/lightgbm-optuna-baseline,Tabular Playground Series - Mar 2021
436,55569381,886.0,,0,0,/anirag/catboost-starter,Tabular Playground Series - Mar 2021
437,57318156,930.0,0.8823033555191782,6,2,/hirazawahiroshi/r-data-visualization-and-rf-baseline-tps-2021-03,Tabular Playground Series - Mar 2021
438,56795307,972.0,,0,0,/emstrakhov/kaggle-competition-mar-15-2021,Tabular Playground Series - Mar 2021
439,59404038,927.0,,2,7,/abhishekv5055/tabular-playground-classification-model,Tabular Playground Series - Mar 2021
440,57757703,952.0,,0,1,/ssingla/tabular-march-21-eda-randomforest,Tabular Playground Series - Mar 2021
441,58995964,979.0,,0,0,/oneoxo/tabular-playground-march-2021-neural-network,Tabular Playground Series - Mar 2021
442,56815236,993.0,,1,2,/borislavnovikov1/xgboost-binary-features,Tabular Playground Series - Mar 2021
443,55832943,994.0,0.8792543729284185,0,3,/kushagrachugh/tabular-playground-series-march-2021,Tabular Playground Series - Mar 2021
444,58329472,990.0,0.8778794875956373,0,2,/jarupula/tps-march-2021,Tabular Playground Series - Mar 2021
445,57744129,999.0,0.8767974227109422,0,1,/mikedev/simple-eda-and-random-forest-prediction,Tabular Playground Series - Mar 2021
446,58139210,1010.0,0.8767720196895327,0,1,/grzegorzlippe/get-started-mar-tabular-playground-competition,Tabular Playground Series - Mar 2021
447,55773147,1011.0,0.8732276377222499,0,2,/jackstapleton/tabplaymar-baseline,Tabular Playground Series - Mar 2021
448,58347072,1021.0,0.8755629533592835,2,11,/radofanantenana/tps-mar2021-with-keras,Tabular Playground Series - Mar 2021
449,56935040,1038.0,,0,5,/karandora/tps-march-2021-quick-guide-to-h2o-automl-in-r,Tabular Playground Series - Mar 2021
450,57026963,1041.0,0.7961254218406421,0,4,/daikikatsuragawa/tps-mar-2021-benchmark-using-h2o-automl,Tabular Playground Series - Mar 2021
451,57024616,1063.0,0.7482365828477303,0,5,/igorkruglov/tabular-playground-03-2021,Tabular Playground Series - Mar 2021
452,56584844,1071.0,,2,3,/drcapa/playground-series-mar-2021-tutorial,Tabular Playground Series - Mar 2021
453,55682747,1078.0,0.8694659612964429,2,6,/shanmukh05/tabular-playground-march-2021,Tabular Playground Series - Mar 2021
454,56237688,1105.0,,0,1,/vinicius20/get-started-mar-tabular-playground-competition,Tabular Playground Series - Mar 2021
455,58357139,1180.0,,0,0,/davefw/get-started-mar-tabular-playground-competition,Tabular Playground Series - Mar 2021
456,55724935,1077.0,,0,6,/kesavsivakumar/tab-pgrnd-k-best-features-xgboost-vs-catboost,Tabular Playground Series - Mar 2021
457,56895097,1157.0,0.8691016681187783,0,1,/jerinm/tabular-playground-series,Tabular Playground Series - Mar 2021
458,57437903,1204.0,0.7403811916042095,0,1,/kandachi/get-started-mar-tabular-playground-competition,Tabular Playground Series - Mar 2021
459,62274336,1072.0,,0,4,/sourabhy/tps-march-under-over-sampling-eda-and-models,Tabular Playground Series - Mar 2021
460,56894811,1215.0,0.8665547054743874,2,2,/bagusbpg/my-6th-notebook,Tabular Playground Series - Mar 2021
461,56170747,1220.0,0.8454173287761955,0,10,/titericz/rapids-eda-target-encoding-feature-search,Tabular Playground Series - Mar 2021
462,56003128,1226.0,,0,3,/mahmutozgekarakaya/auc-curve-for-one-hot-encoding-and-label-encoding,Tabular Playground Series - Mar 2021
463,58377993,1242.0,0.8132317279733536,6,10,/vaishnavipatil4848/tabular-playground-march-2021,Tabular Playground Series - Mar 2021
464,58377993,1242.0,0.8132317279733536,6,10,/vaishnavipatil4848/tabular-playground-march-2021,Tabular Playground Series - Mar 2021
465,55566030,1252.0,0.813579274261961,0,5,/sunaysawant/tabular-playground-mar-21-rf,Tabular Playground Series - Mar 2021
466,56128930,1253.0,0.813579274261961,0,3,/shweta0910/tabular-playground-mar-21-ml-rf,Tabular Playground Series - Mar 2021
467,55999489,1266.0,,2,8,/asimzahid/tps-march-h2o-automl,Tabular Playground Series - Mar 2021
468,58348567,1275.0,0.3610991678132863,0,1,/black9t/sgdclassifier,Tabular Playground Series - Mar 2021
469,56625593,1283.0,0.7882547087069068,0,2,/tracyporter/tab-mar-21,Tabular Playground Series - Mar 2021
470,58486630,1307.0,,0,2,/keenborder/super-learner-one-hot-encoding,Tabular Playground Series - Mar 2021
471,56807541,1324.0,,0,1,/zachwel/test-fastai,Tabular Playground Series - Mar 2021
472,57919803,1309.0,,0,1,/anu4646/notebookb368f8e62e,Tabular Playground Series - Mar 2021
473,57857048,1348.0,,1,5,/rizdelhi/tps-march-2021,Tabular Playground Series - Mar 2021
474,55551846,1315.0,0.7692685569213266,3,12,/benfraser/fastai-tabular-classification,Tabular Playground Series - Mar 2021
475,57386571,1322.0,,0,1,/praveenmaripeti/tps-mar-21-feature-selection-techniques-catboost,Tabular Playground Series - Mar 2021
476,60401889,1345.0,,0,0,/shrutimehendale/tabular-playground-series-march-2021,Tabular Playground Series - Mar 2021
477,57888778,1340.0,,0,1,/mminguc/tps-mar,Tabular Playground Series - Mar 2021
478,56811085,1334.0,,0,1,/dspetrenko/pipeline-poc,Tabular Playground Series - Mar 2021
479,58482428,1342.0,0.7694728803173737,0,4,/vishalrossi/tab-march-classification,Tabular Playground Series - Mar 2021
480,55746511,1335.0,0.7567755447751661,0,5,/thrasy/tps-2021-03-quick-and-dirty-classifiers-testing,Tabular Playground Series - Mar 2021
481,62379249,1337.0,,4,17,/mahmoudlimam/target-encoding-with-gini-index,Tabular Playground Series - Mar 2021
482,55779918,1349.0,,3,18,/subinium/tps-march-eda-dimension-reduction,Tabular Playground Series - Mar 2021
483,57567698,1355.0,,2,7,/prithviraj7387/tabular-playground-eda,Tabular Playground Series - Mar 2021
484,58399852,1365.0,,0,2,/hugoortega/tabular-playground-series-mar-2021,Tabular Playground Series - Mar 2021
485,55965947,1408.0,,0,1,/mohammedsohailabrar/tabular-playground-march,Tabular Playground Series - Mar 2021
486,57789850,1429.0,0.752690287472709,1,4,/kkmax1015/tabular-featureengineering-with-xfeat-for-beginner,Tabular Playground Series - Mar 2021
487,57702155,1488.0,0.5,0,1,/ezzzio/tabular-playground-march-2021,Tabular Playground Series - Mar 2021
488,55627510,34.0,0.935672514619883,0,2,/uozcan12/2021-machine-learning,2021-기계학습
489,62817975,2.0,,0,1,/legoshi/bms-resnet-lstm,Bristol-Myers Squibb – Molecular Translation
490,58067342,13.0,,2,9,/sorkun/bms-mt-stereochemical-layer-prediction,Bristol-Myers Squibb – Molecular Translation
491,55922237,18.0,,2,7,/nofreewill/resize-images,Bristol-Myers Squibb – Molecular Translation
492,55809705,20.0,,10,91,/yasufuminakama/molecular-translation-naive-baseline,Bristol-Myers Squibb – Molecular Translation
493,55757597,23.0,69.33338201838315,16,70,/andypenrose/genetic-algorithm-for-naive-baseline,Bristol-Myers Squibb – Molecular Translation
494,65541184,24.0,,0,5,/stassl/bms-competition-stats,Bristol-Myers Squibb – Molecular Translation
495,61483167,47.0,,0,23,/kozodoi/computing-dataset-mean-and-std,Bristol-Myers Squibb – Molecular Translation
496,59907120,50.0,,4,24,/affjljoo3581/bms-molecular-translation-train-inchi-tokenizer,Bristol-Myers Squibb – Molecular Translation
497,60822255,59.0,4.945833343647963,10,26,/ivanmordovetc/inchi-efficientnetb7-25-epochs-inference,Bristol-Myers Squibb – Molecular Translation
498,59967366,66.0,,33,39,/tuckerarrants/inchi-allowed-external-data,Bristol-Myers Squibb – Molecular Translation
499,63584825,81.0,,0,3,/interneuron/moldalle,Bristol-Myers Squibb – Molecular Translation
500,58363603,95.0,,2,24,/wuliaokaola/bmsmt-0331-normalize-your-predictions,Bristol-Myers Squibb – Molecular Translation
501,55917968,131.0,,2,5,/kalfirst/bristol-myers-squibb-count-atom,Bristol-Myers Squibb – Molecular Translation
502,62001396,157.0,,2,20,/michaelwolff/bms-inchi-cropped-img-sizes-for-best-resolution,Bristol-Myers Squibb – Molecular Translation
503,62842677,164.0,4.65845622182559,7,34,/kirderf/basic-postp-with-different-submissions,Bristol-Myers Squibb – Molecular Translation
504,57365248,230.0,,3,16,/akhileshdkapse/learn-image-embedding-via-unet-tpu-part-i,Bristol-Myers Squibb – Molecular Translation
505,55752331,238.0,,1,9,/paulorzp/denoise-images,Bristol-Myers Squibb – Molecular Translation
506,62898493,241.0,,0,12,/wentixiaogege/inchi-efficientnetb7-inference-public-weights,Bristol-Myers Squibb – Molecular Translation
507,55725370,271.0,75.85775713751711,0,5,/mohamed3abdelrazik/molecular-translation-naive-baseline,Bristol-Myers Squibb – Molecular Translation
508,58704309,293.0,,7,74,/bjoernholzhauer/bristol-myers-squibb-eda-and-preparing-data,Bristol-Myers Squibb – Molecular Translation
509,58009744,345.0,,0,4,/jcesquiveld/generate-inchi-strings-with-lstm,Bristol-Myers Squibb – Molecular Translation
510,63808146,350.0,,0,0,/liucong12601/inchi-preprocess-v2,Bristol-Myers Squibb – Molecular Translation
511,58211869,394.0,,0,1,/kalabanga/moleculartraintestsplit,Bristol-Myers Squibb – Molecular Translation
512,56619706,584.0,,0,3,/rssrwn/inchi-tokenisation,Bristol-Myers Squibb – Molecular Translation
513,58472798,587.0,,0,8,/moeinshariatnia/cnn-rnn-cnn-pretraining-w-regression-preprocess,Bristol-Myers Squibb – Molecular Translation
514,55982263,609.0,,28,93,/pasewark/pytorch-resnet-lstm-with-attention,Bristol-Myers Squibb – Molecular Translation
515,55671845,691.0,,11,62,/ammarali32/molecular-translation-simple-training-starter,Bristol-Myers Squibb – Molecular Translation
516,60834219,708.0,,0,1,/tchaye59/mt-tfrecord-custom-vocab,Bristol-Myers Squibb – Molecular Translation
517,56651513,721.0,69.13775971204856,0,9,/ghaiyur/baseline-starter,Bristol-Myers Squibb – Molecular Translation
518,58334748,726.0,,8,15,/afajohn/data-loading-starter,Bristol-Myers Squibb – Molecular Translation
519,56047478,736.0,,18,67,/wineplanetary/understanding-inchi-format-and-arrange-train-label,Bristol-Myers Squibb – Molecular Translation
520,57177798,740.0,73.54790237574791,0,1,/saztorralba/moleculartranslation-autoregressivelstmnoimages,Bristol-Myers Squibb – Molecular Translation
521,56344889,744.0,,6,15,/accountstatus/using-cnn-and-ctc-for-prediction,Bristol-Myers Squibb – Molecular Translation
522,64850480,747.0,,0,0,/yeayates21/bms-mt-simple-tree-based-bucket-response-model,Bristol-Myers Squibb – Molecular Translation
523,55936062,751.0,,3,13,/arka47/convlstm-pytorch-skeleton,Bristol-Myers Squibb – Molecular Translation
524,55746812,754.0,75.85775713751711,0,7,/poornap/molecular-translation-eda-text-generation-model,Bristol-Myers Squibb – Molecular Translation
525,56141229,765.0,,12,29,/mnavaidd/molecular-translation-tensorflow,Bristol-Myers Squibb – Molecular Translation
526,56673025,774.0,,3,17,/juansensio/e2e-transformer-image-captioning-example,Bristol-Myers Squibb – Molecular Translation
527,56127299,782.0,76.15839557180591,26,51,/maksymshkliarevskyi/bms-mol-tr-approaches-eda-denoise-baseline,Bristol-Myers Squibb – Molecular Translation
528,62450249,801.0,,0,1,/sambhavsg/bms-baseline-inchi-first-layer-train-tf-keras,Bristol-Myers Squibb – Molecular Translation
529,57087746,810.0,110.13610359518464,0,1,/sanjitschouhan/molecular-transalation,Bristol-Myers Squibb – Molecular Translation
530,56177275,817.0,,24,183,/ihelon/molecular-translation-exploratory-data-analysis,Bristol-Myers Squibb – Molecular Translation
531,59130868,818.0,,0,3,/drcapa/bms-molecular-translation-tutorial,Bristol-Myers Squibb – Molecular Translation
532,62753835,1.0,,2,26,/harangdev/shopee-embedding-visualizations-before-after-inb,Shopee - Price Match Guarantee
533,56796729,5.0,,0,27,/aerdem4/memory-efficient-parallel-string-matching,Shopee - Price Match Guarantee
534,56689757,16.0,,6,22,/vicioussong/rapids-tfidfvectorizer-cv-0-734,Shopee - Price Match Guarantee
535,56272468,14.0,,72,353,/cdeotte/rapids-cuml-tfidfvectorizer-and-knn,Shopee - Price Match Guarantee
536,57198261,18.0,,20,196,/slawekbiel/arcface-explained,Shopee - Price Match Guarantee
537,61350506,19.0,0.652115291126869,2,50,/nicksergievskiy/pytorch-is-all-you-need-tfidf,Shopee - Price Match Guarantee
538,58724686,21.0,,70,244,/ishandutta/v7-shopee-indepth-eda-one-stop-for-all-your-needs,Shopee - Price Match Guarantee
539,58391394,26.0,,2,13,/tanulsingh077/code-for-data-generation-for-siamese-training,Shopee - Price Match Guarantee
540,56389748,30.0,,15,36,/super13579/lb-0-6-up-image-retrieval-by-euclidean-effinet,Shopee - Price Match Guarantee
541,58747993,33.0,0.6458979638398537,0,3,/namgalielei/shopeeeffb3-submission,Shopee - Price Match Guarantee
542,62610706,31.0,,2,9,/atmguille/shopee-object-detection-generate-data,Shopee - Price Match Guarantee
543,56219838,37.0,0.5737041085826271,2,6,/takusid/sample-submit,Shopee - Price Match Guarantee
544,59506645,45.0,,3,9,/jacob34/lb-probing-product-overlap-shared,Shopee - Price Match Guarantee
545,56438333,66.0,,1,36,/ragnar123/shopee-training-baseline,Shopee - Price Match Guarantee
546,60038837,73.0,,38,107,/heyytanay/shopee-eda-understanding-the-competition,Shopee - Price Match Guarantee
547,60481612,85.0,,3,42,/chienhsianghung/shopee-text-img-embedding-colab-enabled,Shopee - Price Match Guarantee
548,59097495,96.0,,0,11,/lhagiimn/shopee-tf-with-tpu-256x256-tfrecs,Shopee - Price Match Guarantee
549,59593168,88.0,,0,2,/chihantsai/b3-try,Shopee - Price Match Guarantee
550,61878847,105.0,0.7360451714616048,0,0,/joshualancaster/arcface-submission,Shopee - Price Match Guarantee
551,58584526,111.0,0.6975129706864296,0,3,/vargeek/unsupervised-image-text-baseline,Shopee - Price Match Guarantee
552,57522764,114.0,,5,16,/tmhrkt/shopee-cv-splitting-way,Shopee - Price Match Guarantee
553,58647031,128.0,0.7218771040642263,8,51,/muhammad4hmed/you-need-more-tensors-in-neighbourhood,Shopee - Price Match Guarantee
554,56674666,131.0,,2,6,/mnavaidd/shopee-rapids-tfidfvectorizer,Shopee - Price Match Guarantee
555,56814836,172.0,,0,24,/rohitsingh9990/shopee-error-analysis,Shopee - Price Match Guarantee
556,63592770,148.0,,0,0,/toshihikok/148th-nfnet-l0-nfnet-l1-ensemble-inference,Shopee - Price Match Guarantee
557,57535074,165.0,0.6814018614169242,3,17,/karthur10/resnet-sbert-unsupervised-baseline,Shopee - Price Match Guarantee
558,59114765,160.0,,0,3,/jcpser/shoppe-text-augmenter-2,Shopee - Price Match Guarantee
559,58196164,157.0,,0,3,/xfffrank/shopee-eda-basic,Shopee - Price Match Guarantee
560,59296017,170.0,,0,4,/alturutin/shopee-tfrecords,Shopee - Price Match Guarantee
561,60813553,207.0,,3,17,/ankursingh12/shopee-swav-training,Shopee - Price Match Guarantee
562,60826782,894.0,0.6894271770027656,0,13,/anlgrbz/embed-type-optimum-threshold-search-inference,Shopee - Price Match Guarantee
563,63135566,313.0,,0,0,/dpaul891/train-model1-image-only,Shopee - Price Match Guarantee
564,58945703,437.0,,2,11,/abhishekvermasg1/eda-wordcloud-indo-eng-insights,Shopee - Price Match Guarantee
565,62263903,409.0,,7,11,/nickthenick23/shopee-fast-indonesian-english-translator-offline,Shopee - Price Match Guarantee
566,60826682,773.0,,4,12,/zakarii/optimum-threshold-25-000,Shopee - Price Match Guarantee
567,58688595,759.0,,5,23,/xuxu1234/you-need-more-tensors-in-neighbourhood,Shopee - Price Match Guarantee
568,59112290,194.0,,0,6,/manwithaflower/shopee-bert-images,Shopee - Price Match Guarantee
569,60835892,449.0,0.5625415498108474,0,4,/jackiemai/ensemble-model,Shopee - Price Match Guarantee
570,57790829,452.0,,0,7,/darknesszx/image-text-baseline1,Shopee - Price Match Guarantee
571,56237838,471.0,0.586269235874889,13,50,/manabendrarout/image-and-text-eda-very-naive-model,Shopee - Price Match Guarantee
572,61058202,501.0,,1,6,,Shopee - Price Match Guarantee
573,60358316,530.0,0.063250574325154,0,7,/harshitt21/shopee-arcface,Shopee - Price Match Guarantee
574,60694131,533.0,,25,69,/debarshichanda/pytorch-supervised-contrastive-learning,Shopee - Price Match Guarantee
575,57646265,539.0,,0,7,/snnclsr/shopee-eda-starter-images-titles,Shopee - Price Match Guarantee
576,56285851,576.0,0.5594042436712802,31,66,/chumajin/eda-of-shopee-for-starter,Shopee - Price Match Guarantee
577,59289872,638.0,0.7078645018706082,1,7,/ahmedewida/unsupervised-baseline-arcface,Shopee - Price Match Guarantee
578,59289872,638.0,0.7078645018706082,1,7,/ahmedewida/unsupervised-baseline-arcface,Shopee - Price Match Guarantee
579,59795932,770.0,,6,28,/hongym7/ocr-tutorial-feat-tesseract,Shopee - Price Match Guarantee
580,56645682,448.0,,17,43,/wolfgang91/shopee-eda-hamming-distance-and-sentence-embedding,Shopee - Price Match Guarantee
581,56957815,684.0,,0,1,/masatouchi/eda-of-shopee-for-starter,Shopee - Price Match Guarantee
582,57069678,700.0,,0,5,/jdoesv/sentence-level-embeddings-as-features,Shopee - Price Match Guarantee
583,60890256,712.0,0.6314768583413926,7,28,/taherhaggui/modelisation-using-tf-efficienet,Shopee - Price Match Guarantee
584,59277505,428.0,,0,2,/dharmiksv/notebook7cc69ca39a,Shopee - Price Match Guarantee
585,58617401,728.0,,1,9,/weiheli/qwq-baseline,Shopee - Price Match Guarantee
586,59933552,733.0,,0,4,/izotov/idg-shopee-training-eff-b4,Shopee - Price Match Guarantee
587,61535698,758.0,,0,6,/nokokgl/shopee-pytorch-resnet50-tfidf-faiss,Shopee - Price Match Guarantee
588,61166037,821.0,,0,3,/haruhiko/evaluate-ocr,Shopee - Price Match Guarantee
589,56905583,319.0,0.586269235874889,2,9,/santoshd3/shopee,Shopee - Price Match Guarantee
590,60425689,349.0,,1,2,/michaelqq/shopee-data-analysis-correct-wrong-labels,Shopee - Price Match Guarantee
591,62468751,370.0,,0,7,/zachmayer/pairwise-dataset,Shopee - Price Match Guarantee
592,62327207,971.0,,0,2,/cyberpunk317/shopee-product-matching-full,Shopee - Price Match Guarantee
593,56303965,870.0,0.5737041085826271,4,22,/piantic/simple-baseline,Shopee - Price Match Guarantee
594,59865987,912.0,,0,5,/atsushiiwasaki/speed-up-the-inner-product-for-cosine-similarity,Shopee - Price Match Guarantee
595,61654622,837.0,0.7327534300564157,0,0,/lizhaonan/nfnet-l0-efficientnet-b5-ensemble-inference,Shopee - Price Match Guarantee
596,60898077,741.0,,0,0,/brucesacrifice/second-submit,Shopee - Price Match Guarantee
597,60898077,741.0,,0,0,/brucesacrifice/second-submit,Shopee - Price Match Guarantee
598,57608645,807.0,0.4903473006200387,5,15,/tomohiroh/shopee-autoencoder-knn,Shopee - Price Match Guarantee
599,61558558,817.0,,0,0,/leomlenthusiast/find-text-from-images,Shopee - Price Match Guarantee
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628,60144642,1393.0,,2,7,/eneszvo/clean-wrong-labels-speed-up-with-bktree,Shopee - Price Match Guarantee
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630,59094556,1497.0,0.7033742473523752,17,147,/finlay/unsupervised-image-text-baseline-in-20min,Shopee - Price Match Guarantee
631,59263343,1506.0,0.3778011441539142,4,40,/sunshinesyc/image-text-baseline,Shopee - Price Match Guarantee
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640,57917001,1684.0,,3,5,/reppy4620/tfbertmodel-arcmargin-tpu-training,Shopee - Price Match Guarantee
641,57257777,1697.0,,1,17,/nativityinblack/baseline,Shopee - Price Match Guarantee
642,56755502,1713.0,0.5958288597971045,52,159,/maksymshkliarevskyi/shopee-before-we-start-eda-phash-baseline,Shopee - Price Match Guarantee
643,56334208,1742.0,,1,7,/dschettler8845/visual-eda-baseline-shopee,Shopee - Price Match Guarantee
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646,57007619,1743.0,,2,7,/uthamkanth/shopee-text-modelling-and-its-visual-outputs,Shopee - Price Match Guarantee
647,57833249,1784.0,,0,8,/catadanna/result-for-the-3-test-images-using-text,Shopee - Price Match Guarantee
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649,61754935,1816.0,,0,1,/ugurca/unsupervised-image-text-baseline-in-20m-662277,Shopee - Price Match Guarantee
650,60897619,1820.0,0.701776083053513,0,0,/parkharit/rapids-tfidfvectorizer-cv-0-700,Shopee - Price Match Guarantee
651,60003890,1851.0,0.701776083053513,0,3,/carsonzhe/pretrain-img-tfidf,Shopee - Price Match Guarantee
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653,61975660,1884.0,0.701776083053513,0,0,/uppalrishabh/notebookddb17e26ae,Shopee - Price Match Guarantee
654,57939530,1715.0,,20,55,/srcecde/shoppee-eda-fuzzymatch-phash-cosinesim-tfidf,Shopee - Price Match Guarantee
655,58302863,1907.0,,8,58,/xhlulu/shopee-generate-data-for-triplet-loss,Shopee - Price Match Guarantee
656,56593149,1916.0,,21,29,/accountstatus/shopee-competition-using-bert-model,Shopee - Price Match Guarantee
657,59434435,1905.0,,0,4,/sandersli/shopee-image-triplets-tfrecs,Shopee - Price Match Guarantee
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659,61296717,1935.0,0.6950641915736059,0,2,/bargavjagatha/rapids-effecientnet-tfidfvectorizer,Shopee - Price Match Guarantee
660,61744545,1943.0,0.6881478131071146,0,0,/chloebryant/working-with-images-and-text-c8a84c,Shopee - Price Match Guarantee
661,61745212,2001.0,0.6408600659170167,0,9,/ricopue/fast-sklearn-pairwise-distances-chunked,Shopee - Price Match Guarantee
662,60874401,2017.0,,1,5,/alibaba19/fastai-arcface-pipeline-training,Shopee - Price Match Guarantee
663,58133547,2035.0,,16,112,/andradaolteanu/i-shopee-text-prep-fe-image-augmentation,Shopee - Price Match Guarantee
664,60285473,2037.0,,0,1,/claire2021/nlp-tfidf,Shopee - Price Match Guarantee
665,61064839,2028.0,0.658064566612688,0,1,/yehoonjoo/shopee-detecting-product-similarity,Shopee - Price Match Guarantee
666,59768499,2027.0,0.652137647546705,0,0,/mendelevium/efficientnet-embedding-tf-idf,Shopee - Price Match Guarantee
667,62501516,2040.0,0.6415573878447065,0,0,/ruhong/shopee-product-matching,Shopee - Price Match Guarantee
668,60969165,2058.0,,3,27,/realsid/stratifiedgroupkfold-using-sklearn,Shopee - Price Match Guarantee
669,57482626,2056.0,,53,153,/underwearfitting/pytorch-densenet-arcface-validation-training,Shopee - Price Match Guarantee
670,56342175,2061.0,,4,22,/bguberfain/clip-baseline,Shopee - Price Match Guarantee
671,61385088,2099.0,,2,18,/yukiohkawa/shopee-data-check,Shopee - Price Match Guarantee
672,57067972,2118.0,0.6256980542533224,0,7,/pritommojumder/shopee-price-matching-experiment,Shopee - Price Match Guarantee
673,59903796,2137.0,,0,2,/bernhard1/compx560,Shopee - Price Match Guarantee
674,58014421,2148.0,,7,51,/mohneesh7/shopee-challenge-eda-nlp-on-title-ocr,Shopee - Price Match Guarantee
675,62242121,2156.0,,0,0,/taaffeitegem/shopee-lite-v-7,Shopee - Price Match Guarantee
676,58808721,2192.0,,1,6,/lexplua/shopee-phash-playground,Shopee - Price Match Guarantee
677,61781991,2195.0,,4,16,/kcostya/ride-the-lightning-training,Shopee - Price Match Guarantee
678,56561453,2198.0,,16,73,/isaienkov/shopee-data-understanding-and-analysis,Shopee - Price Match Guarantee
679,61444283,2222.0,0.5737041085826271,0,0,/wannikasonarra/shopee-product,Shopee - Price Match Guarantee
680,58628188,2255.0,0.5594042436712802,3,8,/yasinnaal/shopee-price-match-guarantee-yasin,Shopee - Price Match Guarantee
681,60087357,2287.0,0.5411986658553671,0,0,/harikunderu/shopee-0-523-with-minimal-steps,Shopee - Price Match Guarantee
682,59852529,2313.0,,1,4,/drcapa/shopee-price-match-guarantee-starter,Shopee - Price Match Guarantee
683,59852440,2319.0,,34,41,/shanmukh05/shopee-pmg-tensorflow-tpu-training,Shopee - Price Match Guarantee
684,57280337,2328.0,,0,1,/swhong409/edatest,Shopee - Price Match Guarantee
685,73840119,2336.0,,1,17,/mohamedbakrey/m-b-shopee-product-matching,Shopee - Price Match Guarantee
686,58409111,2352.0,,0,1,/jasonhuanghao/cnnnn,Shopee - Price Match Guarantee
687,62163261,2357.0,,0,2,/alangoncalves/alan-projeto-redes-neurais,Shopee - Price Match Guarantee
688,56262402,2372.0,0.4611875272197899,0,3,/swathithiruveravi/eda-and-naive-approach,Shopee - Price Match Guarantee
689,60919682,2398.0,,0,0,/jinal17/cnn-sivyati,Shopee - Price Match Guarantee
690,60919682,2398.0,,0,0,/jinal17/cnn-sivyati,Shopee - Price Match Guarantee
691,63749528,2402.0,,0,0,/yukfaiwong/shopee-full-model,Shopee - Price Match Guarantee
692,58524765,2417.0,,1,40,/coder247/similarity-using-word2vec-text,Shopee - Price Match Guarantee
693,61020306,2424.0,0.0,0,0,/smits31/shopee-with-pretrained-models,Shopee - Price Match Guarantee
695,56655439,7.0,,3,13,/sauravmaheshkar/herbarium-2021-pytorch-starter-weights-biases,Herbarium 2021 - Half-Earth Challenge - FGVC8
697,67015267,1321.0,0.8881381049112212,3,40,/kidnarcissus/hw1-20210624-merge-model,ML2021Spring-hw1
698,58772028,18.0,,0,0,/michellewatson/mwatson-syde522-a2-v10,SYDE 522 (Winter 2021)
699,58841686,59.0,0.98025,0,1,/wzafar/starter-kit,SYDE 522 (Winter 2021)
700,59101787,4.0,,0,0,/mikhailyurasov/notebooke7d9fa1145,Plant Pathology 2021 - FGVC8
701,73115967,53.0,0.860599334073251,0,0,/alekseyeliseev/pytorchlightning-efficientnetv2-inference-tsfm,Plant Pathology 2021 - FGVC8
702,57834819,57.0,,0,2,/crissallan/eda-sample-images-visualization,Plant Pathology 2021 - FGVC8
703,57810217,9.0,,0,3,/ashish2001/tfrecords-plant-pathology,Plant Pathology 2021 - FGVC8
704,60639998,23.0,,0,3,/memorylorry/resize512-plant-pathology-2021-fgvc8,Plant Pathology 2021 - FGVC8
705,66054797,29.0,0.8419903810580825,0,0,/prepare4/efficient-b4-b5,Plant Pathology 2021 - FGVC8
706,62783195,61.0,0.1775804661487236,0,0,/rustyelectron/plant-path-inference-resnet200d,Plant Pathology 2021 - FGVC8
707,63581353,67.0,,1,0,,Plant Pathology 2021 - FGVC8
708,65703799,74.0,,2,3,/aithammadiabdellatif/background-removal,Plant Pathology 2021 - FGVC8
709,63341360,52.0,,0,1,/congnguyen8201/int3414-22-n11-training,Plant Pathology 2021 - FGVC8
710,62683841,56.0,0.76267110617832,0,4,/vgarshin/plant-efficientnet-submit-pytorch,Plant Pathology 2021 - FGVC8
711,57492085,111.0,,0,5,/datasciencegeek/eda-plantpathology2021-fgvc8,Plant Pathology 2021 - FGVC8
712,61979687,83.0,,1,5,/coldfir3/plant-pathology-2021-dataset-rescaled-to-600x400px,Plant Pathology 2021 - FGVC8
713,61100213,96.0,,0,1,/mansigp/plant-leaf-mobile-net,Plant Pathology 2021 - FGVC8
714,57181680,124.0,,0,7,/nickuzmenkov/plant-pathology-2021-making-tfrecords,Plant Pathology 2021 - FGVC8
715,57163306,94.0,0.6078431372549021,0,2,/zachwel/fastai-cnn-learner-2,Plant Pathology 2021 - FGVC8
716,64009018,70.0,,0,0,/qianzxz/fork-of-pytorchlightning-efficientnet-focalloss-in,Plant Pathology 2021 - FGVC8
717,64038037,106.0,0.8227894931557512,0,0,/sakshi12345/main-sub,Plant Pathology 2021 - FGVC8
718,64019136,84.0,0.8004439511653717,0,1,/tylerswann/plant-pathology-2021-classification,Plant Pathology 2021 - FGVC8
719,74074703,108.0,0.7652608213096557,0,2,/bcghost/plant-pathology,Plant Pathology 2021 - FGVC8
720,58847201,117.0,,0,17,/shanmukh05/plant-pathology-2k21-baseline-gpu-training,Plant Pathology 2021 - FGVC8
721,61983148,137.0,,1,6,/antoreepjana/multi-label-image-classification-plant-pathology,Plant Pathology 2021 - FGVC8
722,60366892,103.0,,0,9,/ljh0128/multi-label-data-split-method,Plant Pathology 2021 - FGVC8
723,58021932,95.0,,0,0,/tunhunhminh/2021-fgvc8-efn-net-train,Plant Pathology 2021 - FGVC8
724,64041706,109.0,,0,0,/damianib/tfrecords-plant-pathology,Plant Pathology 2021 - FGVC8
725,59274087,85.0,,5,31,/jirkaborovec/plant-pathology-with-lightning,Plant Pathology 2021 - FGVC8
726,64028921,129.0,0.7614132445430997,0,0,/tringuyenminh1204/pp-2021-new,Plant Pathology 2021 - FGVC8
727,63334832,73.0,,22,233,/ayuraj/experiment-tracking-with-weights-and-biases,Plant Pathology 2021 - FGVC8
728,59575328,140.0,,0,0,/teykaihong/fgvc8-fastai-training1,Plant Pathology 2021 - FGVC8
729,63141004,152.0,,14,10,/mreenav/plant-pathology-basic-cnn,Plant Pathology 2021 - FGVC8
730,61349251,150.0,0.790972992970773,0,0,/labdhisheth/plant-pathology-inceptionv3-2,Plant Pathology 2021 - FGVC8
731,65924413,165.0,,3,6,/lucaspillapimentel/densenet169-transfer-learning-fgvc8-2021,Plant Pathology 2021 - FGVC8
732,57391136,185.0,,4,38,/buinyi/understanding-the-evaluation-metric-cv,Plant Pathology 2021 - FGVC8
733,62009423,182.0,,2,16,/amartyabhattacharya/reaching-98-59-f1-score-using-transfer-learning,Plant Pathology 2021 - FGVC8
734,91920491,235.0,,0,0,/svyatoslavsokolov/plant-pathology-for-students,Plant Pathology 2021 - FGVC8
735,63876689,179.0,,0,5,/duythanhng/pp2021-keras-fine-tune,Plant Pathology 2021 - FGVC8
736,57220856,161.0,,7,45,/pegasos/plant2021-pytorch-lightning-starter-training,Plant Pathology 2021 - FGVC8
737,63810717,178.0,0.1775804661487236,1,2,/falloutbabe/pp-2021-multi-label-model,Plant Pathology 2021 - FGVC8
738,57327092,206.0,,0,9,/saurabhbagchi/pytorch-starter-wip,Plant Pathology 2021 - FGVC8
739,57192253,166.0,,5,21,/ankursingh12/fastai-plant2021-starter-training,Plant Pathology 2021 - FGVC8
740,60954134,213.0,0.2044923629829293,0,0,/vasumavani/plant-pathology-2021-submission,Plant Pathology 2021 - FGVC8
741,63450475,222.0,,2,5,/brendanartley/plant-pathology-2021-tfrecords,Plant Pathology 2021 - FGVC8
742,63951761,218.0,,0,0,/kirichenko17roman/pytorch-efficientnet,Plant Pathology 2021 - FGVC8
743,60235586,200.0,0.2096559378468367,0,1,/maxinstellar/transformer-vit-baseline,Plant Pathology 2021 - FGVC8
744,62629923,212.0,,0,1,,Plant Pathology 2021 - FGVC8
745,62067186,250.0,0.6632260451350352,0,0,/gb00000/plant-pathology-2021,Plant Pathology 2021 - FGVC8
746,64037594,183.0,,0,1,/ligala/pytorch-efficientnet,Plant Pathology 2021 - FGVC8
747,64037594,183.0,,0,1,/ligala/pytorch-efficientnet,Plant Pathology 2021 - FGVC8
748,64037594,183.0,,0,1,/ligala/pytorch-efficientnet,Plant Pathology 2021 - FGVC8
749,62864764,236.0,,0,1,/hoang18020566/cdcn-group10,Plant Pathology 2021 - FGVC8
750,64018796,291.0,0.7669256381798003,0,0,/hansoleom/submit-test,Plant Pathology 2021 - FGVC8
751,63105099,280.0,,0,1,/studywitht/densenets-freeze,Plant Pathology 2021 - FGVC8
752,60947066,310.0,,0,0,/whdcks877/plant-pathology,Plant Pathology 2021 - FGVC8
753,63132042,229.0,,0,0,/phannguyenthe/plant-resnet50,Plant Pathology 2021 - FGVC8
754,60538344,216.0,0.7672955974842767,2,1,/peterpetrov826/saving-apple-trees-with-fastai,Plant Pathology 2021 - FGVC8
755,62975602,242.0,0.7602293747687751,0,0,/markphillipsai/plants-fastai-train-and-infer,Plant Pathology 2021 - FGVC8
756,63802153,283.0,,0,0,/nikitakirpa/pytorch-efficientnet,Plant Pathology 2021 - FGVC8
757,63178151,247.0,0.7556048834628182,0,0,,Plant Pathology 2021 - FGVC8
758,62653798,268.0,0.7593044765075837,0,0,/jarxrr/ensemble,Plant Pathology 2021 - FGVC8
759,59579603,232.0,0.5897151313355534,0,1,/kingofarmy/resnet50-fgvc8-submission,Plant Pathology 2021 - FGVC8
760,63894168,285.0,,0,0,/konstantinitsi/pytorch-efficientnet-my-version,Plant Pathology 2021 - FGVC8
761,59916651,282.0,0.7585275619681829,0,7,/julichitai/visual-transformer-vit-baseline-training,Plant Pathology 2021 - FGVC8
762,64853926,238.0,0.7381798002219753,0,0,/huzeyfedegirmenci/plant-effnet-predict-87,Plant Pathology 2021 - FGVC8
763,63028209,262.0,,2,15,/ritvik1909/multi-label-image-classification,Plant Pathology 2021 - FGVC8
764,59426305,327.0,0.7545689974102848,0,2,/dhruv282/plant-pathology-notebook-v2,Plant Pathology 2021 - FGVC8
765,61933532,274.0,,0,2,/yowtshjhj/plant2021,Plant Pathology 2021 - FGVC8
766,64509846,277.0,0.7828708842027373,0,0,/nitekot/fork-of-inference-plant2021-detectron,Plant Pathology 2021 - FGVC8
767,63213913,292.0,0.7323344432112466,1,1,/longhainguyen/nh-m-1-chuy-n-c-ng-ngh-submission,Plant Pathology 2021 - FGVC8
768,60003226,308.0,,0,4,/ted0071/plant2021-preprocessing,Plant Pathology 2021 - FGVC8
769,63314096,293.0,,0,1,/tototohpl/group2-processing-data,Plant Pathology 2021 - FGVC8
770,63294642,297.0,0.6798372179060306,0,0,/ngothinhdz/cdcn-thinh,Plant Pathology 2021 - FGVC8
771,63876629,287.0,0.7197558268590454,0,10,/emorkrin/baseline-keras-17-04,Plant Pathology 2021 - FGVC8
772,61343460,334.0,0.6721420643729188,0,2,/chuck23233/full-trained-densenet,Plant Pathology 2021 - FGVC8
773,61321584,333.0,0.737254901960784,0,0,/alllancheung/notebook7dc05abc73,Plant Pathology 2021 - FGVC8
774,56992090,256.0,,11,17,/datafan07/plant-pathology-v-transformers-baseline-training,Plant Pathology 2021 - FGVC8
775,62333186,257.0,0.7371069182389937,2,7,/c7934597/plant2021-pytorch-lightning-starter-inference,Plant Pathology 2021 - FGVC8
776,63311403,299.0,0.6268590455049944,0,0,/bachhieu/nh-m-8,Plant Pathology 2021 - FGVC8
777,63906629,271.0,,6,6,/greynolan/plant-pathology-2021,Plant Pathology 2021 - FGVC8
778,66414251,337.0,0.6959674435812061,0,0,/teddy880511/fgvc8,Plant Pathology 2021 - FGVC8
779,60132755,312.0,0.4732889382167972,6,25,/arnabs007/apple-leaf-diseases-with-inceptionresnetv2-keras,Plant Pathology 2021 - FGVC8
780,64380154,323.0,,0,0,/devyacheslav/lightning-train-plant-pathology-2021,Plant Pathology 2021 - FGVC8
781,60103353,326.0,0.7248982611912687,0,1,/lanle793/plant-pathology-2021-fgcv8-fastai,Plant Pathology 2021 - FGVC8
782,63195793,335.0,0.2254901960784311,0,0,/hanguyen18020434/plant-pathology-2021-resnet50-detail-mode-v20mod,Plant Pathology 2021 - FGVC8
783,58821101,329.0,0.4228634850166484,0,0,/afridi10/plant-pathology-2021-submission,Plant Pathology 2021 - FGVC8
784,62846517,370.0,,0,1,/tunguyen240820/plant,Plant Pathology 2021 - FGVC8
785,62810629,357.0,0.7241583425823153,6,14,/daviddirethucus/plant-pathology-densenet169,Plant Pathology 2021 - FGVC8
786,63228006,381.0,0.6699963004069553,0,0,/anhtra/hehee,Plant Pathology 2021 - FGVC8
787,58430278,332.0,0.7214576396596372,0,0,/catwhisker/cs5489-project-submission-baseline,Plant Pathology 2021 - FGVC8
788,63252562,388.0,,0,0,/bonggg/notebooke6e8b09885,Plant Pathology 2021 - FGVC8
789,63260300,361.0,0.6906030336662966,1,1,/trinhtt/cdcn-cnn-model-zoo,Plant Pathology 2021 - FGVC8
790,62924231,344.0,0.713503514613392,1,2,/maxvandijck/plant-pathology,Plant Pathology 2021 - FGVC8
791,62683216,366.0,0.7180540140584537,0,0,/phmvithong/plant-pathology,Plant Pathology 2021 - FGVC8
792,60184383,374.0,,0,6,/adityakane/plant-pathology-2021-dataset-maker,Plant Pathology 2021 - FGVC8
793,63235322,368.0,0.7148723640399558,1,2,/francescomart/plant-classification-with-inception-v3-f1-0-857,Plant Pathology 2021 - FGVC8
794,76144048,377.0,0.7214206437291899,10,16,/ranjeetshrivastav/plant-pathology-2021-fgvc8-transfer-learning,Plant Pathology 2021 - FGVC8
795,58482293,380.0,,0,5,/jeremynadal/plantpathology2021-trained,Plant Pathology 2021 - FGVC8
796,63211291,355.0,,0,0,/fan141/plant-resnet50,Plant Pathology 2021 - FGVC8
797,56923964,418.0,,0,2,/mohammadasimbluemoon/plant-pathology-multi-class-2021,Plant Pathology 2021 - FGVC8
798,59560733,379.0,0.704735479097299,0,0,/hopeff/notebook1c3b14df11,Plant Pathology 2021 - FGVC8
799,63095214,398.0,,0,1,/minho119/resnet18-tez,Plant Pathology 2021 - FGVC8
800,63391616,382.0,,2,4,/dandierlean/dataset-evaluation,Plant Pathology 2021 - FGVC8
801,63146571,399.0,0.1772105068442471,0,0,/hngtrnchong/plant-pathology-cnn-model,Plant Pathology 2021 - FGVC8
802,63212828,400.0,,1,1,/thirupalanim/plant-pathology,Plant Pathology 2021 - FGVC8
803,63106932,427.0,,2,2,/nur988/plant-pathology-2021,Plant Pathology 2021 - FGVC8
804,64038656,412.0,0.5920088790233087,0,1,/jl18pg052/inference-notebook-for-plant-comp,Plant Pathology 2021 - FGVC8
805,62728536,426.0,0.1775804661487236,0,3,/artemygolovnev/cnn-keras-multi-label-classification,Plant Pathology 2021 - FGVC8
806,63301904,446.0,0.6242323344432115,0,0,/loilevan/restnet-nh-m8,Plant Pathology 2021 - FGVC8
807,57658187,436.0,0.0863485016648169,2,14,,Plant Pathology 2021 - FGVC8
808,57752331,445.0,0.6078801331853498,0,4,/kuboko/pp2021-pytorch-vgg-16-fine-tune-inference,Plant Pathology 2021 - FGVC8
809,64559460,452.0,,0,0,/xavierbarbier/plant-pathology-2021-fgvc8-eda,Plant Pathology 2021 - FGVC8
810,63801271,470.0,,0,4,/virajkadam/plant-pathology-apple-leaf-diseases,Plant Pathology 2021 - FGVC8
811,62818080,490.0,0.236958934517203,2,4,/stpeteishii/plant-pathology-densenet201,Plant Pathology 2021 - FGVC8
812,57543827,495.0,0.3719200887902337,0,1,/leeminwoo/pytorch-renet32,Plant Pathology 2021 - FGVC8
813,59852458,497.0,,1,11,/drcapa/plant-pathology-starter-eda-datagenerator,Plant Pathology 2021 - FGVC8
814,60309349,508.0,,0,8,/jabertuhin/multi-label-classification-training-with-pl,Plant Pathology 2021 - FGVC8
815,61453067,513.0,,0,1,/lucascouri/at-5-estat-stica-descritiva-plant-pathology,Plant Pathology 2021 - FGVC8
816,61380233,516.0,0.0763965963743987,0,3,/v1shal9/plant-pathology-prediction,Plant Pathology 2021 - FGVC8
817,63699975,517.0,0.3169071402145758,0,1,/csy1432/notebook6251d770cd,Plant Pathology 2021 - FGVC8
818,62560832,523.0,0.0,0,1,/ashery/plant-pathology-2021-fgvc8,Plant Pathology 2021 - FGVC8
819,57407818,521.0,,4,6,/dimakyn/plant-2021-densenet201-efficientnetb7-tpu,Plant Pathology 2021 - FGVC8
820,63244814,524.0,,0,1,/jena0001/analysis-and-preprocessing,Plant Pathology 2021 - FGVC8
821,61759897,535.0,0.2522382537920823,0,0,/jacobkutchi/plantpathology-jkutchi,Plant Pathology 2021 - FGVC8
822,61229240,539.0,0.2194228634850165,0,9,/jerifate/plant-pathology-2021-keras-model-inceptionv3,Plant Pathology 2021 - FGVC8
823,59984124,550.0,0.200517943026267,0,6,/traptrip/visual-transformer-vit-baseline-t2t,Plant Pathology 2021 - FGVC8
824,61597596,548.0,,0,1,/baokar7/plant-pathology-with-keras-and-transfer-learning,Plant Pathology 2021 - FGVC8
825,56924454,551.0,0.2128745837957824,1,26,/ateplyuk/plant-2021-starter,Plant Pathology 2021 - FGVC8
826,61018340,560.0,0.1775804661487236,0,0,/wonyongl/merged,Plant Pathology 2021 - FGVC8
827,61311143,562.0,,11,11,/lys620/opencv-eda-and-classification,Plant Pathology 2021 - FGVC8
828,57556342,580.0,,0,3,/arindamg/plant-pathology-efficientnet-93-val-acc,Plant Pathology 2021 - FGVC8
829,62108766,594.0,,0,3,/alexhernan/plants-training,Plant Pathology 2021 - FGVC8
830,62693413,600.0,0.1775804661487236,0,2,/tedjdchen/plant2021-project,Plant Pathology 2021 - FGVC8
831,64103877,609.0,,0,2,/suvoooo/plant-pathology-multilabel-inceptionv3,Plant Pathology 2021 - FGVC8
832,57681571,610.0,0.0837957824639289,0,0,/bekarysnurtay/bn-plant-pathology-efficientnet-b7,Plant Pathology 2021 - FGVC8
833,61081481,612.0,0.1499075101738809,0,3,/hyeonjin6/introduction-to-plant-pathology,Plant Pathology 2021 - FGVC8
834,80262515,625.0,,15,33,/mohamedbakrey/m-b-plant-pathology-2021-make-eda,Plant Pathology 2021 - FGVC8
835,66373384,55.0,,1,7,/spshota/coleridge-text-matching-and-ner-cnt,Coleridge Initiative - Show US the Data
836,66770265,13.0,0.6191122629478795,0,5,/trentb/coleridge-dataset-extractor,Coleridge Initiative - Show US the Data
837,61673654,96.0,0.5200566886437858,0,5,/eguidotti/test-data-are-not-fully-labeled,Coleridge Initiative - Show US the Data
838,67624328,4.0,,0,1,/naotous/coleridge-inspect-examples,Coleridge Initiative - Show US the Data
839,59813158,83.0,0.5330125973286067,1,27,/rohanrao/coleridge-string-matching-benchmark-in-r,Coleridge Initiative - Show US the Data
840,66329638,77.0,,0,1,/mfalfafa/coleridge-xlm-roberta-base-epoch-1-training,Coleridge Initiative - Show US the Data
841,61268486,184.0,,4,6,/ochaaaaaaan/doc2vec,Coleridge Initiative - Show US the Data
842,61897482,72.0,,0,5,/ht5brer/coleridge-initiative-named-entity-recognition,Coleridge Initiative - Show US the Data
843,63089781,9.0,,0,2,/tez6c32/coleridge-bert-masked-dataset-modeling-edit,Coleridge Initiative - Show US the Data
844,65809224,34.0,,0,2,/khubchandani/bert-masked-dataset-modeling,Coleridge Initiative - Show US the Data
845,64010594,122.0,,5,27,/mlconsult/100000-govt-datasets-api-json-to-df,Coleridge Initiative - Show US the Data
846,62737431,291.0,,2,10,/chienhsianghung/coleridge-initiative-naive-cv-local-validation,Coleridge Initiative - Show US the Data
847,67827573,179.0,0.5289401252542982,7,6,/abderrahimalakouche/bert-masked-language-modeling,Coleridge Initiative - Show US the Data
848,57698347,183.0,,2,5,/kuroyuli/eda-wordclouds-of-broad-categories,Coleridge Initiative - Show US the Data
849,66062597,128.0,0.5330125973286067,0,5,/rajat95gupta/string-matching-starter-implementation,Coleridge Initiative - Show US the Data
850,64355698,316.0,,2,11,/ajaypawar123/eda-text-processing-string-matching-beginners,Coleridge Initiative - Show US the Data
851,62457034,511.0,0.5253657609728292,1,9,/kartikbhargav/blazing-fast-eda-coleridge-baseline,Coleridge Initiative - Show US the Data
852,65532722,146.0,,1,15,/jt120lz/highlight-view,Coleridge Initiative - Show US the Data
853,62861949,325.0,0.5283826064746823,6,45,/gauravsahani/coleridge-initiative-let-s-show-us-the-data,Coleridge Initiative - Show US the Data
854,61150518,328.0,0.534232693647476,2,10,/jitshil143/coleridge-initiative-eda-baseline-model,Coleridge Initiative - Show US the Data
855,61150518,328.0,0.534232693647476,2,10,/jitshil143/coleridge-initiative-eda-baseline-model,Coleridge Initiative - Show US the Data
856,61428125,108.0,0.5305875612706091,18,65,/debarshichanda/plotly-let-s-see-the-data,Coleridge Initiative - Show US the Data
857,66247173,366.0,,0,1,/haiyunhu/coleridge-model-training-20210621,Coleridge Initiative - Show US the Data
858,62907284,192.0,0.5333375386362202,20,101,/chumajin/coleridge-initiative-eda-for-biginner,Coleridge Initiative - Show US the Data
859,57800237,384.0,0.534232693647476,22,133,/manabendrarout/tabular-data-preparation-basic-eda-and-baseline,Coleridge Initiative - Show US the Data
860,65266611,387.0,0.5177570880903232,0,2,/liuchungmeng/coleridge-predict-with-masked-dataset-modeling,Coleridge Initiative - Show US the Data
861,62005761,450.0,0.5336030852879813,0,2,/jarupula/colaridge-bert,Coleridge Initiative - Show US the Data
862,72708034,451.0,,0,2,/oleksandrsirenko/coleridge-initiative-rule-based-model,Coleridge Initiative - Show US the Data
863,66156113,498.0,,0,4,/razerspeed/coleridge-data-cleaned,Coleridge Initiative - Show US the Data
864,66399050,27.0,,1,9,/prateekagnihotri/efficient-matching-3m-dataset-names-in-30-mins,Coleridge Initiative - Show US the Data
865,62252219,153.0,0.5326135000315716,0,9,/samratthapa/very-simple-baseline-model-using-training-labels,Coleridge Initiative - Show US the Data
866,66046714,300.0,,0,3,/victorasso/speeding-up-json-files-readings-using-dask,Coleridge Initiative - Show US the Data
867,58859638,193.0,,1,8,/verracodeguacas/fast-sample-submission-coleridge-pandas-pickle,Coleridge Initiative - Show US the Data
868,63205577,275.0,0.536415835599879,2,35,/suryadeepti/mask-modelling,Coleridge Initiative - Show US the Data
869,63221790,196.0,,0,3,/shindeganesh/coleridge-mm-version-4,Coleridge Initiative - Show US the Data
870,71784960,225.0,,0,1,/ashishadhikari061/matching-mask-added-govt-data-model,Coleridge Initiative - Show US the Data
871,58751583,231.0,0.534232693647476,0,0,/nobatgeldi/coleridge-initiative-eda-baseline-model,Coleridge Initiative - Show US the Data
872,65238810,251.0,0.0308020554737506,0,5,/hsuchialun/show-us-the-data,Coleridge Initiative - Show US the Data
873,64369516,127.0,,0,0,/anuragtr/pytorch-bert-for-ner-v1,Coleridge Initiative - Show US the Data
874,65435027,712.0,,0,2,/ksnoeij/coleridge-matching-bert-ner-mlip27,Coleridge Initiative - Show US the Data
875,65961939,56.0,,0,0,/abdulkadirguner/314version-trials,Coleridge Initiative - Show US the Data
876,65122722,49.0,,0,0,/slashie/coleridge-ner-chain-v02-c04,Coleridge Initiative - Show US the Data
877,64470082,631.0,,0,2,/christosmavrikis/score-57ish-with-additional-govt-datasets,Coleridge Initiative - Show US the Data
878,62734993,626.0,0.0,0,1,/paoloantonuccio/notebooka5c6393d44,Coleridge Initiative - Show US the Data
879,64607794,88.0,0.2484835421990947,0,6,/ozanozgur/regex-search-and-keyword-elimination,Coleridge Initiative - Show US the Data
880,65540289,292.0,,0,0,/frederikeelsmann/data-analysis-notebook,Coleridge Initiative - Show US the Data
881,59935447,793.0,,0,1,/lukaszruczynski/poor-labeling-of-training-data,Coleridge Initiative - Show US the Data
882,63678537,612.0,,0,4,/ash1706/train-bert-base-ner,Coleridge Initiative - Show US the Data
883,158217443,756.0,,3,26,/nikitakudriashov/coleridge-initiative-baseline,Coleridge Initiative - Show US the Data
884,62987011,159.0,0.4833881336801295,0,0,/takeajioka/coleridge-predict-with-masked-dataset-modeling,Coleridge Initiative - Show US the Data
885,58014065,577.0,,7,15,/tungmphung/coleridge-initiative-local-score-computation,Coleridge Initiative - Show US the Data
886,61431168,587.0,0.4874839754402537,0,6,/armandmorin/show-us-data,Coleridge Initiative - Show US the Data
887,65532392,517.0,0.5337380636185417,0,2,/rezashokrzad/coleridge-matching-by-bert-ner,Coleridge Initiative - Show US the Data
888,57612638,1062.0,0.1700653491851035,0,6,/taruntiwarihp/coleridge-initiative-modelling,Coleridge Initiative - Show US the Data
889,57806707,905.0,0.0,0,3,/srcecde/coleridge-lsh-eda-json-to-dataframe,Coleridge Initiative - Show US the Data
890,57900824,38.0,0.3766168686773779,0,2,/jdoesv/heuristics-final,Coleridge Initiative - Show US the Data
891,58002192,1073.0,,0,6,/jamessorrell/spacy-ner-preprocessing,Coleridge Initiative - Show US the Data
892,61052199,1084.0,0.5332118393766103,62,351,/prashansdixit/coleridge-initiative-eda-baseline-model,Coleridge Initiative - Show US the Data
893,61052199,1084.0,0.5332118393766103,62,351,/prashansdixit/coleridge-initiative-eda-baseline-model,Coleridge Initiative - Show US the Data
894,57589331,1100.0,,3,6,/skeller/title-clustering-with-theme-detection,Coleridge Initiative - Show US the Data
895,57629638,1111.0,0.4430560514102106,2,8,/ahmedewida/na-ve-submission,Coleridge Initiative - Show US the Data
896,61186709,1205.0,,2,14,/adnaiksachin25/wordcloud-cosine-jaccard-sequencematcher,Coleridge Initiative - Show US the Data
897,65059125,1213.0,,0,0,/krutikadhavale/coleridge-initiative-eda-baseline-model,Coleridge Initiative - Show US the Data
898,65699738,917.0,,0,0,/matthijsneutelings/mlip-24-train-final-version,Coleridge Initiative - Show US the Data
899,65634247,972.0,,0,0,/heleenvisserman/mlip-5-de-woordzoekers-bert-literal-matching,Coleridge Initiative - Show US the Data
900,65232968,985.0,,0,0,/clararus/pytorch-bert-for-named-entity-recognition,Coleridge Initiative - Show US the Data
901,65441942,1266.0,0.0,0,0,/makkiemai/mlip14-citation-worthiness,Coleridge Initiative - Show US the Data
902,65441942,1266.0,0.0,0,0,/makkiemai/mlip14-citation-worthiness,Coleridge Initiative - Show US the Data
903,65656748,1570.0,0.0216708202405461,0,0,/peaceduck/coleridge-nlp-validation,Coleridge Initiative - Show US the Data
904,61385222,897.0,,0,5,/tthien/meow-baseline,Coleridge Initiative - Show US the Data
905,61437712,1304.0,0.534232693647476,0,1,/chandan5/notebookec7ff7e1f4,Coleridge Initiative - Show US the Data
906,65366756,912.0,0.3930310977894342,0,0,/lmgeertjes/mlip-coleridge-matching-bert-ner,Coleridge Initiative - Show US the Data
907,58656782,834.0,,0,5,/vishalsrinirao/coleridge-computing-evaluation-metrics,Coleridge Initiative - Show US the Data
908,62072601,971.0,,2,15,/abhishekvermasg1/v3-coleridge-extensive-eda,Coleridge Initiative - Show US the Data
909,65263968,1541.0,,0,0,/dgirzadas/coleridge-preselection-model,Coleridge Initiative - Show US the Data
910,64472848,1019.0,0.1034377852144812,0,0,/gerwindekruijf/coleridge-matching-bert-ner-new-model,Coleridge Initiative - Show US the Data
911,65615348,891.0,,0,0,/honghongzhu/mlip30-pattern-matching-and-scibert,Coleridge Initiative - Show US the Data
912,65390685,907.0,,0,0,/djesse/predict-ner-d6e89c,Coleridge Initiative - Show US the Data
913,65529313,839.0,,1,3,/bartpleiter/scibert-ner-string-matching,Coleridge Initiative - Show US the Data
914,64894862,1020.0,0.4766661909519052,0,1,/tuhina13/bert-ner-stringmatch,Coleridge Initiative - Show US the Data
915,66032564,1025.0,,0,0,/diegoflorezestrada/paraphrase-minilm-encode,Coleridge Initiative - Show US the Data
916,65146407,1026.0,,0,5,/tanmaymane18/coleridge-just-matching-the-strings,Coleridge Initiative - Show US the Data
917,63993264,936.0,0.5333375386362202,0,5,/santosh1974/coleridge-initiative,Coleridge Initiative - Show US the Data
918,65461678,940.0,0.5333375386362202,0,0,/nem2020/coleridge-initiative-nltk-eda-v2,Coleridge Initiative - Show US the Data
919,62978095,571.0,,7,6,/shivammiglani/spacy-custom-ner-baseline-w-o-string-matching,Coleridge Initiative - Show US the Data
920,59938206,1418.0,0.5330125973286067,1,8,/kazakan/simple-string-matching-with-ahocorasick,Coleridge Initiative - Show US the Data
921,58125758,1421.0,,0,5,/pehahn/basic-data-input-with-r,Coleridge Initiative - Show US the Data
922,65359344,953.0,0.3495129037771321,0,0,/jorahn/coleridge-hf-ner-ft,Coleridge Initiative - Show US the Data
923,58383357,809.0,,0,5,/hsbota/simple-baseline-finding-labels-in-text-hbot,Coleridge Initiative - Show US the Data
924,61781774,925.0,,1,14,/zashio/for-beginners-load-all-datas-as-dataframe,Coleridge Initiative - Show US the Data
925,57724463,1036.0,0.5305875612706091,17,174,/josephassaker/coleridge-initiative-eda-na-ve-submission,Coleridge Initiative - Show US the Data
926,60891993,1041.0,,0,2,/shunnosukekawai/simple-eda,Coleridge Initiative - Show US the Data
927,57955561,1069.0,,2,6,/anaidashaginian/named-entity-recognition-with-spacy-first-attempt,Coleridge Initiative - Show US the Data
928,58474133,1092.0,,15,86,/pashupatigupta/starter-competition-data-eda-and-modelling,Coleridge Initiative - Show US the Data
929,64633033,766.0,,0,0,/bootiu/coleridge-expand-text-dataset,Coleridge Initiative - Show US the Data
930,65646352,737.0,,0,0,/hvwesten/where-s-waldo-dataset-edition,Coleridge Initiative - Show US the Data
931,64559336,1389.0,,4,13,/olivierfoudras/coleridge-data-competition-short-eda,Coleridge Initiative - Show US the Data
932,63939355,1396.0,,1,8,/jluza92/entity-extraction-for-classification-spacy-s-ner,Coleridge Initiative - Show US the Data
933,65980866,1400.0,,2,3,/laoliulaoliu/show-us-data,Coleridge Initiative - Show US the Data
934,57707371,1444.0,0.5283826064746823,3,13,/poornap/coleridge-data-loading-eda-simple-submission,Coleridge Initiative - Show US the Data
935,62725249,1445.0,,3,18,/mohamedbakrey/coleridge-loading-data-eda,Coleridge Initiative - Show US the Data
936,60858983,1453.0,,0,2,/robonidos/coleridge-eda-identify-keywords,Coleridge Initiative - Show US the Data
937,58188707,1456.0,0.5241806682425094,0,9,/msafi04/coleridge-show-us-the-data-eda-naive-submission,Coleridge Initiative - Show US the Data
938,58850786,1491.0,,1,5,/beezus666/extremely-basic-text-matching,Coleridge Initiative - Show US the Data
939,65275909,1035.0,,2,4,/starrain3/trainning-code,Coleridge Initiative - Show US the Data
940,63312231,798.0,,0,5,/icrybaby/cheat-code-101,Coleridge Initiative - Show US the Data
941,64863822,807.0,0.5143519860829225,0,1,/bigdatanerds/notebookee2b53dded,Coleridge Initiative - Show US the Data
942,58174577,1546.0,,0,1,/georgemazzeo/coleridge,Coleridge Initiative - Show US the Data
943,66396500,721.0,,0,1,/saralafia/v2-string-matching,Coleridge Initiative - Show US the Data
944,57684639,1575.0,,0,1,/chengjiun/coleridgeinitiative-eda-section-list,Coleridge Initiative - Show US the Data
945,64787075,1526.0,,4,5,/sumeetsawant/coleridge-simple-phrase-matching-spacy,Coleridge Initiative - Show US the Data
946,58475064,63.0,,0,2,/narendra/coleridge-eda-positive-sentences,Coleridge Initiative - Show US the Data
947,66427483,23.0,0.4496734215374309,1,6,/ilyenkov/coleridgeinitiative-show-us-the-data-v0,Coleridge Initiative - Show US the Data
948,65171281,900.0,0.4427329192546584,1,7,/mrparamatma/data-extraction-visualization,Coleridge Initiative - Show US the Data
949,66116472,919.0,,0,4,/areibman/friday-data-science-squad-coleridge,Coleridge Initiative - Show US the Data
950,64862304,790.0,,0,4,/minhhieutran2112/show-me-the-data-preparer,Coleridge Initiative - Show US the Data
951,66241156,1543.0,,0,1,/baotramduong/coleridge-initiative-n-gram-models,Coleridge Initiative - Show US the Data
952,58918669,825.0,,0,1,/poedator/coleridge-words-in-titles,Coleridge Initiative - Show US the Data
953,57776170,1530.0,0.4088878438749118,7,41,/jamesmcguigan/coleridge-string-literals,Coleridge Initiative - Show US the Data
954,58121775,1531.0,0.4088878438749118,0,1,/inder123/version-1-0,Coleridge Initiative - Show US the Data
955,66115632,851.0,0.3772754957027813,0,0,/kartikga7/ner-0,Coleridge Initiative - Show US the Data
956,66389061,47.0,0.2380242311276794,0,8,/nbroad/no-training-question-answering-model,Coleridge Initiative - Show US the Data
957,59916083,744.0,,0,3,/davidemariani/coleridge-ner-full-info-df,Coleridge Initiative - Show US the Data
958,66237863,837.0,,0,2,/manang/notebookb555ddcd5f,Coleridge Initiative - Show US the Data
959,65919589,1553.0,0.2338858920344922,0,0,/gavinjang/bert-with-pre-trained-model,Coleridge Initiative - Show US the Data
960,60360130,572.0,0.1977714103788602,0,2,/sonluong1987/r-showusthedata,Coleridge Initiative - Show US the Data
961,63556457,1580.0,,17,29,/jagdmir/coleridge-ner-using-spacy,Coleridge Initiative - Show US the Data
962,60857987,1591.0,,1,5,/mohitduklan/coleridge-initiative-show-us-the-data-eda,Coleridge Initiative - Show US the Data
963,60230376,1593.0,,0,1,/shellysinha/coleridgew2v-py,Coleridge Initiative - Show US the Data
964,61329696,1594.0,0.0,0,1,/aishreeramesh/ai4see-nlp-1,Coleridge Initiative - Show US the Data
965,60787141,10.0,,0,2,/unfriendlyai/your-own-personal-auto88coder,Задача TerraEvolution от Роскосмоса
966,58435868,152.0,,0,6,/yus002/tps-april-visualization-practice,Tabular Playground Series - Apr 2021
967,58579342,117.0,,0,5,/kalashnimov/tps-apr-2021-eda,Tabular Playground Series - Apr 2021
968,59340180,81.0,0.8114959231452329,62,95,/alexryzhkov/n3-tps-april-21-lightautoml-starter,Tabular Playground Series - Apr 2021
969,61483788,95.0,,15,15,/marcinstasko/ann-ensembling-meta-and-pseudometa-classifier,Tabular Playground Series - Apr 2021
970,61426486,96.0,0.8177928473399532,57,131,/remekkinas/ensemble-learning-meta-classifier-for-stacking,Tabular Playground Series - Apr 2021
971,61168051,100.0,,7,3,/vhomello/top-10-categorical-encoders-tps-apr,Tabular Playground Series - Apr 2021
972,58574290,103.0,0.7783563413255833,1,3,/kingabzpro/easy-to-understand-r-code-lgbm-bagged,Tabular Playground Series - Apr 2021
973,100840484,37.0,,6,21,/khotijahs1/ml-experiment-tracking-with-truefoundry-platform,Tabular Playground Series - Apr 2021
974,58486502,104.0,0.7847339953176717,2,6,/tunguz/tps-april-2021-eda,Tabular Playground Series - Apr 2021
975,58526230,105.0,0.7426334059901509,0,9,/gpreda/titanic-for-the-masses,Tabular Playground Series - Apr 2021
976,58430627,93.0,,0,6,/zhaodianwen/tps-april-1-eda,Tabular Playground Series - Apr 2021
977,59385591,64.0,,13,25,/sureshmecad/tabular-titanic-apr2021,Tabular Playground Series - Apr 2021
978,59352521,108.0,,4,4,/kmldas/synthanic-eda,Tabular Playground Series - Apr 2021
979,61001621,87.0,,12,29,/pranjalverma08/tps-april-21-the-ann-approach-score-80-782,Tabular Playground Series - Apr 2021
980,60468305,189.0,,19,32,/jeongyoonlee/autoencoder-pseudo-label-autolgb,Tabular Playground Series - Apr 2021
981,58636941,29.0,,3,12,/lucabasa/be-careful-about-your-test-set,Tabular Playground Series - Apr 2021
982,60888714,24.0,,0,0,/huyuet/apr-2021-a-single-lightgbm,Tabular Playground Series - Apr 2021
983,59922137,80.0,,5,11,/jitendramanwani/tps-april-2021-eda-viz-insights-model-end-2-end,Tabular Playground Series - Apr 2021
984,59202170,65.0,0.7814644385242593,2,7,/salilchoubey/tps-apr-eda-very-baseline-model,Tabular Playground Series - Apr 2021
985,59818062,73.0,,0,4,/siddharthpchauhan/kaggle-tabular-playground-april-2021,Tabular Playground Series - Apr 2021
986,58586050,34.0,,1,3,/santoshd3/tps-april,Tabular Playground Series - Apr 2021
987,60482111,36.0,0.0,53,31,/harunshimanto/tps-2021-eda-baseline-using-pyspark,Tabular Playground Series - Apr 2021
988,60995953,42.0,0.8172277387583757,1,7,/quincyqiang/tps-apr-2021-pseudo-labeling-voting-ensemble,Tabular Playground Series - Apr 2021
989,60888069,120.0,0.8001130217163155,3,17,/erikgarcia/tps-april-2021-logistic-regression-4-variables,Tabular Playground Series - Apr 2021
990,59756269,734.0,0.7927262452571244,4,9,/aipi12/voting-ensemble-keras-nn-catboost-lgbm,Tabular Playground Series - Apr 2021
991,61054577,181.0,0.7906676354242351,3,18,/napetrov/tps04-svm-with-intel-extension-for-scikit-learn,Tabular Playground Series - Apr 2021
992,58412295,169.0,0.7184144667796883,2,9,/gomes555/tps-apr2021-eda-profiling-rf-pipeline-baseline,Tabular Playground Series - Apr 2021
993,58824150,167.0,0.758133527084847,0,2,/antonellomartiello/tabular-apr01-quick-test-with-optuna-and-lgbm,Tabular Playground Series - Apr 2021
994,58824150,167.0,0.758133527084847,0,2,/antonellomartiello/tabular-apr01-quick-test-with-optuna-and-lgbm,Tabular Playground Series - Apr 2021
995,61438627,115.0,,0,2,/chienhsianghung/tps-apr-lgbm-catboost-decisiontree-pseudo,Tabular Playground Series - Apr 2021
996,60153807,183.0,0.7977718575926375,2,11,/khoongweihao/tps-apr-2021-tabnet,Tabular Playground Series - Apr 2021
997,60172720,184.0,,10,36,/gauravsahani/survival-predict-eda-feature-selection-optuna-lgbm,Tabular Playground Series - Apr 2021
998,60556126,207.0,0.8148058448373294,0,0,/pratiksharm/tps-apr2021-catboost-run-pseudo-label,Tabular Playground Series - Apr 2021
999,58472194,188.0,0.7878824574150319,3,12,/piantic/tps-apr-h20-automl-starter,Tabular Playground Series - Apr 2021
1000,59746017,203.0,0.8063695810123517,0,0,/ajpagotto/simple-eda-svc-pipeline,Tabular Playground Series - Apr 2021
1001,59771723,194.0,0.8148058448373294,17,20,/manwithaflower/lazy-and-boring-blending,Tabular Playground Series - Apr 2021
1002,59309963,205.0,,4,7,/davirolim/improving-model-with-sagemaker-hpo,Tabular Playground Series - Apr 2021
1003,58871413,234.0,0.795269233874223,2,8,/springmanndaniel/lgbm-baseline-in-r,Tabular Playground Series - Apr 2021
1004,60738547,215.0,0.7827964801808347,8,15,/pavfedotov/tps-april-eda-logistic-regression,Tabular Playground Series - Apr 2021
1005,60563882,191.0,0.793695002825543,5,10,/docxian/tabular-playground-4-start-me-up,Tabular Playground Series - Apr 2021
1006,61464408,251.0,0.8126261403083879,0,12,/jonaspalucibarbosa/tps04-21-eda-models-voting-pseudolabel,Tabular Playground Series - Apr 2021
1007,58996871,244.0,0.7857431177847743,4,4,/somsubhrometya/tps-2021-04-starter-notebook-eda-basic-models,Tabular Playground Series - Apr 2021
1008,59004696,289.0,0.8058852022281424,2,20,/belov38/catboost-lb,Tabular Playground Series - Apr 2021
1009,61395689,253.0,0.8110115443610236,0,3,/elon4773/titanic-visualization-bayesian-optimization,Tabular Playground Series - Apr 2021
1010,58732584,254.0,0.7923629611689674,0,1,/luanademi/solving-the-synthanic-using-democracy,Tabular Playground Series - Apr 2021
1011,59170348,474.0,,12,46,/carlmcbrideellis/synthanic-feature-engineering-beware,Tabular Playground Series - Apr 2021
1012,64501572,277.0,0.8053604585452491,28,38,/mykeysid10/tps-april-xgb,Tabular Playground Series - Apr 2021
1013,59522790,304.0,0.775167514329539,0,0,/darknez/first-tab-apr,Tabular Playground Series - Apr 2021
1014,60948974,280.0,0.8035440381044644,1,6,/tlgks32/kaggle-playground-featureengineering-study2,Tabular Playground Series - Apr 2021
1015,60484954,268.0,,2,5,/priyabratapanda/tpsa-80-acc-with-catboost-and-bayesoptimization,Tabular Playground Series - Apr 2021
1016,60453590,283.0,0.8060062969241947,5,8,/joatom/tps-apr-2021-simple-and-quick-baseline,Tabular Playground Series - Apr 2021
1017,60323676,342.0,,6,9,/kaiskermani/eda-pseudo-labelling-and-tuned-dnn,Tabular Playground Series - Apr 2021
1018,69165771,286.0,0.8044724307741987,0,2,/vernondsouza123/april-playground-competition-solution,Tabular Playground Series - Apr 2021
1019,61398347,298.0,0.8007588600952612,1,1,/eunijnjun/tps-april-eda-feature-engineering-sklearn,Tabular Playground Series - Apr 2021
1020,59672418,319.0,0.7978122224913216,0,0,/niknovikov/tps-apr-2021-eda-model-rus,Tabular Playground Series - Apr 2021
1021,59180465,314.0,0.7959150722531686,21,32,/tomwarrens/tps-april-2021-lgbm-optuna,Tabular Playground Series - Apr 2021
1022,58826063,305.0,,17,21,/jmargni/tps-apr-2021-lightgbm-cv,Tabular Playground Series - Apr 2021
1023,59271059,311.0,,0,0,/poipii/optuna-testbench,Tabular Playground Series - Apr 2021
1024,59327938,333.0,,3,6,/pourchot/train-data-clustering-visualization,Tabular Playground Series - Apr 2021
1025,59444357,347.0,,8,13,/sahilt93/tabular-playground-rf-xgb-feature-engineering,Tabular Playground Series - Apr 2021
1026,60877851,331.0,,0,0,/kwonjungmin/notebook5df7ae9696,Tabular Playground Series - Apr 2021
1027,61463637,351.0,,0,0,/lagors/fuun-vote-with-cat-lgbm-rf-and-optuna,Tabular Playground Series - Apr 2021
1028,58755539,360.0,,1,8,/craigmthomas/tps-apr-2021-eda,Tabular Playground Series - Apr 2021
1029,61336053,363.0,0.8019294421571002,2,3,/vladimirabramov/synthanic-with-lgbmclassifier,Tabular Playground Series - Apr 2021
1030,59413822,380.0,,0,2,/mekazanc/for-beginners,Tabular Playground Series - Apr 2021
1031,60579967,405.0,,0,0,/betancourt/tabularplayground-april-eda,Tabular Playground Series - Apr 2021
1032,61460600,361.0,0.8019698070557842,0,10,/hayahiko/easy-way-lgbm-auto-lgbm-tuner-wtih,Tabular Playground Series - Apr 2021
1033,58754478,362.0,0.7846532655203036,0,0,/yhirakawa/titanic-for-beginners,Tabular Playground Series - Apr 2021
1034,59270119,410.0,0.8020101719544684,4,11,/svyatoslavsokolov/tps-apr-2021-lgbm,Tabular Playground Series - Apr 2021
1035,59704143,459.0,0.7924033260676516,3,10,/onielg/lgbm-catboostvslgbm,Tabular Playground Series - Apr 2021
1036,59221098,411.0,0.801848712359732,13,9,/bagusbpg/my-12th-notebook,Tabular Playground Series - Apr 2021
1037,61450048,419.0,,9,15,/nishantdhingra/april-tps-starter-with-pycaret,Tabular Playground Series - Apr 2021
1038,61016855,392.0,,13,9,/ekozyreff/tps-2021-04-support-vector-machines,Tabular Playground Series - Apr 2021
1039,62236814,397.0,,14,10,/nikitasenpai/tps-titanic-best-score-gridsearchcv-78-acc,Tabular Playground Series - Apr 2021
1040,58476183,409.0,,0,2,/mihir27/tps-april-eda-titanic-data,Tabular Playground Series - Apr 2021
1041,58678541,438.0,0.7866311455558247,0,1,/barteksadlej123/lgb-train-and-submit-baseline,Tabular Playground Series - Apr 2021
1042,58678541,438.0,0.7866311455558247,0,1,/barteksadlej123/lgb-train-and-submit-baseline,Tabular Playground Series - Apr 2021
1043,59614768,420.0,,13,22,/tarushi89/tps-april-your-baseline-model,Tabular Playground Series - Apr 2021
1044,60648260,456.0,0.7936142730281747,0,0,/shunsukeyamamoto/tps-apr-2021,Tabular Playground Series - Apr 2021
1045,59913085,452.0,0.8004359409057883,6,15,/bhavikjain/tabular-playground-series-april-ensemble,Tabular Playground Series - Apr 2021
1046,59913085,452.0,0.7990231694518447,6,15,/bhavikjain/tabular-playground-series-april-ensemble,Tabular Playground Series - Apr 2021
1047,61065999,471.0,0.7880439170097683,6,6,/kazamkhattar/first,Tabular Playground Series - Apr 2021
1048,61384202,439.0,,0,1,/jsmithperera/tps-lgbm-optuna,Tabular Playground Series - Apr 2021
1049,61330231,483.0,,0,1,/shilleroleg/syntanic-pipeline,Tabular Playground Series - Apr 2021
1050,61035309,435.0,,1,9,/dpaluszk/titanic-simple-approach-33-solution-in-10-mins,Tabular Playground Series - Apr 2021
1051,58494474,495.0,,0,4,/pratikkgandhi/simple-xgboost-starter-optuna,Tabular Playground Series - Apr 2021
1052,59462138,544.0,,6,9,/rahulmish/april-tabular-2021-detailed-solution-79-6accuracy,Tabular Playground Series - Apr 2021
1053,60026253,462.0,0.7957939775571163,9,8,/omkarchoulwar/tps-apr-21-models-and-eda,Tabular Playground Series - Apr 2021
1054,58483484,515.0,0.7904254460321305,19,21,/mt77pp/mljar-automl-tps-apr-21,Tabular Playground Series - Apr 2021
1055,59125288,543.0,0.7974893033018488,2,8,/marcosmuozgonzlez/tps-apr-2021-feat-eng-boruta-optuna-xgboost,Tabular Playground Series - Apr 2021
1056,59125288,543.0,0.7974893033018488,2,8,/marcosmuozgonzlez/tps-apr-2021-feat-eng-boruta-optuna-xgboost,Tabular Playground Series - Apr 2021
1057,58522191,507.0,0.7870347945426657,4,13,/hamzaghanmi/tps-apr-beginner-guide-eda-lgbm,Tabular Playground Series - Apr 2021
1058,60779928,472.0,0.7882457415031888,1,2,/peeushthedeveloper/tps-april-21-eda-feature-engineering,Tabular Playground Series - Apr 2021
1059,61659027,516.0,,0,0,/srivatsan25297/tabulardata-april,Tabular Playground Series - Apr 2021
1060,61295272,458.0,0.7977314926939534,0,0,/juanromera/tabular-playground,Tabular Playground Series - Apr 2021
1061,60142333,502.0,0.7860660369742472,0,1,/nacmarino/tps202104-logistic-optuned,Tabular Playground Series - Apr 2021
1062,61633961,534.0,,4,4,/emspell/april-2021-tabular-playground-syntanic,Tabular Playground Series - Apr 2021
1063,60438550,497.0,0.7913538387018648,6,10,/superant/tabular-april-single-lgbm-baseline,Tabular Playground Series - Apr 2021
1064,59345814,528.0,,60,111,/subinium/tps-apr-highlighting-the-data,Tabular Playground Series - Apr 2021
1065,58845900,505.0,,0,2,/caneiro/tps-synthanic-2021-04-00-first-look,Tabular Playground Series - Apr 2021
1066,61154378,532.0,,1,2,/pedrohsr/impute-nan-with-regression-techniques,Tabular Playground Series - Apr 2021
1067,61461427,583.0,,10,12,/akioonodera/tps-apr-2021-lgbm-binary,Tabular Playground Series - Apr 2021
1068,60554490,520.0,0.7962783563413256,1,3,/viteshkakadia/tps-apr-automl-libraries-comparison,Tabular Playground Series - Apr 2021
1069,61170151,554.0,0.7962783563413256,0,1,/naokiokada/tabular-playground-series-apr-2021,Tabular Playground Series - Apr 2021
1070,60946820,639.0,,4,6,/satvik2204/tps-april-eda,Tabular Playground Series - Apr 2021
1071,60270738,676.0,0.7909905546137079,1,6,/jazivxt/use-it-or-lose-it,Tabular Playground Series - Apr 2021
1072,60975731,625.0,0.7939775571163317,3,15,/andreyrus/tps-apr-rf-with-intel-extension-for-scikit-learn,Tabular Playground Series - Apr 2021
1073,60416611,612.0,0.7951885040768548,6,6,/abhishekv5055/tabular-playground-series-apr-2021,Tabular Playground Series - Apr 2021
1074,59366716,617.0,0.7923629611689674,2,4,/remydoyen/tabular-playground-series-simple-logistic-reg,Tabular Playground Series - Apr 2021
1075,59583174,615.0,,4,10,/j2hoon85/2021-april-play-ground-eda-for-kaggle-newbies,Tabular Playground Series - Apr 2021
1076,61504926,580.0,,0,0,/nikosraftogiannis/simple-ensemble-soft-voting,Tabular Playground Series - Apr 2021
1077,59998104,641.0,,6,5,/tjcdev/tps-eda-fe-ethnicity-baseline,Tabular Playground Series - Apr 2021
1078,60952245,592.0,,0,1,/thomasstokes/tabular-playground-series-apr2021,Tabular Playground Series - Apr 2021
1079,58415080,603.0,,19,36,/sh0wmaker/tps-april-eda-for-starter,Tabular Playground Series - Apr 2021
1080,58537103,598.0,0.7889319447808186,2,9,/daikikatsuragawa/tps-apr-2021-benchmark-using-mljar,Tabular Playground Series - Apr 2021
1081,64009491,648.0,,15,35,/namanmanchanda/tps-april-complete-eda-prediction,Tabular Playground Series - Apr 2021
1082,59360726,556.0,,1,8,/lakshya91/basic-eda-and-modeling,Tabular Playground Series - Apr 2021
1083,60891542,629.0,,1,6,/hakanerdogan/simple-code-scikit-learn-ensemble,Tabular Playground Series - Apr 2021
1084,59272795,578.0,,1,2,/natthasit/practice-titanic,Tabular Playground Series - Apr 2021
1085,58465621,652.0,,6,43,/muhammadimran112233/tps-eda-fe-cv-modeling-results,Tabular Playground Series - Apr 2021
1086,58504843,632.0,0.786792605150561,0,2,/kengofujii/tabular-apr-base-model,Tabular Playground Series - Apr 2021
1087,59358426,739.0,,1,5,/adnandodmani/april-titanic-logistic-random-forest-knn-79,Tabular Playground Series - Apr 2021
1088,58734546,673.0,,4,5,/halilakkaynak/tps-apr-eda-and-ann,Tabular Playground Series - Apr 2021
1089,61218419,699.0,0.7917171227900218,2,2,/kyosukemorita/tps-apr-2021-simple-tabnet,Tabular Playground Series - Apr 2021
1090,61118605,550.0,0.7345604262533301,4,4,/rajgandhi/titanic-tps-apr-2021-voting-classifier,Tabular Playground Series - Apr 2021
1091,61118605,550.0,0.7847339953176717,4,4,/rajgandhi/titanic-tps-apr-2021-voting-classifier,Tabular Playground Series - Apr 2021
1092,61118605,550.0,0.7736740130782271,4,4,/rajgandhi/titanic-tps-apr-2021-voting-classifier,Tabular Playground Series - Apr 2021
1093,61118605,550.0,0.7741987567611205,4,4,/rajgandhi/titanic-tps-apr-2021-voting-classifier,Tabular Playground Series - Apr 2021
1094,61317749,661.0,,2,9,/melanie7744/tps4-lr-dt-rfandxgb,Tabular Playground Series - Apr 2021
1095,58644282,776.0,,0,0,/trout59687/titanic-decision-tree-demo,Tabular Playground Series - Apr 2021
1096,58487012,706.0,0.7865504157584564,3,7,/shyambhu/tps-april-basic-modeling,Tabular Playground Series - Apr 2021
1097,61309351,680.0,,1,6,/utkarsh175/lgbm-xgb-rf-tutorial,Tabular Playground Series - Apr 2021
1098,60331432,668.0,,0,2,/jaeworld/tps-april-2021-visualization-optuna-lgbm,Tabular Playground Series - Apr 2021
1099,60459174,690.0,,0,0,/rohitkumaran/synthanic-playground-apr,Tabular Playground Series - Apr 2021
1100,58738242,696.0,,4,11,/rmiperrier/tps-apr-eda-starter-models,Tabular Playground Series - Apr 2021
1101,59303233,755.0,0.7901025268426576,0,0,/calebyenusah/tps-april-2021,Tabular Playground Series - Apr 2021
1102,58422490,712.0,,0,5,/sourabhy/tpa-april,Tabular Playground Series - Apr 2021
1103,59236629,732.0,0.79179785258739,1,3,/donkeys/compare-to-original-data-do-random-search-lgbm,Tabular Playground Series - Apr 2021
1104,61009835,759.0,,2,8,/alexanderbader/nu-titanic,Tabular Playground Series - Apr 2021
1105,88454558,766.0,0.7914749333979172,18,22,/ranjeetshrivastav/tabular-playground-series-apr-2021,Tabular Playground Series - Apr 2021
1106,61435416,744.0,,2,2,/ash112/tps-april-2021,Tabular Playground Series - Apr 2021
1107,61356656,799.0,0.7842496165334625,0,0,/sishahemmed/tabular-data-april,Tabular Playground Series - Apr 2021
1108,61037189,762.0,0.7911116493097602,1,1,/forsesi/no-learning-rates,Tabular Playground Series - Apr 2021
1109,60528501,865.0,,4,1,/aleanto/tabular-playground-april2021-eda-model-tarining,Tabular Playground Series - Apr 2021
1110,58755074,756.0,,2,7,/karthikdk/fastai-tabular-playground-series,Tabular Playground Series - Apr 2021
1111,58695249,826.0,,2,2,/hiroshi0530/lm-with-various-encoding-methods,Tabular Playground Series - Apr 2021
1112,59875887,771.0,,0,0,/ctlockhart3/lightgbm-binary-classifier-tps-apr2021,Tabular Playground Series - Apr 2021
1113,58522439,834.0,,1,5,/srimanthtenneti/titanic-model-v1,Tabular Playground Series - Apr 2021
1114,59233827,872.0,,6,13,/igalbronshtein/tps21apr-feature-engineering-name-column,Tabular Playground Series - Apr 2021
1115,58435730,844.0,,0,1,/drcapa/tps-apr21-tutorial-xgb,Tabular Playground Series - Apr 2021
1116,60716762,930.0,,8,10,/viteshkhurana18/tabular-playground-series-mota-bhai,Tabular Playground Series - Apr 2021
1117,61561448,917.0,0.7816258981189957,0,1,/lucaskup/feature-eng-plus-ensemble-knn-rf-lda-svm-mlp,Tabular Playground Series - Apr 2021
1118,60828898,939.0,0.7854605634939856,2,5,/petregriscenco/titanic-tabular-april-2021,Tabular Playground Series - Apr 2021
1119,58478703,968.0,,3,6,/hamzaadnan/catboost-achieve-77-acc-without-preprocessing,Tabular Playground Series - Apr 2021
1120,60093125,962.0,,3,4,/luisbedia/tabular-playground-abr2021,Tabular Playground Series - Apr 2021
1121,60018393,996.0,0.7239444578994106,0,0,/georgz/tabular-playground-series-april,Tabular Playground Series - Apr 2021
1122,61438995,901.0,,2,5,/jchanke/tabular-playground-series-apr-2021,Tabular Playground Series - Apr 2021
1123,58407238,952.0,0.7858238475821425,7,8,/harshitt21/tps-april-2021-visualization-baseline-model,Tabular Playground Series - Apr 2021
1124,58407238,952.0,0.7858238475821425,7,8,/harshitt21/tps-april-2021-visualization-baseline-model,Tabular Playground Series - Apr 2021
1125,61355083,910.0,,3,2,/porter97/synthanic-logistic-regression,Tabular Playground Series - Apr 2021
1126,60923475,955.0,,1,10,/halflings/titanic-problem-al-fihriya-academy-livestream,Tabular Playground Series - Apr 2021
1127,59817939,1053.0,,28,28,/atharvchaudhari/tabular-playground-series-apr-2021,Tabular Playground Series - Apr 2021
1128,61651983,1008.0,,2,10,/mpwolke/petit-prince-by-currypurin,Tabular Playground Series - Apr 2021
1129,58675783,1030.0,,1,4,/niks8411/tabular-playground,Tabular Playground Series - Apr 2021
1130,59493618,984.0,,2,4,/abhishekvermasg1/catboost,Tabular Playground Series - Apr 2021
1131,59606682,938.0,0.7701622668927101,0,1,/saztorralba/synthetictitanicdata-lstmnameencoder,Tabular Playground Series - Apr 2021
1132,74773915,1044.0,,4,20,/mohamedbakrey/eda-for-tps-apr-2021-and-build-best-ml-model,Tabular Playground Series - Apr 2021
1133,62872107,977.0,,0,1,/mujinjo/tps-apr-2021-ml-mjjo,Tabular Playground Series - Apr 2021
1134,60823940,1067.0,,0,1,/crained/tps-april-2020-for-beginners,Tabular Playground Series - Apr 2021
1135,60938586,1040.0,,0,0,/caiquefcoelho/tabular-playground-april,Tabular Playground Series - Apr 2021
1136,59846489,1009.0,0.2908694599176556,0,2,/minhn520/tabular-playground-series-tensorflow,Tabular Playground Series - Apr 2021
1137,60706335,1052.0,0.783684507951885,0,1,/tracyporter/titanic-april-2021,Tabular Playground Series - Apr 2021
1138,59426721,926.0,0.7831597642689917,3,10,/askolkova/tps-april-supervised-algorithms,Tabular Playground Series - Apr 2021
1139,60770070,1095.0,,2,5,/aniketwattamwar/random-forest-classifier-model,Tabular Playground Series - Apr 2021
1140,62226260,1113.0,,3,2,/baekhakjeon/case-study-titanic,Tabular Playground Series - Apr 2021
1141,61311893,1121.0,0.7777508678453217,10,14,/vaishnavipatil4848/tps-april-21-eda-predictions,Tabular Playground Series - Apr 2021
1142,60559773,1124.0,,8,11,/kesavsivakumar/k-best-features-xgboost-elasticnet,Tabular Playground Series - Apr 2021
1143,58486979,1094.0,,0,5,/rsesha/autoviml-score-77-4-apr-tps-2021,Tabular Playground Series - Apr 2021
1144,60707388,1163.0,,4,2,/obiaf88/titanic-eda,Tabular Playground Series - Apr 2021
1145,59020927,1176.0,0.7525631710664407,2,5,/kongnyooong/ensemble-for-raw-beginners-to-top-25,Tabular Playground Series - Apr 2021
1146,58848206,1175.0,,0,0,/christopherwsmith/tabular-playground-series-april,Tabular Playground Series - Apr 2021
1147,61383338,1183.0,0.7392023896020021,0,1,/lakshanagv/logistic-regression-tabular-playground-april,Tabular Playground Series - Apr 2021
1148,61383890,1187.0,,0,0,/sonluong1987/nn-raw-tblr-playground-titanic,Tabular Playground Series - Apr 2021
1149,61207107,1189.0,,2,2,/roguecomputer/rfc-71-9-accuracy-data-vis,Tabular Playground Series - Apr 2021
1150,60943293,1237.0,,0,1,/arvindmakwana/notebook993201d83c,Tabular Playground Series - Apr 2021
1151,58694576,22.0,,1,12,/imeintanis/metric-explained-row-wise-micro-averaged-f1,BirdCLEF 2021 - Birdcall Identification
1152,111997355,10.0,,0,0,/nitindatta/inference,BirdCLEF 2021 - Birdcall Identification
1153,62113229,18.0,,7,21,/whurobin/training-pipeline-in-pytorch-lightning,BirdCLEF 2021 - Birdcall Identification
1154,64372827,1.0,0.7620549886621326,1,14,/namakemono/birdclef-train-and-evaluation-pipeline-4f36dd,BirdCLEF 2021 - Birdcall Identification
1155,64215289,39.0,,0,5,/tanulsingh077/sed-model-tanul-s-version,BirdCLEF 2021 - Birdcall Identification
1156,60048757,23.0,0.6131746031746036,43,219,/kneroma/clean-fast-simple-bird-identifier-inference,BirdCLEF 2021 - Birdcall Identification
1157,64625970,38.0,0.728988095238097,0,0,/kunihikofurugori/final-submission,BirdCLEF 2021 - Birdcall Identification
1158,62693967,90.0,,0,0,/dylanliuofficial/birdclef-mels-computer-d5-256-public-0,BirdCLEF 2021 - Birdcall Identification
1159,58773186,66.0,,0,5,/takamichitoda/birdclef-train-only-metadata,BirdCLEF 2021 - Birdcall Identification
1160,63444746,109.0,,0,1,/hanson0910/notebookc5e650e273,BirdCLEF 2021 - Birdcall Identification
1161,64638310,47.0,,1,3,/fffrrt/location-and-time-postprocessing-birdclef-2021,BirdCLEF 2021 - Birdcall Identification
1162,62309459,51.0,,0,5,/guedou/metric-implementation,BirdCLEF 2021 - Birdcall Identification
1163,62960686,79.0,,0,8,/dryanfurman/birdclef-eda-and-fastai,BirdCLEF 2021 - Birdcall Identification
1164,63573153,91.0,0.6449305555555566,1,18,/majunfu/clean-fast-simple-bird-identifier,BirdCLEF 2021 - Birdcall Identification
1165,64438121,102.0,0.6580158730158737,0,1,/sishihara/birdclef-2021-inference,BirdCLEF 2021 - Birdcall Identification
1166,60015089,138.0,,0,16,/sarpal465/birdclef2021-complete-eda,BirdCLEF 2021 - Birdcall Identification
1167,63210331,166.0,0.6425297619047629,1,12,/zifencai/simple-bird-identifier-inference,BirdCLEF 2021 - Birdcall Identification
1168,114708671,213.0,,0,0,/kellyhu0109/bird-identifier,BirdCLEF 2021 - Birdcall Identification
1169,61090083,245.0,,0,9,/utpalrudra/a-simple-training-model,BirdCLEF 2021 - Birdcall Identification
1170,62798459,276.0,,0,2,/tiagovieira/pytorch-pipeline-training,BirdCLEF 2021 - Birdcall Identification
1171,62847561,279.0,,0,0,/dkrocksup/datapreparation,BirdCLEF 2021 - Birdcall Identification
1172,60026767,336.0,,2,9,/aramacus/at-the-right-place-in-the-right-time,BirdCLEF 2021 - Birdcall Identification
1173,62658551,410.0,0.6177380952380959,0,0,/kengofujii/clean-fast-simple-bird-identifier-20210502,BirdCLEF 2021 - Birdcall Identification
1174,58686317,432.0,0.5455357142857142,0,15,/ahmedewida/birdclef-2021-starter-notebook,BirdCLEF 2021 - Birdcall Identification
1175,59301823,472.0,,2,9,/coder247/bird-clef-cnn-and-spectogram,BirdCLEF 2021 - Birdcall Identification
1176,63817725,513.0,,0,5,/hotsonhonet/baseline-birdclef,BirdCLEF 2021 - Birdcall Identification
1177,63072194,516.0,0.5467261904761904,0,0,/kristjanr/birdclef2021-sample-submission,BirdCLEF 2021 - Birdcall Identification
1178,63255577,418.0,,0,4,/josephamigo/beware-secondary-labels-can-be-repeated,BirdCLEF 2021 - Birdcall Identification
1179,64160101,596.0,,0,1,/stpeteishii/birdclef-2021-audio-detection,BirdCLEF 2021 - Birdcall Identification
1180,58668690,562.0,,0,5,/anuragupadhyaya/birdclef2021-data-shading-visual-eda,BirdCLEF 2021 - Birdcall Identification
1181,60183366,639.0,,1,14,/johnowhitaker/peak-identification,BirdCLEF 2021 - Birdcall Identification
1182,61360567,674.0,,0,2,/trendysloth/notebooka033a269fc,BirdCLEF 2021 - Birdcall Identification
1183,62253354,679.0,,0,1,/ashavish/birdclef-2021-eda-train-attempt1,BirdCLEF 2021 - Birdcall Identification
1184,60639926,687.0,,9,133,/drcapa/birdclef-2021-starter,BirdCLEF 2021 - Birdcall Identification
1185,59207197,699.0,,17,35,/mohamedbakrey/birdclef-2021-do-a-sound-analysis,BirdCLEF 2021 - Birdcall Identification
1186,61380147,700.0,0.5467261904761904,0,6,/kojima1976/bird-prog-2,BirdCLEF 2021 - Birdcall Identification
1187,59920820,761.0,0.5467261904761904,0,1,/sakthivelj/birdclef-2021-birdcall-identification,BirdCLEF 2021 - Birdcall Identification
1188,59831672,720.0,,0,0,/saztorralba/birdcall-activitydetectorlogmelcnn,BirdCLEF 2021 - Birdcall Identification
1189,59321532,722.0,,9,20,/jmreuter/birdclef-visualizing-non-target-sounds,BirdCLEF 2021 - Birdcall Identification
1190,65358463,751.0,,0,0,/hashandananjaya/clean-fast-simple-bird-identifier-training-colab,BirdCLEF 2021 - Birdcall Identification
1191,59898567,653.0,,3,4,/toldo171/birdclef-process-create-and-download-img-dataset,BirdCLEF 2021 - Birdcall Identification
1192,74265735,780.0,,26,115,/shtrausslearning/soundscape-visualisations,BirdCLEF 2021 - Birdcall Identification
1193,58619705,782.0,0.5345238095238096,1,5,/rohitbpur/birdclef-2021-starter-rohit,BirdCLEF 2021 - Birdcall Identification
1194,61075245,774.0,,2,3,/duythanhng/birdclef-2021-pytorch-augmentation,BirdCLEF 2021 - Birdcall Identification
1195,62742258,779.0,0.5293650793650794,0,0,/emorkrin/birdclef-spectrum-transfer-learning,BirdCLEF 2021 - Birdcall Identification
1196,58861984,781.0,,0,8,/msafi04/birdclef-2021-eda-train,BirdCLEF 2021 - Birdcall Identification
1197,65105092,798.0,,0,0,/tobiasbonnesen/birdclef2021-model-training-thesis-baseline,BirdCLEF 2021 - Birdcall Identification
1198,61599867,794.0,,0,5,/virajkadam/birdclef-exploratory-data-analysis,BirdCLEF 2021 - Birdcall Identification
1199,60875853,796.0,0.4593253968253973,0,5,/percyvelle/bird-competition,BirdCLEF 2021 - Birdcall Identification
1200,62246264,804.0,,0,6,/julichitai/birdclef-eda-fft,BirdCLEF 2021 - Birdcall Identification
1201,61589737,37.0,,0,0,/nizarelkhalili/competition1ships,Navires 2021 à la mano
1202,63133222,4.0,0.9154198680977336,0,1,/maximkazantsev/avito-category-prediction-4th-place-solution,Avito Category Prediction
1203,60926881,44.0,,0,0,/igorlukhnev/notebooke0bf68bfb4,Avito Category Prediction
1204,62860587,107.0,0.7838888778671171,0,0,/danilshishkin/final,Avito Category Prediction
1205,62728263,3.0,0.1357334809058851,3,21,/wuwawa/automl-using-h2o,California House Prices
1206,62594291,5.0,,3,16,/jackzh/the-4th-place-approach-random-forest,California House Prices
1207,62728995,12.0,,7,27,/curiosity30/the-12th-place-approach-catboost,California House Prices
1208,61004605,33.0,,3,13,/whurobin/baseline,California House Prices
1209,60857113,50.0,,16,31,/litianfu1997/magic-defeats-magic,California House Prices
1210,62543673,49.0,,10,18,/seefun/automl-using-auto-gluon,California House Prices
1211,60208420,64.0,7.672223826026067,4,83,/haoyilin/d2l-kaggle-getting-started,California House Prices
1212,63922982,13.0,,1,11,/antoreepjana/feature-reduction-on-dae-te-le-features-tps0521,Tabular Playground Series - May 2021
1213,62642820,40.0,,26,44,/remekkinas/cnn-2d-convolution-for-solving-tps-05,Tabular Playground Series - May 2021
1214,64347606,28.0,1.0857103965626875,14,23,/mehrankazeminia/tps-may-21-catboost-tabularutilizedautoml,Tabular Playground Series - May 2021
1215,63496406,151.0,,6,17,/sagnik1511/tabular-playground-eda-prediction-under-100,Tabular Playground Series - May 2021
1216,64020428,32.0,,18,38,/pranjalverma08/tps-may-21-the-ensemble-approach-with-optuna,Tabular Playground Series - May 2021
1217,61545396,33.0,1.1015272235243323,2,14,/yus002/logistic-regression-optuna-tuning,Tabular Playground Series - May 2021
1218,62351140,35.0,,15,101,/ruchi798/tps-may-rapids,Tabular Playground Series - May 2021
1219,62938455,37.0,1.0863526627560292,14,28,/hayahiko/tps-may-easy-way-lgbm-optuna-step-by-step,Tabular Playground Series - May 2021
1220,63736468,45.0,,2,11,/gomes555/tps-may2021-r-tidymodels-stacks,Tabular Playground Series - May 2021
1221,63320320,123.0,,7,10,/antonellomartiello/tps-may-eda-visualization-with-plotly-mljar,Tabular Playground Series - May 2021
1222,63876382,456.0,1.0891307967533062,0,3,/robert76/tps-may-blending,Tabular Playground Series - May 2021
1223,63060714,108.0,,14,22,/ansh422/tps-may-simple-eda,Tabular Playground Series - May 2021
1224,62283919,110.0,,0,15,/kritidoneria/tps-may-2021-intro-to-adversarial-validation,Tabular Playground Series - May 2021
1225,61803096,65.0,1.0897177620190963,7,21,/debarshichanda/tps-may-21-xgboost-optuna,Tabular Playground Series - May 2021
1226,63266400,112.0,,6,10,/ritesh7355/tps-may21-xgboost-lightautoml,Tabular Playground Series - May 2021
1227,61843542,51.0,1.085982918228331,46,73,/alexryzhkov/lightautoml-baseline-tps-may-2021,Tabular Playground Series - May 2021
1228,64716874,17.0,1.0855724363617354,1,9,/azzamradman/top-2-lightautoml-stacking,Tabular Playground Series - May 2021
1229,62178096,53.0,,0,1,/bruceharold/eda-feature-and-class-characteristics,Tabular Playground Series - May 2021
1230,63030140,78.0,,6,9,/pourchot/keras-concat-sequential-api-conv1d-embedding,Tabular Playground Series - May 2021
1231,61479435,63.0,,5,10,/hwangjihun/tps-may-2021-xgboost-starters-for-beginners,Tabular Playground Series - May 2021
1232,62281217,103.0,,0,8,/sourabhy/tps-may,Tabular Playground Series - May 2021
1233,62544175,138.0,1.0859826893159912,14,17,/cybrk5/tps-may2021-eda-and-lightautoml-80-catboost-20,Tabular Playground Series - May 2021
1234,63854161,89.0,1.085861281805523,17,30,/ryanbarretto/boring-blend-of-stack-and-weights,Tabular Playground Series - May 2021
1235,63854161,89.0,1.085861281805523,17,30,/ryanbarretto/boring-blend-of-stack-and-weights,Tabular Playground Series - May 2021
1236,64145619,67.0,1.0943602734547668,2,8,/faisalalsrheed/dancing-with-tensorflow-decision-forests,Tabular Playground Series - May 2021
1237,64099241,189.0,,6,8,/aphilip/may-tps-fastai-tabular-with-smote-resampling,Tabular Playground Series - May 2021
1238,62582975,235.0,,7,15,/sureshmecad/tps-apr21-evalml-automl,Tabular Playground Series - May 2021
1239,63375611,238.0,,30,33,/lykin22/tps-may21-xgboost-lgbm-lightautoml,Tabular Playground Series - May 2021
1240,64434165,190.0,1.0858870391019102,7,23,/bhavikjain/tps-may-2021-eda-catboost-lightautoml,Tabular Playground Series - May 2021
1241,64434165,190.0,1.085794375248407,7,23,/bhavikjain/tps-may-2021-eda-catboost-lightautoml,Tabular Playground Series - May 2021
1242,64434165,190.0,1.0868482517441005,7,23,/bhavikjain/tps-may-2021-eda-catboost-lightautoml,Tabular Playground Series - May 2021
1243,63152423,231.0,,6,13,/maverix/oof-weighted-ensemble,Tabular Playground Series - May 2021
1244,64542387,157.0,,22,18,/omkarpatil0217/tabular-may-op,Tabular Playground Series - May 2021
1245,61905632,221.0,1.0877563105971164,9,30,/tomwarrens/tps-may-2021-lightgbm-optuna,Tabular Playground Series - May 2021
1246,61931571,206.0,,4,7,/yhirakawa/tbs-may-eda-xgboost-optuna,Tabular Playground Series - May 2021
1247,62120793,159.0,,76,93,/andreshg/tps-may-a-complete-analysis,Tabular Playground Series - May 2021
1248,63931473,207.0,1.0884322158819577,3,3,/meihanw/tps-may-automl-tables-benchmark,Tabular Playground Series - May 2021
1249,63931572,203.0,,15,15,/adrianhajdukiewicz/logistic-regression-gridsearchcv-knn-xgboost,Tabular Playground Series - May 2021
1250,62346015,54.0,1.0887746137952097,3,12,/fusioncenter/resnet-architecture-with-categorical-embeddings,Tabular Playground Series - May 2021
1251,63990879,131.0,,4,13,/shreyanshkabra/tps-may2021,Tabular Playground Series - May 2021
1252,62709239,259.0,1.0876875432358584,1,4,/aerdem/tps-may-lgbm,Tabular Playground Series - May 2021
1253,63856131,228.0,1.0867533791494115,0,2,/paramond/notebookdea6627b94,Tabular Playground Series - May 2021
1254,62128215,202.0,,2,7,/maostack/tps-05-expreriment-on-undersampling,Tabular Playground Series - May 2021
1255,64524170,234.0,1.0946432768762946,2,8,/jonaspalucibarbosa/tps05-21-nn-with-keras-first-nn,Tabular Playground Series - May 2021
1256,63915171,132.0,1.1022056146916108,0,1,/nacmarino/tps202105-lightgbm-optuned,Tabular Playground Series - May 2021
1257,63918706,367.0,1.0870409333600222,0,10,/rajgandhi/tps-march-calibration,Tabular Playground Series - May 2021
1258,63918706,367.0,1.0896523786016628,0,10,/rajgandhi/tps-march-calibration,Tabular Playground Series - May 2021
1259,62163072,384.0,1.0867009954036957,3,13,/shashwatwork/breaking-the-leaderboard-with-mljar,Tabular Playground Series - May 2021
1260,64323151,376.0,1.0997102243787822,3,7,/jtourkis/tab-keras-multiclass-neural-network,Tabular Playground Series - May 2021
1261,63227975,363.0,1.0871509204077927,3,21,/aipi12/eda-lgbm-optuna-using-gpu,Tabular Playground Series - May 2021
1262,61561601,272.0,1.0868990276567874,0,3,/belov38/catboost-catfeatures,Tabular Playground Series - May 2021
1263,64310432,282.0,1.086938382249685,0,0,/juanromera/tabular-playground-may-2021,Tabular Playground Series - May 2021
1264,61479117,475.0,1.0893871909388777,2,6,/rajsengo/tps-may-tpot-automl-baseline,Tabular Playground Series - May 2021
1265,64536450,311.0,,17,24,/piantic/tps-june-2021-basic-eda-t-sne-visualization,Tabular Playground Series - May 2021
1266,62956115,375.0,,2,6,/landist/umap-clustering-classification,Tabular Playground Series - May 2021
1267,64462053,442.0,1.0878766343074715,21,28,/mykeysid10/tps-may-catboost,Tabular Playground Series - May 2021
1268,88455198,350.0,1.1087382794907945,4,11,/ranjeetshrivastav/tps-may-tuning-ann-using-randomizedsearchcv,Tabular Playground Series - May 2021
1269,61948532,383.0,1.0922672718527218,0,8,/docxian/tabular-playground-5-multiclass-starter,Tabular Playground Series - May 2021
1270,64018154,378.0,1.3862943611201324,1,7,/brookie210/tps-may2021-catboost-baseline-model,Tabular Playground Series - May 2021
1271,62596239,336.0,1.0913736284785909,1,4,/erikgarcia/tps-may-2021-logistic-regression,Tabular Playground Series - May 2021
1272,64460941,414.0,,1,6,/phantazyq/baseline-catboost-without-params,Tabular Playground Series - May 2021
1273,64614228,141.0,1.087919395794669,0,0,/jenssvensmark/scikit-stacking-tabular-play-may,Tabular Playground Series - May 2021
1274,62144764,506.0,,7,19,/melanie7744/tps5-eda-raising-more-questions-than-answers,Tabular Playground Series - May 2021
1275,61710064,285.0,,0,5,/herwinvw/logloss-baseline,Tabular Playground Series - May 2021
1276,61685025,421.0,,2,22,/kshitijmohan/catboost-baseline,Tabular Playground Series - May 2021
1277,62275297,416.0,,5,10,/krystianwicherek/tps-may-eda-and-model,Tabular Playground Series - May 2021
1278,62563319,435.0,,6,5,/gurujaing/tps-starter-pack-using-boosting,Tabular Playground Series - May 2021
1279,64285893,407.0,1.0897389659034875,1,5,/maunish/tps-may-lgbm-goes-brrrr,Tabular Playground Series - May 2021
1280,62823602,510.0,,1,5,/gsdeepakkumar/playground-series-may-21-simple-rf-with-5-folds,Tabular Playground Series - May 2021
1281,64581282,388.0,,0,5,/sahilpalarpwar/xgboost-first,Tabular Playground Series - May 2021
1282,63601179,515.0,1.0882113334677004,17,28,/akioonodera/tps-may2021-xgboost,Tabular Playground Series - May 2021
1283,63781508,397.0,,27,28,/gcmadhan/tabular-playground-may-2021-h2o-ai,Tabular Playground Series - May 2021
1284,63765200,527.0,1.0882939024855256,0,3,/trimparashut/boosting-ensemble-simple-baseline,Tabular Playground Series - May 2021
1285,141756552,541.0,,10,7,/umutoncu/tps-may-one-vs-rest-model-baseline,Tabular Playground Series - May 2021
1286,64275649,507.0,,5,18,/tharunreddy/eda-xgboost-baseline-grid-search-for-starters,Tabular Playground Series - May 2021
1287,62275763,391.0,1.0884405575023983,4,10,/gpamoukoff/don-t-forget-the-feature-engineering,Tabular Playground Series - May 2021
1288,63562173,569.0,,4,6,/raozjuil/tps-may-2021,Tabular Playground Series - May 2021
1289,62172686,479.0,,0,5,/jsmithperera/tps-may-simple-mlp-smote,Tabular Playground Series - May 2021
1290,63321952,480.0,,5,7,/faelk8/tabular-may-2021-eda-lgbm,Tabular Playground Series - May 2021
1291,66887245,430.0,,0,9,/gauravsarkar/tpsmay-top-500-solution,Tabular Playground Series - May 2021
1292,62227684,501.0,1.2512170419515742,27,40,/accountstatus/tps-may-starter,Tabular Playground Series - May 2021
1293,62864261,499.0,,1,9,/napetrov/svm-tps-may-2021-with-scikit-learn-intelex,Tabular Playground Series - May 2021
1294,62898263,505.0,,15,41,/jeongyoonlee/kaggler-dae-autolgb-baseline,Tabular Playground Series - May 2021
1295,63011188,429.0,1.1037599777859155,12,24,/siddharthpchauhan/tps-may-2021-for-begineers,Tabular Playground Series - May 2021
1296,64599506,558.0,1.0877110017236022,0,0,/hariharannarayanan/which-gradient-boosting-is-better,Tabular Playground Series - May 2021
1297,62951969,575.0,,9,17,/thiagopanini/presenting-xplotter-and-mlcomposer-on-tps-may21,Tabular Playground Series - May 2021
1298,63562624,496.0,,0,5,/kumardeepu/tabular-playground-series-may-2021,Tabular Playground Series - May 2021
1299,62358700,602.0,,2,13,/prithviraj7387/tabular-playground-may-classification-eda,Tabular Playground Series - May 2021
1300,64554190,538.0,,7,9,/hiromasatabuchi/algorithm-pipeline-gridsearch-simple-my-automl,Tabular Playground Series - May 2021
1301,64521768,607.0,1.0937199234923751,0,1,/arindam235/tabplayground-may21,Tabular Playground Series - May 2021
1302,61920633,477.0,,2,12,/barteksadlej123/very-informative-random-variable,Tabular Playground Series - May 2021
1303,61531232,484.0,,5,14,/igalbronshtein/tpsmay21-baseline-randomforest-xgboost-catboost,Tabular Playground Series - May 2021
1304,62934852,533.0,1.0898347976949867,11,16,/omkarchoulwar/tps-may-21-eda-and-models,Tabular Playground Series - May 2021
1305,62072671,481.0,,14,58,/iamleonie/what-if-we-approach-this-as-text-classification,Tabular Playground Series - May 2021
1306,65784666,608.0,,0,7,/hakanerdogan/tps-may-2021-multiple-algorithms-loss-function,Tabular Playground Series - May 2021
1307,64645282,646.0,,0,0,/konovalvolodymyr/ml-rgr,Tabular Playground Series - May 2021
1308,62259605,657.0,,0,5,/akhilprasannan/extratreesclassifier-and,Tabular Playground Series - May 2021
1309,64075496,588.0,,2,6,/anks7190/hyperopt-and-catboost-crossvalidation,Tabular Playground Series - May 2021
1310,63319033,613.0,1.0912000672947295,2,3,/jagunn/tps-may-2021-xgbc,Tabular Playground Series - May 2021
1311,63237938,571.0,,1,8,/munumbutt/kfold-tuned-ensemble-boosted-trees,Tabular Playground Series - May 2021
1312,62062005,625.0,,12,14,/sayantansadhu/tps-may-complete-step-by-step-notebook,Tabular Playground Series - May 2021
1313,63007188,672.0,1.0932492901013675,0,2,/mstkmyhr/2021-05-15-tps-baseline-submission-by-lightgbm,Tabular Playground Series - May 2021
1314,67580097,661.0,,5,23,/ankitp013/tps-catboost-tuning-shap-explained,Tabular Playground Series - May 2021
1315,62114907,687.0,,0,1,/natthasit/tps-may,Tabular Playground Series - May 2021
1316,61820341,673.0,,1,3,/ash112/tps-may-2021,Tabular Playground Series - May 2021
1317,62782960,699.0,1.0930090387571438,1,3,/susree64/tabular-playground-may21,Tabular Playground Series - May 2021
1318,64527325,662.0,,0,1,/smita09/tabular-series-beginner-solution,Tabular Playground Series - May 2021
1319,61508520,761.0,1.0940313932232577,0,3,/tthien/simple-eda-and-baseline-model,Tabular Playground Series - May 2021
1320,62764032,751.0,,0,2,/greengamma/stratifiedkfold-with-lightgbm,Tabular Playground Series - May 2021
1321,61488070,776.0,1.094606025486184,0,2,/drcapa/tps-may21-tutorial-starter,Tabular Playground Series - May 2021
1322,64323210,771.0,1.0979544781741757,8,10,/nikitasenpai/tps-may-simple-good-accuracy,Tabular Playground Series - May 2021
1323,62477637,767.0,,3,5,/tbourton/tps-eda-classification,Tabular Playground Series - May 2021
1324,62219288,757.0,,4,11,/mujinjo/tps-may-2021-eda-and-xgboost-mjjo,Tabular Playground Series - May 2021
1325,63798265,781.0,,13,14,/xiaolx/unbalanced-sample,Tabular Playground Series - May 2021
1326,62215144,783.0,1.0961818215226582,12,22,/harunshimanto/tps-2021-eda-build-an-artificial-neural-network,Tabular Playground Series - May 2021
1327,63220492,797.0,1.1366264286316634,1,13,/duythanhng/tps-may-keras-stratifiedkfold,Tabular Playground Series - May 2021
1328,67036794,823.0,,18,36,/jeongbinpark/tps-may-simple-dnn,Tabular Playground Series - May 2021
1329,64440509,879.0,1.1210511651453152,4,3,/sivasankarmc/tps-may21-xgb-shap,Tabular Playground Series - May 2021
1330,63766373,817.0,,60,185,/subinium/tps-may-categorical-eda,Tabular Playground Series - May 2021
1331,61577100,824.0,1.102783112928857,0,1,/bhimantoros/tps-may-2021-mlp-class-weighting-cv,Tabular Playground Series - May 2021
1332,64339602,846.0,,36,30,/tiwariayan/eda-pca-xgboost,Tabular Playground Series - May 2021
1333,100426364,871.0,,1,3,/harisonmwangi/tps-may-2021-eda,Tabular Playground Series - May 2021
1334,80908437,870.0,,0,7,/kiranclement/tps-may-21,Tabular Playground Series - May 2021
1335,61646853,862.0,,0,6,/jamesbond00700/tabular-may-log-res,Tabular Playground Series - May 2021
1336,61566942,845.0,,0,2,/salhimohamednadjib/mlp-b-char,Tabular Playground Series - May 2021
1337,66834957,900.0,1.092235194901406,0,0,/shunsukeyamamoto/tps-may-2021,Tabular Playground Series - May 2021
1338,62346216,908.0,22.80899788179917,1,5,/tracyporter/tab-may-2021-smote,Tabular Playground Series - May 2021
1339,62056328,913.0,1.2714062617578648,0,5,/stpeteishii/tabular-playground-conv1d,Tabular Playground Series - May 2021
1340,62056328,913.0,1.2714062617578648,0,5,/stpeteishii/tabular-playground-conv1d,Tabular Playground Series - May 2021
1341,62925095,918.0,1.3609720432848411,0,2,/polinakoroleva/tps-apr,Tabular Playground Series - May 2021
1342,62925095,918.0,1.1063265113871876,0,2,/polinakoroleva/tps-apr,Tabular Playground Series - May 2021
1343,62925095,918.0,1.1063265113871876,0,2,/polinakoroleva/tps-apr,Tabular Playground Series - May 2021
1344,62925095,918.0,20.693976594080787,0,2,/polinakoroleva/tps-apr,Tabular Playground Series - May 2021
1345,64391947,943.0,,2,3,/keenborder/kaggle-may-practice,Tabular Playground Series - May 2021
1346,64484732,968.0,1.113661153935812,0,0,/tatakkun/playground-series-05-2021,Tabular Playground Series - May 2021
1347,62347572,964.0,,4,6,/ahsu00/svm-tabular-playground-series-may-2021,Tabular Playground Series - May 2021
1348,63884854,969.0,2.7236792475505087,1,11,/pavfedotov/tps-may-2021-mlp-keras,Tabular Playground Series - May 2021
1349,62265111,975.0,,5,19,/shrutisaxena/h2o-automl-code-for-beginners,Tabular Playground Series - May 2021
1350,62376105,1002.0,,3,8,/donmarch14/may-playground-series-beginners-guide,Tabular Playground Series - May 2021
1351,64508113,1007.0,,0,0,/rockyyashchauhan/notebook4ebeceb17f,Tabular Playground Series - May 2021
1352,64878850,1014.0,,0,0,/caiquefcoelho/tabular-playground-may,Tabular Playground Series - May 2021
1353,62739009,1013.0,1.1875633810415986,8,14,/palanjali007/xgbclassifier,Tabular Playground Series - May 2021
1354,63181860,1017.0,,5,9,/srhyeu/tps-may-tidymodels-tutorial-with-r-tidymodels,Tabular Playground Series - May 2021
1355,64143458,1021.0,1.506764852407139,0,2,/minhn520/tabular-playground-may-xgboost,Tabular Playground Series - May 2021
1356,62443852,1037.0,1.2854176268199955,6,5,/thejas112/tabular-playground-series-may2021-v2,Tabular Playground Series - May 2021
1357,61838090,1058.0,1.3862943611201324,6,17,/yasserhessein/tps-may21-withe-best-score-99,Tabular Playground Series - May 2021
1358,62696108,1071.0,,1,6,/vexxingbanana/tps-may-dnn-implementation-with-functional-api,Tabular Playground Series - May 2021
1359,64516884,1091.0,,0,0,/shivakumargingade/tabular-playground-series-mlp,Tabular Playground Series - May 2021
1360,71832624,3.0,0.442453027985826,0,6,/potatoc5/final-sub,CommonLit Readability Prize
1361,63896984,2.0,,0,3,/takoihiraokazu/fe001-step-1-create-folds,CommonLit Readability Prize
1362,67207090,19.0,0.5929334765723578,0,0,/ktgiahieu/bert-base-readability,CommonLit Readability Prize
1363,64976572,14.0,,5,20,/qinhui1999/training-tf-roberta-large-on-mlm,CommonLit Readability Prize
1364,69657809,1.0,,3,14,/mathislucka/commonlitreadability-r3,CommonLit Readability Prize
1365,63271787,28.0,,0,4,/shinomoriaoshi/readability-data-augmentation,CommonLit Readability Prize
1366,70234632,9.0,,1,5,/nmkt6e6d6b74/training-roberta-large-using-cross-entropy,CommonLit Readability Prize
1367,66880106,5.0,,0,0,/w5833946/f1-itpt,CommonLit Readability Prize
1368,67789829,48.0,0.4572926618489245,2,19,/kaerunantoka/commonlit-110-inf,CommonLit Readability Prize
1369,65475391,10.0,,0,2,/chamecall/bert-train,CommonLit Readability Prize
1370,69742148,49.0,0.4510683804344046,3,11,/nyleve/3-roberta-electra-deberta-4-layer,CommonLit Readability Prize
1371,64518177,37.0,,1,31,/teeyee314/readability-url-scrape,CommonLit Readability Prize
1372,103198408,75.0,,0,1,/neilz0211/fork-of-clrp-inference-emsemble-83bac6,CommonLit Readability Prize
1373,96106910,66.0,,0,2,/hengwdai/commonlit-readability-auto3ml,CommonLit Readability Prize
1374,61911545,50.0,,18,164,/abhishek/step-1-create-folds,CommonLit Readability Prize
1375,64897398,31.0,0.4954984328454342,0,1,/gilfernandes/commonlit-pytorch-distilbart-svm,CommonLit Readability Prize
1376,63261731,52.0,,4,14,/maunish/clrp-pytorch-train-tpu,CommonLit Readability Prize
1377,69994355,106.0,,2,6,/muktan/roberta-large-double-attention-1-2-4-8-16-20,CommonLit Readability Prize
1378,62004146,90.0,0.5501250395540694,4,14,/hengzheng/simpletransformers-regression-starter-less-code,CommonLit Readability Prize
1379,62390651,60.0,,0,5,/muhammad4hmed/commonlit-hierarchical-attention-networks,CommonLit Readability Prize
1380,69646429,194.0,0.4838392085017152,2,9,/allohvk/comlit-tryst-with-han,CommonLit Readability Prize
1381,63995709,354.0,0.5375839038483983,5,18,/dagnelies/kiss-roberta,CommonLit Readability Prize
1382,68980503,251.0,0.4597839752558592,29,57,/pichenguang/commonlit-two-models-with-new-model,CommonLit Readability Prize
1383,68711875,299.0,,0,1,/o00585/464-pre6,CommonLit Readability Prize
1384,63758281,40.0,0.6579546936884687,2,17,/shahules/commonlit-roberta-xgb-ensemble,CommonLit Readability Prize
1385,81364860,101.0,0.5527318267930429,1,0,/mst8823/baseline-001-infer,CommonLit Readability Prize
1386,66145036,87.0,0.4819112365880694,1,10,/mananjhaveri/transformers-for-the-first-time,CommonLit Readability Prize
1387,68378649,338.0,,1,0,/joezzb/synonyms,CommonLit Readability Prize
1388,67068876,108.0,0.474509010660022,9,98,/andretugan/lightweight-roberta-solution-in-pytorch,CommonLit Readability Prize
1389,61750154,113.0,0.6691985292654884,5,34,/ulrich07/ridge-regression-starter,CommonLit Readability Prize
1390,68741668,109.0,0.4691307692534728,0,0,/urvishp80/roberta-base-last-2-hs-inference-seed-3000,CommonLit Readability Prize
1391,64183571,192.0,,0,0,/andyanybody/fork-of-commonlit-readability-prize-roberta-torch,CommonLit Readability Prize
1392,66545677,99.0,,1,0,/bacterio/1-bd-ia-directo-eda,CommonLit Readability Prize
1393,64384346,191.0,,0,0,/pppass/commonlit-readability-robertalarge-tf-stratifie,CommonLit Readability Prize
1394,62379568,1295.0,0.545744765850627,0,4,/zefirchik/start-bert-models,CommonLit Readability Prize
1395,64376039,126.0,,10,11,/wmanka/roll-your-own-rnn-pytorch,CommonLit Readability Prize
1396,62568629,253.0,1.116190771217855,0,7,/sourabhy/common-lit-cnn-model,CommonLit Readability Prize
1397,63085043,611.0,,0,0,/kumapo/bert-baseline-training-validation,CommonLit Readability Prize
1398,61863356,185.0,,6,14,/snnclsr/commonlit-pytorch-distilbert-training,CommonLit Readability Prize
1399,121521218,118.0,,0,0,/mahluo/pytorch-roberta-pretrain,CommonLit Readability Prize
1400,64111678,308.0,,2,8,/lekynam2000/bart-custom-loss-use-stderror,CommonLit Readability Prize
1401,67811633,216.0,0.4865747471255596,1,13,/vineethakkinapalli/clrp-roberta-base-representation-techniques,CommonLit Readability Prize
1402,65446086,136.0,0.8130595898378441,0,7,/hinepo/clrp-textstat-feature-eng-xgb-importances,CommonLit Readability Prize
1403,62245789,246.0,,5,58,/heyytanay/commonlit-eda-understanding-the-competition,CommonLit Readability Prize
1404,67450480,153.0,1.5466640475051796,0,4,/rajat95gupta/commonlit-roberta-base-starter-implementation,CommonLit Readability Prize
1405,67642861,352.0,,2,3,/katsuyanomura/eda-crp,CommonLit Readability Prize
1406,68618729,150.0,0.482900123994155,0,1,/shrey19/notebook89fa882372,CommonLit Readability Prize
1407,64615496,129.0,0.4787273426827315,15,31,/duttadebadri/eda-basline-modeling-commonlit-passages,CommonLit Readability Prize
1408,66837496,235.0,,1,11,/julian3833/1-learning-out-of-the-box-bert-lb-0-577,CommonLit Readability Prize
1409,62378731,627.0,0.611084174322704,0,9,/gaetanlopez/pytorch-roberta-inference,CommonLit Readability Prize
1410,65035458,183.0,,4,25,/utcarshagrawal/commonlit-eda-most-nlp-techniques,CommonLit Readability Prize
1411,64016695,340.0,,1,17,/ajax0564/training-tf-roberta-on-mlm,CommonLit Readability Prize
1412,63568012,289.0,,9,30,/ammarnassanalhajali/commonlit-readability-eda,CommonLit Readability Prize
1413,69614171,65.0,,2,10,/authman/clit-fails,CommonLit Readability Prize
1414,69959759,594.0,,0,1,/jacob34/commonlit-create-target-samples,CommonLit Readability Prize
1415,65758814,285.0,,2,11,/yus002/readability-will-i-overfit,CommonLit Readability Prize
1416,62195471,298.0,,9,32,/indranilbhattacharya/eda-feature-engineering,CommonLit Readability Prize
1417,88433360,301.0,,3,11,/wuharlem/bert-simple,CommonLit Readability Prize
1418,62606780,159.0,0.7431858679166369,1,4,/konumaru/baseline-with-linear-regression,CommonLit Readability Prize
1419,63537872,1095.0,,4,65,/hannes82/commonlit-readability-roberta-simple-baseline,CommonLit Readability Prize
1420,69400664,1112.0,,0,0,/joshualancaster/commonlit-readability-prize-roberta-torch-itpt,CommonLit Readability Prize
1421,69556229,350.0,,0,1,/leontrout/useful,CommonLit Readability Prize
1422,69667222,351.0,0.8248618259663303,0,0,/liuyuanjiang/test-model,CommonLit Readability Prize
1423,66216786,330.0,,12,27,/gabellinifrancesco/nlp-from-bag-of-words-to-transformer-commonlit,CommonLit Readability Prize
1424,63075127,668.0,0.7003806962093402,9,35,/safavieh/basic-word-based-model,CommonLit Readability Prize
1425,69272190,341.0,,0,0,/kuroyuli/commonlit-readnet-using-fastai,CommonLit Readability Prize
1426,64233075,714.0,0.4777874238530838,23,145,/rhtsingh/commonlit-readability-prize-roberta-torch-infer,CommonLit Readability Prize
1427,64990361,447.0,,0,0,/bongbu/notebook41b8773172,CommonLit Readability Prize
1428,68522238,449.0,0.8225093517092799,3,25,,CommonLit Readability Prize
1429,67840001,603.0,,22,70,/debarshichanda/pytorch-commonlit-readability-bert-baseline,CommonLit Readability Prize
1430,62800944,457.0,0.6041481726998089,22,139,/ravishah1/readability-feature-engineering-non-nn-baseline,CommonLit Readability Prize
1431,64753628,471.0,,2,4,/rubiales/scraping-data-augmentation,CommonLit Readability Prize
1432,63635488,481.0,0.7049002413990983,0,1,/lucamtb/readibily-nn,CommonLit Readability Prize
1433,69371699,485.0,,0,2,/pranonraian/clrp-one-roberta-model,CommonLit Readability Prize
1434,66542402,512.0,,0,4,/tusonggao/clrp-pytorch-roberta-base-my-first-model-train,CommonLit Readability Prize
1435,65953440,516.0,0.7969254309237325,4,10,/amiteshgangrade/gradient-boosting-with-glove-embedding,CommonLit Readability Prize
1436,69427567,523.0,1.3880152142993465,0,0,/surajitcba2021/clrp-gru-withattention,CommonLit Readability Prize
1437,66287849,527.0,0.5224024038892141,4,28,/tensorchoko/commonlit-readability,CommonLit Readability Prize
1438,63670481,547.0,0.5169819092532127,9,11,/bhaveshkumar2806/commonlit-readability-basic-eda-and-roberta-base,CommonLit Readability Prize
1439,63670481,547.0,0.5401660099239928,9,11,/bhaveshkumar2806/commonlit-readability-basic-eda-and-roberta-base,CommonLit Readability Prize
1440,63670481,547.0,0.52043328386679,9,11,/bhaveshkumar2806/commonlit-readability-basic-eda-and-roberta-base,CommonLit Readability Prize
1441,62719142,558.0,0.5337438621729884,46,174,/dimitreoliveira/commonlit-readability-eda-roberta-tf-baseline,CommonLit Readability Prize
1442,62341715,1026.0,,5,13,/cascadinglight/commonlit-dimensionality-reduction-and-eda,CommonLit Readability Prize
1443,62265373,561.0,0.6230415502350282,0,8,/manabendrarout/eda-bow-classical-model-with-autokeras-ensemble,CommonLit Readability Prize
1444,81622136,562.0,1.147182248660097,2,4,/aditidutta/clrp-gpt2-implementation,CommonLit Readability Prize
1445,68782905,577.0,,2,9,/bryanb/first-approach-using-xgboost-with-hyperopt,CommonLit Readability Prize
1446,76042507,1070.0,0.7874403095597421,0,0,/pdan93/clrp-features-only-model,CommonLit Readability Prize
1447,62757578,587.0,,6,25,/crained/deberta-pytorch-commonlit-readability-train,CommonLit Readability Prize
1448,67803538,343.0,0.5227515077331447,0,0,/ktamta/eda-baseline,CommonLit Readability Prize
1449,65951041,204.0,,0,1,/bumjunkoo/commonlit-run-glue,CommonLit Readability Prize
1450,62528324,660.0,0.5260995366151014,0,19,/kshitijmohan/commonlit-readability-bert-train-inference,CommonLit Readability Prize
1451,65766610,609.0,0.6675316790042432,4,21,/syurenuko/clrp-word2vec-lightgbm-baseline,CommonLit Readability Prize
1452,67756599,903.0,,0,0,/nicolesy/clrp-inference,CommonLit Readability Prize
1453,69610799,612.0,,1,2,/lililycai/clrp-pytorch-roberta-pretrain,CommonLit Readability Prize
1454,68263036,685.0,,0,0,/juanscanlan/commonlit-inference,CommonLit Readability Prize
1455,69503299,602.0,0.5529127664059246,0,0,/maheller/universal-sentence-model-5-fold,CommonLit Readability Prize
1456,62979654,728.0,1.3650472290269169,0,8,/mzntaka0/simple-vectorization-using-doc2vec,CommonLit Readability Prize
1457,63685976,1348.0,,0,2,/lucabottero/statistical-features-from-text,CommonLit Readability Prize
1458,62274835,752.0,0.4864004413013947,11,18,/ankur310794/crp-mix-6-models-inference,CommonLit Readability Prize
1459,68509524,769.0,,8,25,/renjithrrkj/readnet-implemetation,CommonLit Readability Prize
1460,68619717,772.0,,2,4,/kartikbhargav/clrp-roberta-model-and-inference,CommonLit Readability Prize
1461,66247151,774.0,0.9823291619315886,0,1,/haiyunhu/commonlitreadabilityprize-train,CommonLit Readability Prize
1462,64315075,790.0,0.5450459586768073,0,0,/nityasevak/a-zero-feature-engineering-approach,CommonLit Readability Prize
1463,61743713,796.0,0.8460746845441958,0,5,/lawrencechernin/ridge-regression-starter-with-stop-words,CommonLit Readability Prize
1464,68700596,1081.0,,2,6,/atamazian/clrp-model-with-various-poolers,CommonLit Readability Prize
1465,65433502,823.0,,0,0,/wecdecqw/commonlith-bert,CommonLit Readability Prize
1466,67857179,926.0,0.5078481163108558,3,9,/calvchen/bert-regression-using-pytorch,CommonLit Readability Prize
1467,132100789,829.0,,0,0,/ineed21eep/commonlitreadability-r3,CommonLit Readability Prize
1468,64661968,837.0,,0,2,/pavelpds1/readability-fcnn-embedding,CommonLit Readability Prize
1469,129347470,840.0,,0,1,/kayvanshah/commonlit-readability-roberta-tf,CommonLit Readability Prize
1470,61980602,845.0,0.778760032173957,1,5,/jiny333/simple-baseline-using-pycaret-training-inference,CommonLit Readability Prize
1471,61777228,879.0,,4,15,/ayushggarg/commonlit-readability-prize-eda-and-baseline,CommonLit Readability Prize
1472,69473393,690.0,,0,0,/dhirenkakkar/custom-target-bootstrapping,CommonLit Readability Prize
1473,68994342,1085.0,0.4738850291935694,0,0,/tutty1992/clrp-pytorch-roberta-inference-rbt-l-rbt-b-tpu,CommonLit Readability Prize
1474,64404064,671.0,,6,11,/sharrpie/commonlit-readability-eda-fe-topic-modelling,CommonLit Readability Prize
1475,62556399,1071.0,,7,14,/sauravmaheshkar/commonlit-tensorflow-weights-biases,CommonLit Readability Prize
1476,63402126,1032.0,0.5767089098121257,1,15,/aristotelisch/basic-text-processing-lda-roberta-transformer,CommonLit Readability Prize
1477,63583277,1120.0,,0,1,/revathiprakash/commonlit-readability-eda-kit-wip,CommonLit Readability Prize
1478,64330880,44.0,,0,6,/solorzano/comparison-of-huggingface-text-model-features,CommonLit Readability Prize
1479,63422609,934.0,,17,88,/gunesevitan/commonlit-readability-prize-eda,CommonLit Readability Prize
1480,69850895,659.0,0.4678104958670315,0,2,/davidmezzetti/commonlit-mean-pooled-regression,CommonLit Readability Prize
1481,68357748,127.0,0.4706740612216677,0,1,/wuyhbb/inference-large,CommonLit Readability Prize
1482,64824263,1304.0,0.8152618110949119,0,4,/meihanw/commonlit-autokeras-try-out,CommonLit Readability Prize
1483,68586810,1322.0,0.4677188603896895,1,12,/yogeshkulkarni/commonlit-readability-prize-with-pytorch,CommonLit Readability Prize
1484,68065132,1326.0,0.5389438611533695,0,0,/kabhinay/roberta-base-inference,CommonLit Readability Prize
1485,63056848,635.0,0.4846384857334316,0,19,/lars123/neural-tangent-kernel,CommonLit Readability Prize
1486,62823592,1343.0,0.6581620466183049,0,3,/kazu02/commonlitreadabilityprize-model1,CommonLit Readability Prize
1487,63063765,1163.0,,0,0,/mehrankamal/commonlit-roberta-cnn,CommonLit Readability Prize
1488,63009046,1367.0,,0,12,/maostack/clrp-how-to-get-text-embedding-from-roberta,CommonLit Readability Prize
1489,68099284,1173.0,,0,3,/sergeykubarev/commonlit-readability-simple-models-to-start-with,CommonLit Readability Prize
1490,64998324,1183.0,,2,4,/elemento/litread-ml,CommonLit Readability Prize
1491,66399914,1187.0,,6,14,/tatamikenn/rough-argument-of-theoretical-lower-bound,CommonLit Readability Prize
1492,65447785,1194.0,,0,1,/nikolayromanenkov/lightautoml-roberta,CommonLit Readability Prize
1493,66088281,1213.0,0.7608919223110676,2,5,/w1023672708/tfidf-xgboost,CommonLit Readability Prize
1494,67297963,2693.0,0.7238345446128245,0,3,/vigneshmano/conv1d-test-1,CommonLit Readability Prize
1495,64347274,937.0,0.5887803146248615,18,40,/leighplt/simple-recurrent-model-pytorch,CommonLit Readability Prize
1496,62025531,1159.0,,2,6,/infernape/textstat-linearregression,CommonLit Readability Prize
1497,64229764,1235.0,0.6249799769646619,0,1,/jinhangjiang/commonlit-readability-sbert-dl-jiang,CommonLit Readability Prize
1498,61747396,1247.0,1.0257859623912724,2,20,/louise2001/nltk-commonlit-starter-notebook,CommonLit Readability Prize
1499,64645075,1256.0,0.7065029667954034,2,3,/stpeteishii/commonlit-readability-bert-xgboost,CommonLit Readability Prize
1500,65756526,1421.0,0.7180342998907501,2,2,/annazhukovets/read-rate-svr,CommonLit Readability Prize
1501,68343569,1274.0,,2,33,/the0electronic0guy/commonlit-roberta-top-12,CommonLit Readability Prize
1502,66954972,1280.0,,10,56,/asvskartheek/bert-tpus-jax-huggingface,CommonLit Readability Prize
1503,62997970,1286.0,,2,7,/deb009/commonlit-readability-prize-eda,CommonLit Readability Prize
1504,69579299,652.0,0.4701890549373378,0,2,/ruoxijia/clrp-mp-xgb,CommonLit Readability Prize
1505,69131526,1415.0,,1,0,/davidgzx/stratifiedkfold-on-commonlit-dataset,CommonLit Readability Prize
1506,63063996,1376.0,,0,3,/bharadwajvedula/lb-0-683-tf-glove840b,CommonLit Readability Prize
1507,95487990,1386.0,,0,4,/charliezimmerman/clrp-inference-robertabase-robertalarge-ensemble,CommonLit Readability Prize
1508,82004564,1296.0,0.6623640710380062,0,12,/masatomurakawamm/clrp-roberta-simple-finetune-baseline-1,CommonLit Readability Prize
1509,65535889,1353.0,,0,0,/kirichenko17roman/dl-lab-14-sequence-classification-regression,CommonLit Readability Prize
1510,69467589,1619.0,,0,0,/markwijkhuizen/commonlit-training,CommonLit Readability Prize
1511,69197776,1578.0,,0,2,/mbmackenzie/feature-engineering-and-tfidf,CommonLit Readability Prize
1512,69375246,1375.0,0.4747823612079941,0,2,/hassanrady/roberta-torch-with-svr,CommonLit Readability Prize
1513,61927658,1454.0,,2,10,/houssemayed/exploratory-data-analysis,CommonLit Readability Prize
1514,69641051,1469.0,,0,0,/yogesh1190/rating-passage-reading-complexity,CommonLit Readability Prize
1515,79222665,1533.0,,0,0,/steve5438/commonlit-baseline-model,CommonLit Readability Prize
1516,66459101,1808.0,,0,0,/akabaev/baseline-tf-distilbert,CommonLit Readability Prize
1517,65211067,1561.0,,0,22,/takamichitoda/commonlit-classical-methods-for-text-readability,CommonLit Readability Prize
1518,66005470,1585.0,,0,0,/hwangdongjun/predict-readability,CommonLit Readability Prize
1519,67580119,1532.0,0.5928475934571555,0,2,/chtalhaanwar/simplest-solution,CommonLit Readability Prize
1520,72486385,1824.0,,1,2,/angyalfold/roberta-large-k-fold-models,CommonLit Readability Prize
1521,69516364,1434.0,,24,83,/alincijov/nlp-starter-logsoftmax-nlloss-cross-entropy,CommonLit Readability Prize
1522,61969979,1594.0,,3,4,/srijita97/eda-work,CommonLit Readability Prize
1523,61775143,1362.0,,5,12,/aishwarya2490/commonlit-readability-prize-eda-cleaning-data,CommonLit Readability Prize
1524,63496010,1564.0,0.4823384508869472,2,10,/urstrulysai/ensemble-just-do-it,CommonLit Readability Prize
1525,62259947,1695.0,0.7231830843663859,0,5,/pranav082001/commonlit-simple-ensemble-models-ml,CommonLit Readability Prize
1526,64110400,1822.0,,0,1,/vijendersingh412/classification-with-tensorflow-and-use-large,CommonLit Readability Prize
1527,62464370,1485.0,,1,11,/darknesszx/roberta-simple-roberta-large-baseline,CommonLit Readability Prize
1528,63580724,1499.0,0.6337463534584346,0,0,/iammir/commonlit-distil-roberta,CommonLit Readability Prize
1529,67228302,1705.0,0.4912622825279698,0,2,/justinchae/crp-regression-with-roberta-and-lightgbm,CommonLit Readability Prize
1530,67228302,1705.0,0.4912622825279698,0,2,/justinchae/crp-regression-with-roberta-and-lightgbm,CommonLit Readability Prize
1531,66032768,1806.0,,1,3,/hjhgjghhg/commonlit-readability-roberta-pretrain,CommonLit Readability Prize
1532,66432359,1477.0,,0,1,/heyangk/kkkkk,CommonLit Readability Prize
1533,61741223,1557.0,0.8877973440354269,1,12,/pavelvod/simple-starter-baseline,CommonLit Readability Prize
1534,61751147,1735.0,,8,67,/konradb/linear-baseline-with-cv,CommonLit Readability Prize
1535,67236242,1844.0,0.5586186848995461,0,0,/sourabh219/roberta-baseline-model,CommonLit Readability Prize
1536,64674242,1689.0,,0,1,/artemzapara/commonlit-readability-prize-eda,CommonLit Readability Prize
1537,62679397,1553.0,,11,16,/abhilashreddyy/a-deeper-eda-on-pos-tags-topic-modelling-more,CommonLit Readability Prize
1538,62250577,1678.0,0.6163865262828453,2,5,/bootiu/commonlit-pytorch-lightning-bert-benchmark,CommonLit Readability Prize
1539,63374210,1784.0,,2,2,/tommasomarzi/sub-scoring-error,CommonLit Readability Prize
1540,66068367,1708.0,,0,0,/drzhuzhe/commonlit-stratified-kfold,CommonLit Readability Prize
1541,68956598,1604.0,,0,3,/binhhuunguyen/pytorch-roberta-meanpooling-attention,CommonLit Readability Prize
1542,67732189,1913.0,,0,0,/azertway/textstat-features-ridge,CommonLit Readability Prize
1543,64072596,1668.0,,16,57,/thedrcat/commonlit-what-are-we-reading-about,CommonLit Readability Prize
1544,66141199,1911.0,0.7461554424110586,1,4,/pawan2905/commonlit-readability-prize,CommonLit Readability Prize
1545,62794962,1853.0,,1,4,/dpaluszk/commonlit-cannot-submit-submission-csv-not-found,CommonLit Readability Prize
1546,62254339,1879.0,,0,10,/hayahiko/ridge-10folds-step-by-step,CommonLit Readability Prize
1547,67744521,1761.0,0.6806364739491999,0,0,/thegreatjayant/deep-evidential-regression,CommonLit Readability Prize
1548,62532049,1770.0,,0,18,/harshsharma511/one-stop-understanding-eda-bert-baseline,CommonLit Readability Prize
1549,66409646,1745.0,,0,2,/heyanghuang/baseline-hhy-1-0,CommonLit Readability Prize
1550,61826301,1930.0,0.677781796109765,1,9,/semyonkoshkarov/tf-idf-linearsvr-baseline,CommonLit Readability Prize
1551,64045771,1866.0,0.7482076226898513,12,14,/krishna1997gopal/important-in-readability-eda-tf-idf-w2v-xg-boost,CommonLit Readability Prize
1552,65080432,1828.0,,25,156,/andradaolteanu/i-commonlit-explore-xgbrf-repeatedfold-model,CommonLit Readability Prize
1553,66147121,1894.0,,4,6,/osblouf/external-data-for-model-pretraining,CommonLit Readability Prize
1554,62949756,1826.0,,1,3,/ttjccc/gaussian-multi-target-regularization,CommonLit Readability Prize
1555,68351357,1981.0,,0,0,/ruriarmandhani/clrp-roberta-lstm,CommonLit Readability Prize
1556,61929360,1927.0,0.7834870422385329,0,7,/ajain3982/commonlit-readability-skipgrams-linearreg,CommonLit Readability Prize
1557,89256712,1854.0,,0,0,/toutatsu/roberta-test,CommonLit Readability Prize
1558,64568872,1977.0,0.4993234666280849,8,14,/eneszvo/bert-roberta-distilbert-ensemble-5-fold-cv,CommonLit Readability Prize
1559,63116852,1959.0,,0,0,/xinruizhan/pretrained-bert-nn,CommonLit Readability Prize
1560,61795275,1893.0,,1,11,/aninda/commonlit-fastai,CommonLit Readability Prize
1561,69151787,1902.0,,1,4,/alankadiev/why-am-i-getting-notebook-threw-exception-error,CommonLit Readability Prize
1562,65120490,1900.0,,0,0,/pradipkumardas/1-commonlit-readability-eda,CommonLit Readability Prize
1563,68339693,1928.0,0.5408588062587437,0,1,/virajjayant/commonlit-readability-transformer-network,CommonLit Readability Prize
1564,69080057,1871.0,0.5071197187257737,6,27,/ligala/readability,CommonLit Readability Prize
1565,69845152,2082.0,,0,6,/hserdaraltan/commonlitreadability-bert-train,CommonLit Readability Prize
1566,61787867,2049.0,,0,3,/abhishekvermasg1/eda-what-do-we-teach-our-successors-v3,CommonLit Readability Prize
1567,62702293,2050.0,,0,7,/simakov/lama-bert-starter,CommonLit Readability Prize
1568,72502850,2054.0,,6,18,/evansimpson/eda-for-commonlit-reading-prize,CommonLit Readability Prize
1569,67649425,2058.0,0.6394919204839558,0,0,/aidenkim/commonlit-fastai-baseline,CommonLit Readability Prize
1570,62902846,2042.0,0.5997337694113765,1,4,/abee82/commonlit-readability-using-fastai-v2,CommonLit Readability Prize
1571,62930182,2021.0,,3,12,/takusid/popular-readability-formulas-and-metrics,CommonLit Readability Prize
1572,61952810,2053.0,,0,8,/aruthart/transformers-fastai-quick-starter,CommonLit Readability Prize
1573,61749497,2088.0,,7,26,/anaverageengineer/comlrp-baseline-for-complete-beginners,CommonLit Readability Prize
1574,69538631,2064.0,,0,0,/sagol79/sent-transformer-simple-normal-wiki-texts-svr,CommonLit Readability Prize
1575,66515314,2011.0,0.5782541152963034,0,1,/dragospancescu/commonlit,CommonLit Readability Prize
1576,65273493,2022.0,0.996774263511829,4,30,/adarshsng/complexity-cleaning-f-engg-bi-lstm,CommonLit Readability Prize
1577,67234992,2104.0,0.8349282602245377,0,0,/takiholadi/01-commonlit-linreg-4-features,CommonLit Readability Prize
1578,65571809,2198.0,0.6037101925317802,0,0,/brucebatmanwayne/clrp-distilbert-inference,CommonLit Readability Prize
1579,63263024,2188.0,0.8386324840355818,4,6,/evilmage93/common-lit-bilstm-based-regression,CommonLit Readability Prize
1580,66173146,2143.0,,6,10,/vermichel/commonlit-readability-prize,CommonLit Readability Prize
1581,61887867,2111.0,,2,9,/msafi04/commonlit-readability-bert-baseline-tf,CommonLit Readability Prize
1582,70602794,2144.0,,0,0,/gomesluiz/commonlit-readability-predict-distilbert-ft,CommonLit Readability Prize
1583,67715669,2126.0,,3,17,/tbhavnani/baseline-bert-regression-using-pytorch,CommonLit Readability Prize
1584,64134981,2140.0,0.7553149835113991,0,0,/rerere/commonlit-readability-prize-tf-idf-svm,CommonLit Readability Prize
1585,62763914,2158.0,0.7864539777569992,2,4,/ochaaaaaaan/commonlit-doc2vec-lightgbm,CommonLit Readability Prize
1586,62222287,2224.0,,0,3,/wanko123/exploring-features-and-model-building,CommonLit Readability Prize
1587,62310119,2135.0,,22,131,/jeongyoonlee/tf-keras-bert-baseline-training-inference,CommonLit Readability Prize
1588,68975467,2199.0,,0,2,/javi23ruiz/sbert-feature-engineering,CommonLit Readability Prize
1589,64427093,2180.0,,0,1,/mokicheese/fork-of-fork-of-transformers-cv-train-infe-b02165,CommonLit Readability Prize
1590,69458289,2325.0,0.5333298767634203,0,4,/ekaterinadranitsyna/text-readability-score,CommonLit Readability Prize
1591,69279588,2280.0,0.6247936225053138,0,0,/vungocbinh/commonlitreadabilityprize-bert,CommonLit Readability Prize
1592,70403622,2234.0,,2,11,/kylecloud/commonlit-readability-distilbert-5folds,CommonLit Readability Prize
1593,64667762,2203.0,0.7928299687673296,0,0,/dsquareindia/sbert-lstm,CommonLit Readability Prize
1594,69971628,2276.0,0.5297237534116369,0,0,/ptrikp/distillbert-bert-and-lgbm,CommonLit Readability Prize
1595,62658629,2181.0,,0,7,/virksaab/data-augmentation-and-correlation,CommonLit Readability Prize
1596,65553686,2244.0,,0,0,/coldog/notebook4submit,CommonLit Readability Prize
1597,61748924,2274.0,0.934665334203006,0,12,/yeayates21/commonlit-random-forest-na-ve-baseline,CommonLit Readability Prize
1598,64514381,2302.0,0.6359323131294757,23,56,/getitdone/beginners-friendly-notebook,CommonLit Readability Prize
1599,67937274,2287.0,0.5475095039577257,0,0,/konstantinitsi/bert2-submit1,CommonLit Readability Prize
1600,66784177,2290.0,0.5502305590985953,0,0,/kappawarrior/bertforsequence-with-kfold,CommonLit Readability Prize
1601,61815148,2279.0,,0,2,/roguecomputer/commonlit-readability-eda-plotly-word-cloud,CommonLit Readability Prize
1602,65359479,2308.0,0.5737296137139906,3,7,/ankarsingh/commonlit-text-cleaning-and-huggingface-model,CommonLit Readability Prize
1603,61964450,2285.0,0.5528609613085071,3,27,/shivanandmn/bert-pytorch-commonlit-readability-simple,CommonLit Readability Prize
1604,64906430,2328.0,,0,0,/hazigin/commonlit-readability-bert-lightgbm,CommonLit Readability Prize
1605,85043171,2348.0,,14,28,/mbonnet/baseline-pretrained-distilbert-and-regression,CommonLit Readability Prize
1606,68231359,2298.0,0.6512119220946069,4,10,/rowenwitt/rough-spacy-vectors-simple-bidirectional-lstm,CommonLit Readability Prize
1607,67499887,2286.0,0.6705601895714315,1,1,/nullpo20170707/word2vec-lightgbm,CommonLit Readability Prize
1608,63091330,2313.0,0.5829829048364992,0,2,/wptouxx/clrp-xgboost,CommonLit Readability Prize
1609,64099076,2245.0,0.8378272844882249,13,30,/accountstatus/readability-index-in-python,CommonLit Readability Prize
1610,65836782,2389.0,0.5700423684317142,0,0,/gavinjang/make-prediction,CommonLit Readability Prize
1611,68071651,2375.0,0.5707512819512676,1,2,/chenhuang666/a-baseline-model-implemented-by-bert,CommonLit Readability Prize
1612,63290852,2346.0,0.572081728556181,2,2,/vdefont/dummy,CommonLit Readability Prize
1613,66259947,2407.0,,14,38,/tarandeep97/performance-comparison-of-regression-models,CommonLit Readability Prize
1614,67181780,2428.0,,0,1,/dberezhnoy/edacode,CommonLit Readability Prize
1615,73984257,2416.0,,0,4,/dhruv1234/bert-regression,CommonLit Readability Prize
1616,63268671,2387.0,,0,5,/hotsonhonet/training-1,CommonLit Readability Prize
1617,67066604,2408.0,2.1808552588354497,0,1,/satyendrapandey16/notebook2bf07f2904,CommonLit Readability Prize
1618,64939768,2440.0,,0,7,/ejmejm/commonlit-eda-video-tutorial,CommonLit Readability Prize
1619,66143283,2404.0,,0,0,/ashuto7h/commonlit-readability2-model,CommonLit Readability Prize
1620,68287355,2458.0,0.5931772603623162,5,12,/panxnan/notebook-commonlit-readability-basedline,CommonLit Readability Prize
1621,68065340,2454.0,,0,0,/sapal6/common-lit-training,CommonLit Readability Prize
1622,68745298,2420.0,0.6300863479684122,0,5,/maximkazantsev/commonlit-readability-univ-sent-encoder-xgb,CommonLit Readability Prize
1623,61769483,2475.0,1.3802231521741133,4,8,/rushinaik/base-model,CommonLit Readability Prize
1624,69024589,2438.0,0.9652796015748404,0,1,/legend123345/notebookf0cf8e8b72,CommonLit Readability Prize
1625,69581091,2414.0,0.733142649094652,0,0,/serkankaanbahsi/attention-bert-gru,CommonLit Readability Prize
1626,63857632,2517.0,0.6223729696731801,0,5,/davidjlochner/commonlit-elastic-net,CommonLit Readability Prize
1627,84303839,2441.0,,2,11,/kroha5/nn-notebook-lstm,CommonLit Readability Prize
1628,63584640,2453.0,,0,1,/sergioli212/clrp-pytorch-train-clean,CommonLit Readability Prize
1629,67749637,2529.0,0.6232577442586071,0,0,/nageen94/commonlit-stacking-regressors,CommonLit Readability Prize
1630,61944890,2536.0,0.6245175885629125,1,18,/riteshpatil8998/commonlit-readability-cross-validation,CommonLit Readability Prize
1631,61832200,2541.0,0.6249770399987173,0,10,/jitshil143/submission-score-0-62,CommonLit Readability Prize
1632,66295574,2547.0,0.6356655087124681,0,1,/socathie/basic-centroid-w-fasttext,CommonLit Readability Prize
1633,65378501,2575.0,,0,0,/masatoootsuka/commonlit-eda,CommonLit Readability Prize
1634,69448916,2625.0,0.6580209471299922,0,0,/vikasvikkyd/commonlit,CommonLit Readability Prize
1635,64353836,2522.0,0.7325449002270944,0,1,/smsrikanthreddy/commonlit-eda-ml-baseline,CommonLit Readability Prize
1636,66479317,2659.0,0.656198982821525,3,2,/walywaly/readingease,CommonLit Readability Prize
1637,63554047,2615.0,,2,12,/talha1503/commonlitreadability-eda,CommonLit Readability Prize
1638,66860416,2640.0,,0,0,/ankitsinghcoder/fork-of-commonreadability,CommonLit Readability Prize
1639,66784752,2632.0,0.6726477578339765,9,19,/ds572370/deep-evidential-regression,CommonLit Readability Prize
1640,68589668,2603.0,0.6860255194511861,3,12,/ambarish/common-readability-embeddings-lstm,CommonLit Readability Prize
1641,67183160,2639.0,0.6675316790042432,0,1,/daviddirethucus/commonlit-readability-analysis,CommonLit Readability Prize
1642,66764127,2626.0,1.0458868618290966,4,3,/sambhavsg/data-understanding-and-baseline-model-clrp,CommonLit Readability Prize
1643,63170768,2688.0,0.697993573320254,0,0,/kunalman/clrc-eda-v0-1,CommonLit Readability Prize
1644,63547760,2602.0,,0,3,/ashutoshiitg/clrp-roberta-train,CommonLit Readability Prize
1645,64180597,2679.0,,3,7,/shashwatwork/commonlit-the-topic-modelling-approach-with-py,CommonLit Readability Prize
1646,65496793,2675.0,0.8152739473977567,5,26,/prajittr/commonlit-dnn-randomforest-linear-regression,CommonLit Readability Prize
1647,65970482,2700.0,0.6827186227137757,0,1,/mikelovesrobots/substantial-book-club-readability-prize,CommonLit Readability Prize
1648,65970482,2700.0,0.7097994822042509,0,1,/mikelovesrobots/substantial-book-club-readability-prize,CommonLit Readability Prize
1649,62020324,2731.0,0.7800523010373118,0,10,/rybalkin/basic-readability-metrics,CommonLit Readability Prize
1650,62447722,2756.0,0.6932659782624458,0,1,/nabanitaroy/commonlit-challenge,CommonLit Readability Prize
1651,69855803,2794.0,,0,3,/bannourchaker/commonlit-readability-prize-part1-eda-confirmed,CommonLit Readability Prize
1652,95292203,2749.0,0.6119358485088305,0,1,/cenzop/sentence-transformers-mpnetbase-no-tuning,CommonLit Readability Prize
1653,61820614,2740.0,,8,27,/mpwolke/uncommon-literature,CommonLit Readability Prize
1654,61845769,2839.0,0.8913340360775519,2,10,/pehahn/r-submission-1,CommonLit Readability Prize
1655,62506391,2678.0,,0,1,/sumeetsawant/commonlit-readability-ridge-baseline-0-7,CommonLit Readability Prize
1656,65333828,2690.0,,9,5,/krishnagk/notebookcommonlitlinearregression,CommonLit Readability Prize
1657,70450629,2769.0,,2,2,/abdelrhmanhosny/baseline-tfidf,CommonLit Readability Prize
1658,69780155,2738.0,,0,0,/nitekot/commonlit-readability-lab2,CommonLit Readability Prize
1659,65691238,2869.0,,0,1,/shivarama/samplebert,CommonLit Readability Prize
1660,146626591,2676.0,,0,0,/focusleft/commonlit-readability-lstm,CommonLit Readability Prize
1661,61832907,2747.0,0.7891635483274323,1,15,/hamzaghanmi/crp-eda-preprocessing-lightgbm,CommonLit Readability Prize
1662,65547886,2828.0,0.7575842588593535,0,0,/mrruslionkz/notebookff02ed0974,CommonLit Readability Prize
1663,69312015,2728.0,0.7106401940914759,4,16,/sahilt93/feature-extraction-bow-word2vec-tfidf-base-model,CommonLit Readability Prize
1664,62193952,2757.0,0.7404564291645596,10,23,/hamditarek/commonlit-readability-prize-lsa-lda-nn-baseline,CommonLit Readability Prize
1665,69771454,2721.0,,1,1,/romansafronenkov/commonlit-readability,CommonLit Readability Prize
1666,64698625,2817.0,,16,24,/udbhavpangotra/commonlit-readibility-prize-extensive-eda-model,CommonLit Readability Prize
1667,67902881,2841.0,0.8766826476085835,1,3,/mayur7garg/common-lit-readability-similarity,CommonLit Readability Prize
1668,67134381,2810.0,,0,5,/craving1030/caret-and-simple-text-fe-of-commonlit-readability,CommonLit Readability Prize
1669,69643409,2805.0,0.730137316785127,0,0,/jaydeep2401/commonlitreadability,CommonLit Readability Prize
1670,65474166,2767.0,,0,0,/iska47/commonlit-data-exploration-and-classic-algorithms,CommonLit Readability Prize
1671,61990253,2835.0,0.7355445219760207,0,9,/dearsijie/commonlit-readability-tf-lstm-tune-hyperparameters,CommonLit Readability Prize
1672,69180193,2804.0,0.7365484945448247,4,6,/nikitaglazunov/simple-dnn-to-achieve-decent-score,CommonLit Readability Prize
1673,61980132,2872.0,,12,32,/alaasedeeq/commonlit-readability-eda,CommonLit Readability Prize
1674,66521713,2836.0,0.7484898238657101,0,2,/th3niko/keras-bilsmt,CommonLit Readability Prize
1675,64638272,2974.0,1.043142375354125,0,1,/geoffcc/notebook935a1345d7,CommonLit Readability Prize
1676,69755238,2884.0,0.798643674024327,0,0,/devanshusingh/tensorflow-half-attention,CommonLit Readability Prize
1677,69579202,2862.0,,0,0,/lqtuantk97/group-4,CommonLit Readability Prize
1678,64974067,2911.0,,0,5,/donkeys/pip-install-package-from-dataset-no-internet,CommonLit Readability Prize
1679,62863644,2928.0,0.7489294734254028,0,3,/trantrikien239/preprocessing-and-svr-baseline,CommonLit Readability Prize
1680,69439680,2902.0,0.756539103163237,0,0,/sourabh3570/commonliteraturetarget,CommonLit Readability Prize
1681,61881541,2854.0,0.7508403960424069,8,25,/abdokamr/starter-eda-baseline-ridge-and-xgboost,CommonLit Readability Prize
1682,70250603,2958.0,,0,1,/trnkhnhlinh/kali-baseline,CommonLit Readability Prize
1683,66449126,2957.0,0.7629443026894279,0,2,/tracyporter/commonlit-readibility-svr,CommonLit Readability Prize
1684,63186048,3038.0,,1,2,/rohitpande/feature-engg-with-basic-linear-regression,CommonLit Readability Prize
1685,69497713,2952.0,,3,10,/iamshamikb/clrp-eda,CommonLit Readability Prize
1686,63224348,2875.0,0.8596741284675556,2,22,/jeongbinpark/using-keras-word-embedding,CommonLit Readability Prize
1687,66104518,3074.0,0.7608919223110676,1,5,/samarthsharma1408/commonlit-readability-price-simple-eda,CommonLit Readability Prize
1688,64516606,3071.0,0.7613266056229027,2,7,/fabriciotorquato/commonlit-readability-prize,CommonLit Readability Prize
1689,67174138,2946.0,0.7936724986965773,0,0,/rohitgupta29/basic-modelling-v1,CommonLit Readability Prize
1690,62670292,2936.0,,0,2,/gokhankesler/best-i-can-do-with-sklearn,CommonLit Readability Prize
1691,63802841,3144.0,,0,5,/aniketsharma00411/commonlit-readability-decision-tree,CommonLit Readability Prize
1692,68960860,3099.0,0.7725898861299683,1,4,/neel783d/commonlit-regression-model-comparison,CommonLit Readability Prize
1693,67403496,3078.0,0.7737963334138547,0,0,/muhammadalaref/mha-commonlit-readability-prize,CommonLit Readability Prize
1694,67866911,3048.0,,9,23,/junjitakeshima/beginner-s-gradual-improvement,CommonLit Readability Prize
1695,62723093,3076.0,,2,8,/rushikeshdarge/easiest-approach-with-good-rmse,CommonLit Readability Prize
1696,65472471,3030.0,0.790009982612172,0,0,/salikhussaini49/text-difficulty-prediction,CommonLit Readability Prize
1697,65472471,3030.0,0.7992738272593004,0,0,/salikhussaini49/text-difficulty-prediction,CommonLit Readability Prize
1698,65472471,3030.0,0.8004855976779296,0,0,/salikhussaini49/text-difficulty-prediction,CommonLit Readability Prize
1699,69508325,3054.0,0.8341755804827461,4,16,/mcarujo/ease-of-reading-prediction-nlp,CommonLit Readability Prize
1700,69508325,3054.0,0.8235326810153404,4,16,/mcarujo/ease-of-reading-prediction-nlp,CommonLit Readability Prize
1701,67142503,3084.0,0.7960636811733184,0,2,/altruisticemphasis/a-different-approach,CommonLit Readability Prize
1702,63553418,3146.0,0.7975737068218666,2,1,/duboisian/first-draft-model,CommonLit Readability Prize
1703,68773936,3139.0,0.8003088300998747,2,3,/mushaya/readability-index-basic,CommonLit Readability Prize
1704,68929539,3147.0,0.8064896137895623,0,0,/mattjohn/commonlit,CommonLit Readability Prize
1705,66293215,3196.0,0.8153668484519407,3,3,/dhlongle/basic-nlp-with-random-forest,CommonLit Readability Prize
1706,65451495,3206.0,0.8182299925438093,1,4,/jamesmcguigan/commonlit-xgbooost,CommonLit Readability Prize
1707,69154412,3223.0,0.8216610618327818,0,4,/wamateusz/linear-regression,CommonLit Readability Prize
1708,69542967,3304.0,0.8253779814877328,1,4,/shubhamsindal0098/commonlit-readibility-prize,CommonLit Readability Prize
1709,65160464,3300.0,0.8258301101192681,0,0,/raymishra/commonlit-building-from-the-base,CommonLit Readability Prize
1710,62063149,3263.0,0.8301441823595339,6,13,/kritanjalijain/commonlit-eda-and-lstm,CommonLit Readability Prize
1711,68999754,3260.0,0.8332485366822502,0,0,/mabdelhamidmamin/tree-regression-with-dale-table,CommonLit Readability Prize
1712,67750019,3216.0,0.8308591492434059,0,1,/k0mp0t/notebook808bc84371,CommonLit Readability Prize
1713,66191957,3271.0,,13,27,/sumantindurkhya/bert-for-regression,CommonLit Readability Prize
1714,62415573,3266.0,,1,6,/rahatreza/simple-randomforest-pipeline,CommonLit Readability Prize
1715,72117439,3251.0,1.0016227102845596,0,2,/omkargangan/commonlit-readability-competition,CommonLit Readability Prize
1716,68370550,3279.0,0.9268701216948144,2,5,/akashdotcom/commonlit-using-glove-bidirectional-lstm,CommonLit Readability Prize
1717,61995428,3258.0,0.8600702522175441,2,8,/abhibasavapattana/tensorflow-glove6b-lit-readability,CommonLit Readability Prize
1718,64167565,3219.0,0.8685258951145182,13,32,/gcmadhan/commonlit-readability-eda-modeling,CommonLit Readability Prize
1719,61792991,3252.0,0.932171804377205,0,0,/lautenschlager/readability-baseline-using-simple-stats,CommonLit Readability Prize
1720,69072206,3290.0,0.8782053560656624,0,1,/ivanajankov/lstm-nlp,CommonLit Readability Prize
1721,64033905,3341.0,0.999382312943107,0,0,/drdevasiakurian/simple-commonlitreadability-for-beginners,CommonLit Readability Prize
1722,62871373,3280.0,0.8841689233448968,0,2,/threesheds/simple-bow-baseline,CommonLit Readability Prize
1723,62837063,3349.0,0.8850242298311716,1,2,/ash112/commonlit-readability-gbr,CommonLit Readability Prize
1724,64860323,3344.0,0.8923986914638129,1,1,/gabrielcf8/commonlit-readability-competition,CommonLit Readability Prize
1725,64821805,3372.0,0.8946512355212751,2,10,/samsonteo/common-readibility001,CommonLit Readability Prize
1726,64432926,3363.0,0.9844301144237658,0,0,/tpothjuan/basic-eda-and-simple-lstm-model-prediction-tf,CommonLit Readability Prize
1727,69264698,3381.0,1.0573551539810668,0,0,/zmax505/notebook20b449257a,CommonLit Readability Prize
1728,118606510,3342.0,,0,3,/emrearuk/commonlitreadabilityprize,CommonLit Readability Prize
1729,61954787,3402.0,,2,5,/gustavomodelli/readability-lasso-regression,CommonLit Readability Prize
1730,63860902,3443.0,,0,0,/garuna1234/notebooka455286c9a,CommonLit Readability Prize
1731,62735358,3369.0,1.1621015180984895,6,9,/barun2104/commonlit-readability-eda-svd-modeling,CommonLit Readability Prize
1732,61800321,3431.0,0.971258242287794,2,12,/josephassaker/commonlit-readability-eda-na-ve-submission,CommonLit Readability Prize
1733,69368199,3404.0,0.9511061740603812,1,1,/nafiularaf/commonlit-readability,CommonLit Readability Prize
1734,69551715,3413.0,0.9587688628700796,0,0,/yswysc/notebook1qa2ws3ed4rf0ok,CommonLit Readability Prize
1735,61892916,3423.0,,1,7,/anubhav1302/readability-eda,CommonLit Readability Prize
1736,69530907,3447.0,0.9796456830993624,0,0,/skynguyen3101/notebook20e7c65f48,CommonLit Readability Prize
1737,64414181,3435.0,,0,0,/soumochatterjee/discover-difficulty-with-distill-bert,CommonLit Readability Prize
1738,61881713,3438.0,1.001673794429207,0,5,/tobiasgabrielkroll/readability,CommonLit Readability Prize
1739,69157054,3473.0,,0,3,/himako/allennlp-jsonnet-weak-example-using-roberta,CommonLit Readability Prize
1740,66812987,3518.0,,0,1,/biswajitroy7890/bert-embeddings-xgboost-regression-text-data,CommonLit Readability Prize
1741,62139314,3533.0,,0,5,/vivekprajapati2048/a-complete-commonlit-readability-prize-nb,CommonLit Readability Prize
1742,66771616,3561.0,1.4101817916496355,0,1,/reinaueda/submit,CommonLit Readability Prize
1743,69232198,3568.0,,0,4,/rsesha/commonlit-keras-nnlm-tfhub,CommonLit Readability Prize
1744,66738783,3592.0,1.4125268277333412,0,1,/jennyteng/project,CommonLit Readability Prize
1745,66412449,3555.0,,3,32,/thomaskonstantin/commonlit-text-analysis-baseline-modeling,CommonLit Readability Prize
1746,63772748,3624.0,2.2044248626469094,0,10,/shrutisaxena/commonlit-using-h2o-flow,CommonLit Readability Prize
1747,72326598,2.0,,10,62,/hirune924/2ndplace-solution,SETI Breakthrough Listen - E.T. Signal Search
1748,63001313,7.0,,3,22,/abebe9849/visualization-of-oof,SETI Breakthrough Listen - E.T. Signal Search
1749,65975914,11.0,,7,69,/kazanova/leak-submission-lb-0-991,SETI Breakthrough Listen - E.T. Signal Search
1750,66525465,9.0,,3,22,/titericz/removing-normalizing-leak-offline,SETI Breakthrough Listen - E.T. Signal Search
1751,71334044,15.0,,2,7,/tanulsingh077/qishen-ha-alaska-implementation,SETI Breakthrough Listen - E.T. Signal Search
1752,72240024,27.0,,0,0,/zekunn/seti-pretrain-effb1-fold0,SETI Breakthrough Listen - E.T. Signal Search
1753,66048919,41.0,,8,59,/datafan07/pytorch-lightning-single-fold-training-lb-0-97,SETI Breakthrough Listen - E.T. Signal Search
1754,69606240,65.0,,0,4,/urvishp80/pytorch-spatialattention-efficientnet-b1-training,SETI Breakthrough Listen - E.T. Signal Search
1755,62732875,77.0,,1,14,/parthdhameliya77/class-imbalance-weighted-binary-cross-entropy,SETI Breakthrough Listen - E.T. Signal Search
1756,68306576,57.0,,4,17,/kozodoi/seti-mean-and-std-of-new-data,SETI Breakthrough Listen - E.T. Signal Search
1757,66016136,134.0,,5,14,/hanx2smile/leak-submission-lb-1-0,SETI Breakthrough Listen - E.T. Signal Search
1758,70763742,95.0,,0,4,/aristarhbfg/similar-images-in-train-and-test,SETI Breakthrough Listen - E.T. Signal Search
1759,68274443,131.0,0.7040796577480415,8,44,/mrigendraagrawal/tf-spatial-seti-breakthrough-listen-starter,SETI Breakthrough Listen - E.T. Signal Search
1760,64327279,98.0,,7,26,/tuckerarrants/seti-rapids-knn,SETI Breakthrough Listen - E.T. Signal Search
1761,68359588,120.0,,1,10,/coldfir3/seti-dataset-generator-v1,SETI Breakthrough Listen - E.T. Signal Search
1762,68221175,143.0,,0,3,/tomooinubushi/0-9-roc-auc-pytorch-trainer-vit-kfolds,SETI Breakthrough Listen - E.T. Signal Search
1763,71661205,129.0,,0,0,,SETI Breakthrough Listen - E.T. Signal Search
1764,65124203,167.0,,0,1,/bartmaciszewski/seti-bl-1638x256-tfrec-data,SETI Breakthrough Listen - E.T. Signal Search
1765,70735755,188.0,,0,1,/quincyqiang/signal-search-exploratory-data-analysis,SETI Breakthrough Listen - E.T. Signal Search
1766,65280229,177.0,,5,20,/xuxu1234/efficientnet-b1-focal-loss-kfold-mix-up-lb-0-97,SETI Breakthrough Listen - E.T. Signal Search
1767,71097957,198.0,,13,39,/shionhonda/rerun-search-for-effective-data-augmentation,SETI Breakthrough Listen - E.T. Signal Search
1768,62730546,238.0,,1,24,/byfone/efficientnetb1-on-seti-breakthrough-listen,SETI Breakthrough Listen - E.T. Signal Search
1769,62564027,191.0,,0,8,/mathurinache/seti-bl-224x224-tfrec-data,SETI Breakthrough Listen - E.T. Signal Search
1770,62771363,332.0,,36,180,/usharengaraju/seti-eda-baseline-tensorflow-and-tpu,SETI Breakthrough Listen - E.T. Signal Search
1771,71788269,220.0,0.7670333937710404,7,35,/saurabhbagchi/ensemble-for-seti-competition,SETI Breakthrough Listen - E.T. Signal Search
1772,63232556,194.0,,0,7,/woosungyoon/seti-visualization-mean-values,SETI Breakthrough Listen - E.T. Signal Search
1773,64460094,302.0,,6,12,/inumellasricharanv2/seti-eda-pytorch-prior-knowledge,SETI Breakthrough Listen - E.T. Signal Search
1774,71494616,309.0,,0,0,/tegzes/lightning-single-fold-training-new-lb-0-732,SETI Breakthrough Listen - E.T. Signal Search
1775,71850577,370.0,0.7572544627507933,0,0,/bryanthogerson/three-extraterrestrial-termite-colony-v0-1,SETI Breakthrough Listen - E.T. Signal Search
1776,72496535,208.0,,9,16,/tatamikenn/image-cleaning-column-wise-normalization-knn,SETI Breakthrough Listen - E.T. Signal Search
1777,63030979,374.0,,1,1,/miyakawa2286/show-false-positives-from-baseline-oof,SETI Breakthrough Listen - E.T. Signal Search
1778,66007394,253.0,,3,34,/nyanpn/yet-another-leakage-lb0-995,SETI Breakthrough Listen - E.T. Signal Search
1779,65282115,364.0,,0,1,/xuzongniubi/efficientnet-b1-focal-loss-kfold-mix-up-lb-0-97,SETI Breakthrough Listen - E.T. Signal Search
1780,66649825,361.0,,17,36,/debarshichanda/efficientnetv2-mixup-leak-free,SETI Breakthrough Listen - E.T. Signal Search
1781,72439533,469.0,,11,26,/friedchips/magic-2-an-explanation,SETI Breakthrough Listen - E.T. Signal Search
1782,64250689,521.0,,1,3,/assign/seti-with-colab-pro-gpu-tensorflow,SETI Breakthrough Listen - E.T. Signal Search
1783,69041905,529.0,,0,1,/nakuuu/seti-bl-256x256-tfrec-data,SETI Breakthrough Listen - E.T. Signal Search
1784,62697928,534.0,,1,33,/micheomaano/simple-yet-effectiveb0-lb-0-96,SETI Breakthrough Listen - E.T. Signal Search
1785,71937761,593.0,,0,10,/anirudhg15/seti-et-baseline-efficientnetb3,SETI Breakthrough Listen - E.T. Signal Search
1786,66419400,568.0,,23,86,/heyytanay/pytorch-training-augments-vit-kfolds,SETI Breakthrough Listen - E.T. Signal Search
1787,69531670,584.0,0.7055527799719891,0,1,/xjingd/one-stop-understanding-eda-efficientnet,SETI Breakthrough Listen - E.T. Signal Search
1788,68266481,574.0,,6,14,/glazed/eda-looking-for-needles-in-all-the-wrong-places,SETI Breakthrough Listen - E.T. Signal Search
1789,70175137,618.0,0.6807224656484026,16,41,/kenjirokiyono/seti-simple-code-for-beginners-tensorflow,SETI Breakthrough Listen - E.T. Signal Search
1790,68260319,630.0,,0,0,/vikrant6767/seti-breakthrough-listen-tfdata,SETI Breakthrough Listen - E.T. Signal Search
1791,68279154,637.0,,5,41,/awsaf49/seti-bl-256x256-tfrecord-data,SETI Breakthrough Listen - E.T. Signal Search
1792,67726870,669.0,,0,0,/vungocbinh/seti-breakthrough-listen-cnn,SETI Breakthrough Listen - E.T. Signal Search
1793,66369634,657.0,,0,4,/gaetanpelletier/seti-autokeras,SETI Breakthrough Listen - E.T. Signal Search
1794,71972971,690.0,,0,9,/ethanwharris/seti-meets-lightning-flash,SETI Breakthrough Listen - E.T. Signal Search
1795,64698496,700.0,,0,3,/aramos/eda-seti-breakthrough-listen,SETI Breakthrough Listen - E.T. Signal Search
1796,68478177,699.0,0.5801506016639999,2,4,/ricopue/seti-simple-anomaly-detection,SETI Breakthrough Listen - E.T. Signal Search
1797,62570558,702.0,,1,12,/aninda/finding-aliens-fastai,SETI Breakthrough Listen - E.T. Signal Search
1798,72252029,719.0,0.5134751143928011,0,1,/anaclaricerezende/seti-basic-with-tensor-flow,SETI Breakthrough Listen - E.T. Signal Search
1799,71301661,740.0,,0,0,/nizado/seti-listen-toy-model-for-getting-started,SETI Breakthrough Listen - E.T. Signal Search
1800,64664757,767.0,,0,1,/rolandstenger/end2end-with-pytorch-lightning-and-wandb-0-96,SETI Breakthrough Listen - E.T. Signal Search
1801,64657052,2.0,6.117530392076638,8,58,/wrrosa/gsdc-position-shift,Google Smartphone Decimeter Challenge
1802,64618411,19.0,6.16417334079069,17,98,/dehokanta/baseline-post-processing-by-outlier-correction,Google Smartphone Decimeter Challenge
1803,64706121,7.0,5.639944494605687,8,116,/t88take/gsdc-phones-mean-prediction,Google Smartphone Decimeter Challenge
1804,68990473,35.0,,4,19,/avtobusbratiev/additional-gt-data-chipset-location,Google Smartphone Decimeter Challenge
1805,65270837,18.0,,17,97,/kuto0633/road-detection-and-creating-grid-points,Google Smartphone Decimeter Challenge
1806,67361906,60.0,,17,87,/alvinai9603/predict-next-point-with-the-imu-data,Google Smartphone Decimeter Challenge
1807,66807293,88.0,,1,31,/hyperc/gsdc-reproducing-baseline-wls-on-one-measurement,Google Smartphone Decimeter Challenge
1808,69293593,40.0,,5,34,/katomash/a-car-is-moving-or-not-accuracy-94,Google Smartphone Decimeter Challenge
1809,66102380,64.0,,13,58,/museas/estimating-the-direction-with-a-magnetic-sensor,Google Smartphone Decimeter Challenge
1810,70319283,101.0,,0,6,/kyochanpy/gsdc-check-degrees-simple-pp,Google Smartphone Decimeter Challenge
1811,62882271,69.0,,8,34,/carlmcbrideellis/google-smartphone-decimeter-eda,Google Smartphone Decimeter Challenge
1812,69264843,242.0,,8,72,/bpetrb/adaptive-gauss-phone-mean,Google Smartphone Decimeter Challenge
1813,67160957,341.0,,1,12,/ravishah1/google-gps-external-data-via-reverse-geocoders,Google Smartphone Decimeter Challenge
1814,63140603,80.0,6.214573409271781,0,0,/ak0210/demonstration-of-the-kalman-filter,Google Smartphone Decimeter Challenge
1815,69275183,77.0,5.338955602472179,0,2,/pythonlan/gsdc-smart-ensembling,Google Smartphone Decimeter Challenge
1816,69443709,120.0,5.236509224885075,20,66,/somayyehgholami/gsdc-smart-ensembling,Google Smartphone Decimeter Challenge
1817,69939903,180.0,5.23494485189077,0,14,/swimmy/fork-of-gsdc-smart-ensembling-fe1008,Google Smartphone Decimeter Challenge
1818,65140945,128.0,5.558628164256196,4,23,/rtombs/gsdc-blend,Google Smartphone Decimeter Challenge
1819,69180659,238.0,5.366599282750712,2,6,/gopalmahadevan/adaptive-gauss-phone-mean,Google Smartphone Decimeter Challenge
1820,68181202,263.0,5.530901881117563,3,15,/batprem/fork-of-fork-of-fork-of-fork-of-gsdc-blend-0a96ee,Google Smartphone Decimeter Challenge
1821,62709046,307.0,,0,61,/jpmiller/baseline-from-host-data,Google Smartphone Decimeter Challenge
1822,62716230,99.0,,12,114,/emaerthin/demonstration-of-the-kalman-filter,Google Smartphone Decimeter Challenge
1823,63244876,403.0,,0,5,/hamorahadi/notebook15bd24b3a9,Google Smartphone Decimeter Challenge
1824,63152466,412.0,6.208783282546445,8,61,/tqa236/kalman-filter-hyperparameter-search-with-bo,Google Smartphone Decimeter Challenge
1825,63152466,412.0,6.208783282546445,8,61,/tqa236/kalman-filter-hyperparameter-search-with-bo,Google Smartphone Decimeter Challenge
1826,65754038,424.0,,3,13,/muskan2006/exploring-the-datasets,Google Smartphone Decimeter Challenge
1827,66238368,378.0,,10,25,/cuttingmachine/all-in-one-data,Google Smartphone Decimeter Challenge
1828,66538073,486.0,41973.45271078759,2,14,/suryadeepti/pathlib,Google Smartphone Decimeter Challenge
1829,107671262,510.0,,0,0,/andrianinaraharijao/explore-gsdc-data-35220f,Google Smartphone Decimeter Challenge
1830,66067548,462.0,,1,3,/cancan077/kc-world-map-google-decimeter,Google Smartphone Decimeter Challenge
1831,64022423,522.0,,1,8,/maeyamada/verification-phonename-difference-eda,Google Smartphone Decimeter Challenge
1832,64588546,534.0,,2,11,/avivlevi815/gsdc-metric-evaluation-function,Google Smartphone Decimeter Challenge
1833,68575923,622.0,,1,2,/allanzhang1/submission-allan,Google Smartphone Decimeter Challenge
1834,62784472,582.0,,11,83,/mpwolke/wait-for-gps-kaggle,Google Smartphone Decimeter Challenge
1835,66028516,600.0,,4,12,/jmayes/gps-iterative-trilateration-intuition-building,Google Smartphone Decimeter Challenge
1836,66182479,648.0,,0,6,/srini2446/random-forest-regressors-google-decimeter,Google Smartphone Decimeter Challenge
1837,63062485,661.0,7.139570818786891,0,24,/ramswaroopbhakar14/baseline-appraoch-linear-regression,Google Smartphone Decimeter Challenge
1838,63062485,661.0,7.139570818786891,0,24,/ramswaroopbhakar14/baseline-appraoch-linear-regression,Google Smartphone Decimeter Challenge
1839,64311252,668.0,,0,9,/hugolaunay/gps-model,Google Smartphone Decimeter Challenge
1840,65094052,727.0,,34,92,/yasserhessein/eda-google-smartphone-decimeter,Google Smartphone Decimeter Challenge
1841,64142973,755.0,33.18551905262949,9,60,/foreveryoung/least-squares-solution-from-gnss-derived-data,Google Smartphone Decimeter Challenge
1842,66201777,774.0,,0,6,/n3n77i/sp-datafun,Google Smartphone Decimeter Challenge
1843,66819522,777.0,,3,8,/rabeyaakter/google-smartphone-decimeter-challenge,Google Smartphone Decimeter Challenge
1844,62713464,789.0,,1,8,/manang/google-smartphone-decimeter-challenge-wip,Google Smartphone Decimeter Challenge
1845,67183666,3344.0,,133,1006,/jiashenliu/introduction-to-financial-concepts-and-data,Optiver Realized Volatility Prediction
1846,67014226,3351.0,0.0,2,10,/sohommajumder21/optiver-competition-eda-predictions,Optiver Realized Volatility Prediction
1847,67066536,2946.0,0.0,6,27,/pratibha9/a-quick-model,Optiver Realized Volatility Prediction
1848,67102232,2629.0,,0,6,/gpreda/optiver-volatility-quick-look-to-the-data,Optiver Realized Volatility Prediction
1849,67242831,3133.0,,19,95,/konradb/we-need-to-go-deeper-and-validate,Optiver Realized Volatility Prediction
1850,67132712,3112.0,0.0,4,16,/abhishek1aa/feature-engineering-xgboost-lgbm-baseline,Optiver Realized Volatility Prediction
1851,67135503,3186.0,,0,2,/ksmcg90/optiver-basic-eda-w-stock-correlation,Optiver Realized Volatility Prediction
1852,67199806,3704.0,,2,4,/ishwor2048/optiver-realized-volatility-explore-prediction,Optiver Realized Volatility Prediction
1853,67207240,3709.0,0.0,0,0,/chiranjeevbit/optiver-realized-volatility-prediction-and-eda,Optiver Realized Volatility Prediction
1854,67539104,3697.0,0.0,14,13,/shivarama/optiver-realized-volatility-starter-kit-101,Optiver Realized Volatility Prediction
1855,67459243,3369.0,,0,1,/iiillliii/how-can-i-get-lagged-features,Optiver Realized Volatility Prediction
1856,67400761,3370.0,,0,4,/krishnamore/optiver-realized-volatilityz-prediction,Optiver Realized Volatility Prediction
1857,67879395,446.0,,0,2,/ozmanakram/we-need-to-go-deeper,Optiver Realized Volatility Prediction
1858,67477918,3658.0,,0,1,/yiminglii/volatility-prediction,Optiver Realized Volatility Prediction
1859,67393862,2531.0,,2,2,/shamiulislamshifat/optiver-realized-volatility-prediction-gold,Optiver Realized Volatility Prediction
1860,67472635,3126.0,0.0,18,35,/shubhampandey253/the-notebook-you-need-understanding-orvp,Optiver Realized Volatility Prediction
1861,67818959,3203.0,,2,5,/eneszvo/eda-features-engineering-5-fold-cv-xgb-shap,Optiver Realized Volatility Prediction
1862,67566517,2871.0,,10,56,/shahmahdihasan/overly-simplified-ols-prediction,Optiver Realized Volatility Prediction
1863,67492200,2872.0,0.0,4,10,/faelk8/optiver-realized-volatility-eda,Optiver Realized Volatility Prediction
1864,67432679,2908.0,,0,2,/michaelgehrig/number-of-observations-per-bucket,Optiver Realized Volatility Prediction
1865,68655376,3740.0,,5,16,/christophercoffee/technical-factor-analysis,Optiver Realized Volatility Prediction
1866,67703003,2441.0,,2,15,/andrewkkchoi/wap-lr-visual-analysis-most-least-volatility,Optiver Realized Volatility Prediction
1867,67229573,2824.0,,2,8,/chaseos/parquet-patterns-for-loading-data,Optiver Realized Volatility Prediction
1868,67868369,2934.0,,1,5,/alessiopeluso/volatility-baseline,Optiver Realized Volatility Prediction
1869,67012992,2841.0,,0,9,/pehahn/test-arrow-lib,Optiver Realized Volatility Prediction
1870,67910589,3028.0,0.0,7,11,/benjamingowan/nice-r-arrow-features-funny,Optiver Realized Volatility Prediction
1871,67957090,887.0,0.0,5,14,/caesarlupum/xgb-purged-group-ts-validation,Optiver Realized Volatility Prediction
1872,67264351,2979.0,,0,2,/hectorbarrio/volatility-prediction-prepare-data,Optiver Realized Volatility Prediction
1873,69329513,2832.0,,4,92,/lucasmorin/optiver-realized-volatility-introduction,Optiver Realized Volatility Prediction
1874,68504550,2437.0,,0,2,/ninhson/manytoone-gru,Optiver Realized Volatility Prediction
1875,74216681,2241.0,,6,23,/cldavies/single-value-baseline,Optiver Realized Volatility Prediction
1876,69017539,1771.0,,2,23,/marcobeyer/lstm-starter,Optiver Realized Volatility Prediction
1877,67827749,2263.0,,1,10,/houndcl/time-id-in-hidden-test-set-doesn-t-start-from-0,Optiver Realized Volatility Prediction
1878,68479400,3626.0,,0,1,/sakshi1303/optiver-simple-ml-model-3608cb,Optiver Realized Volatility Prediction
1879,79171483,2510.0,,2,11,/kartik2khandelwal/optiverrealizedvolatility-v2-0-0,Optiver Realized Volatility Prediction
1880,69473296,3309.0,0.0,0,2,/teralasowmya/optiver-data-prediction,Optiver Realized Volatility Prediction
1881,68678861,3743.0,0.0,0,0,/chungchichang/kernel-ridge-regression-edited-based-on-weighted,Optiver Realized Volatility Prediction
1882,68407922,2965.0,,0,1,/pyrole/optiver-stock-correlations-analysis,Optiver Realized Volatility Prediction
1883,68843328,2376.0,,0,1,/rabeyaakter/optiver-realized-volatility-prediction-safari,Optiver Realized Volatility Prediction
1884,74071204,2312.0,,2,10,/abaojiang/ohlcv-and-technical-indicators,Optiver Realized Volatility Prediction
1885,68242112,2332.0,,0,0,/mountainking/lightgbm-starter-with-feature-engineering-idea,Optiver Realized Volatility Prediction
1886,68629218,3692.0,,16,57,/hyewon328/understand-and-visualize-volatility-data,Optiver Realized Volatility Prediction
1887,149604988,2344.0,,0,3,/khosiyatsabirova/introduction-to-financial-concepts-and-data,Optiver Realized Volatility Prediction
1888,68102124,2348.0,,23,47,/danwatson16/weighted-xgboost-with-stock-grouping-eda,Optiver Realized Volatility Prediction
1889,67877266,2648.0,,0,1,/kentaroaoyama/notebook481d35b081,Optiver Realized Volatility Prediction
1890,69173933,1712.0,0.0,0,16,/bhaveshkumar2806/volatility-prediction-eda-linear-regression,Optiver Realized Volatility Prediction
1891,67504667,639.0,,0,2,/semaule/eda-visualising-trading-data-optiver,Optiver Realized Volatility Prediction
1892,71259535,3609.0,,0,0,/monicafeng/optiverrealizedvolatility-v2-0-0,Optiver Realized Volatility Prediction
1893,69157285,1500.0,,43,341,/ragnar123/optiver-realized-volatility-lgbm-baseline,Optiver Realized Volatility Prediction
1894,69527204,3790.0,,0,1,/paarthbhasin/cnn-lstm-multivariate,Optiver Realized Volatility Prediction
1895,73592048,3574.0,,2,3,/ericpeterson/lgb-model-2,Optiver Realized Volatility Prediction
1896,68094503,2991.0,,0,0,/duckmoll/notebook2fc210ffb4,Optiver Realized Volatility Prediction
1897,67195745,2132.0,,2,25,/aerdem4/optiver-lofo-feature-importance,Optiver Realized Volatility Prediction
1898,70293336,3582.0,0.0,0,5,/teka1216/baseline-for-volatility-prediction-in-r,Optiver Realized Volatility Prediction
1899,70587798,3455.0,0.0,0,0,/tejasdokras/realized-volatility-predicton,Optiver Realized Volatility Prediction
1900,70826205,1717.0,,3,8,/greeneagle2/eda-orvp-using-dataprep,Optiver Realized Volatility Prediction
1901,68408585,2173.0,,9,37,/medali1992/optiver-feature-engineering-rapids-joblib,Optiver Realized Volatility Prediction
1902,71318137,3633.0,0.0,0,1,/avivlevi815/baseline-model-lgbm-0-4,Optiver Realized Volatility Prediction
1903,67757089,1362.0,,19,111,/tpmeli/insights-correlation-analysis-of-192-features,Optiver Realized Volatility Prediction
1904,72014078,318.0,,2,12,/redjumbie/another-nn-idea,Optiver Realized Volatility Prediction
1905,85204758,2851.0,,2,26,/carlmcbrideellis/optiver-interactive-shakeup-scatterplots,Optiver Realized Volatility Prediction
1906,71571013,3668.0,0.0,0,2,/yamitatsu/volatility-eda,Optiver Realized Volatility Prediction
1907,71621573,1245.0,,9,7,/noriakiendo/bias-of-time-ids-in-the-largest-targets,Optiver Realized Volatility Prediction
1908,71704271,2311.0,0.0,0,0,/zch19940222/volatity-prediction-lgb1,Optiver Realized Volatility Prediction
1909,72015370,2465.0,0.0,0,6,/mateuscco/feature-engineering-pipeline-optimized-lightgbm,Optiver Realized Volatility Prediction
1910,70260700,2411.0,,4,7,/craving1030/lgb-model-with-random-grid-searching-parmeters,Optiver Realized Volatility Prediction
1911,68238494,2318.0,,0,0,/devanshchowdhury/basic,Optiver Realized Volatility Prediction
1912,70884518,2170.0,,0,2,/vjagannath786/understanding-the-competititon-v1-0,Optiver Realized Volatility Prediction
1913,71493889,3723.0,,0,2,/lighttag/make-np-array-of-all-data,Optiver Realized Volatility Prediction
1914,100293949,3060.0,,0,2,/caesarmtuguinay/optiver-competition-first-approach,Optiver Realized Volatility Prediction
1915,68311789,2547.0,,26,36,/rajgandhi/optiver-volatility-prediction-lgbm,Optiver Realized Volatility Prediction
1916,68838447,2099.0,,0,0,/laurencelin/volatility-prediction-deprecated,Optiver Realized Volatility Prediction
1917,71154594,1449.0,,0,2,/patrikdurdevic/optiver-bamt-gbdt,Optiver Realized Volatility Prediction
1918,72353366,2200.0,,6,10,/bayismet/short-fast-nn-lgb,Optiver Realized Volatility Prediction
1919,70993942,1278.0,,0,0,/jiangair/lightgbm-starter-with-feature-engineering-idea,Optiver Realized Volatility Prediction
1920,71486768,1283.0,,18,46,/swimmy/optiver-lgb-with-optimized-params-feat,Optiver Realized Volatility Prediction
1921,68708031,1686.0,,0,0,/noisefallacy/notebook9ce6a5bcd2,Optiver Realized Volatility Prediction
1922,74698214,2051.0,,0,1,/takara710/submission-starter,Optiver Realized Volatility Prediction
1923,75503023,481.0,,1,3,/yusakunokubi/lightgbm-japanese,Optiver Realized Volatility Prediction
1924,73415361,1967.0,0.0,0,1,/markct/volatility-3,Optiver Realized Volatility Prediction
1925,67063803,1598.0,,16,35,/thanish/randomforest-starter-submission,Optiver Realized Volatility Prediction
1926,73585366,2657.0,0.0,11,14,/kevinbird15/fastai-tabular-optiver-starter-notebook,Optiver Realized Volatility Prediction
1927,67521191,120.0,,1,11,/jarfo1/volatility-correlation-among-stocks,Optiver Realized Volatility Prediction
1928,74487124,1912.0,,10,67,/hiromasatabuchi/baseline-simple-flow-with-lightgbm,Optiver Realized Volatility Prediction
1929,70410403,1467.0,,2,14,/aman2114/baseline-0-211,Optiver Realized Volatility Prediction
1930,71474190,609.0,,2,8,/tarlannazarov/optiver-lgb-with-optimized-params,Optiver Realized Volatility Prediction
1931,75693915,1556.0,,0,0,/sambhavsg/data-research-inference-optiver,Optiver Realized Volatility Prediction
1932,73572126,3521.0,0.0,0,1,/taehyunahn/first-submission,Optiver Realized Volatility Prediction
1933,71168780,1478.0,,7,33,/peterzcy/optiver-eda,Optiver Realized Volatility Prediction
1934,71357785,1010.0,,0,22,/shivansh002/xgboost-hyper-parameter-optimization,Optiver Realized Volatility Prediction
1935,72950542,436.0,,0,0,/sinatavakolibanizi/notebook922c6c83b4,Optiver Realized Volatility Prediction
1936,74173257,1583.0,,0,3,/sourabhy/orvp-eda,Optiver Realized Volatility Prediction
1937,75784265,467.0,,0,0,/atsushiiwasaki/orvp-data-preprocessing,Optiver Realized Volatility Prediction
1938,73864434,379.0,,0,3,/ellifa/catboost-incremental-learning-hyperopt,Optiver Realized Volatility Prediction
1939,75584579,1140.0,,0,8,/haiyunhu/introduction-to-financial-concepts-and-data-hu,Optiver Realized Volatility Prediction
1940,74003752,1173.0,,0,0,/tangtunyu/lgbm-infer,Optiver Realized Volatility Prediction
1941,66900116,67.0,,5,30,/munumbutt/wip-eda-on-the-orderbook,Optiver Realized Volatility Prediction
1942,67044876,1955.0,,3,28,/mayunnan/realized-volatility-prediction-code-template,Optiver Realized Volatility Prediction
1943,67539611,63.0,,21,197,/manels/lgb-starter,Optiver Realized Volatility Prediction
1944,68085169,2160.0,,1,8,/something4kag/example-r-pkg-without-internet-nns-for-optiver,Optiver Realized Volatility Prediction
1945,73963916,2889.0,,0,0,/dnging/linear-regression,Optiver Realized Volatility Prediction
1946,67457027,830.0,,2,12,/mhslearner/starter-basic-analysis-with-basic-model,Optiver Realized Volatility Prediction
1947,74159869,945.0,,0,1,/millerrfu/pickle,Optiver Realized Volatility Prediction
1948,69031556,127.0,,0,0,/masamichitoyama/volatility-prediction1,Optiver Realized Volatility Prediction
1949,71414778,185.0,,10,25,/mtinti/lgb-starter-eli5,Optiver Realized Volatility Prediction
1950,75509903,2536.0,,0,9,/k589k589/lightgbm-eda-mandarin,Optiver Realized Volatility Prediction
1951,67174350,816.0,,0,7,/daicongxmu/feature-engineering-tuned-xgboost-lgbm,Optiver Realized Volatility Prediction
1952,74493605,1793.0,,1,15,/tensorchoko/optiver-realized-eda,Optiver Realized Volatility Prediction
1953,74494800,1941.0,0.0,0,2,/aurorazxx/optiver-lightgbm,Optiver Realized Volatility Prediction
1954,72372409,603.0,,2,9,/victorsullivan/optiver-realized-volatility-prediction,Optiver Realized Volatility Prediction
1955,74078756,2799.0,0.0,0,1,/wonjunchoinada/notebook73c31f4859,Optiver Realized Volatility Prediction
1956,74078756,2799.0,0.0,0,1,/wonjunchoinada/notebook73c31f4859,Optiver Realized Volatility Prediction
1957,75560737,1562.0,,0,1,/izotov/85-55-blend-nn-lgb-3-diffmodels,Optiver Realized Volatility Prediction
1958,72620972,1291.0,,1,3,/abelmatas/naive-prediction,Optiver Realized Volatility Prediction
1959,72385247,703.0,,1,8,/kosukeponi/begginer-tried-predicting-realized-vol-lgb,Optiver Realized Volatility Prediction
1960,72382753,785.0,,0,4,/zxstont/short-fast-nn-lgb,Optiver Realized Volatility Prediction
1961,73088421,894.0,,2,4,/madquer/py-package-style-include-pk-code-lgb-tabn,Optiver Realized Volatility Prediction
1962,74397170,989.0,,17,36,/austinzhao/reproduction-explanation-lgbm-baseline,Optiver Realized Volatility Prediction
1963,74816606,3159.0,0.0,0,3,/rohandaniel/optiver-realized-volatility-prediction-rd,Optiver Realized Volatility Prediction
1964,67080900,1106.0,,0,15,/atamazian/optiver-tabnet-training,Optiver Realized Volatility Prediction
1965,69714020,1168.0,,29,120,/felipefonte99/optiver-lgb-with-optimized-params,Optiver Realized Volatility Prediction
1966,72599217,1723.0,,1,9,/nitinsss/lstm-starter-time-series-implementation,Optiver Realized Volatility Prediction
1967,67034507,1103.0,,9,55,/gogo827jz/inference-demo-notebook,Optiver Realized Volatility Prediction
1968,73324783,1678.0,,2,13,/mrutyunjaybiswal/optiver-realized-eda-xgb-baseline-train,Optiver Realized Volatility Prediction
1969,73479305,719.0,,0,1,/timetoshow/0-19741features,Optiver Realized Volatility Prediction
1970,75751826,3666.0,,2,19,/akshayr009/optiver-realized-volatility-prediction,Optiver Realized Volatility Prediction
1971,78960594,3019.0,,0,8,/lukaslegerer/linear-model-with-simple-features,Optiver Realized Volatility Prediction
1972,74388396,312.0,,4,15,/davidgauthier/linearmodel-var,Optiver Realized Volatility Prediction
1973,70419420,1436.0,,0,11,/ramikhreas/accelerating-trading-on-gpu-via-rapids-agg-fun,Optiver Realized Volatility Prediction
1974,91752499,2836.0,,0,0,/dmtrrr/optiver-combined-lstm-and-cnn-approach-0-2436,Optiver Realized Volatility Prediction
1975,72455365,1555.0,,0,11,/mayangrui/optiver-realized-volatility-prediction,Optiver Realized Volatility Prediction
1976,75037108,1537.0,,1,13,/tiger1026/lgbm-baseline-with-more-feature-engineering,Optiver Realized Volatility Prediction
1977,88418828,2641.0,,0,21,/johnakwei/realized-volatility-ln-rf-knn-garch-in-r,Optiver Realized Volatility Prediction
1978,73611606,1198.0,,0,0,/vv0x0x/optiver-pca-2lstm,Optiver Realized Volatility Prediction
1979,72932933,1185.0,,0,6,/ptrikp/single-stock-book-order-time-series,Optiver Realized Volatility Prediction
1980,70520179,2678.0,,0,2,/narendra/optiver-order-book-eda,Optiver Realized Volatility Prediction
1981,73420808,1528.0,,0,11,/skloveyyp/optiver-lgb-with-optimized-params,Optiver Realized Volatility Prediction
1982,72069443,837.0,,1,11,/syerwin/optiver-realized-ensemble-tabnet-and-lgbm,Optiver Realized Volatility Prediction
1983,75425919,177.0,,0,0,/rasevanth/data-prep,Optiver Realized Volatility Prediction
1984,75465289,3605.0,0.0,1,1,/htetaung04/optiver-submission,Optiver Realized Volatility Prediction
1985,74791349,1105.0,,2,24,/res1235/preprocessing-rapids-finish-in-3-mins,Optiver Realized Volatility Prediction
1986,71534485,2759.0,,7,34,/kittlein/volatility-1d-cnn-in-r-keras,Optiver Realized Volatility Prediction
1987,73909753,115.0,,5,31,/endremoen/feature-engineering-optimal-clustering-analysis,Optiver Realized Volatility Prediction
1988,67095353,161.0,,0,42,/yus002/realized-volatility-prediction-lgbm-train,Optiver Realized Volatility Prediction
1989,75741653,2952.0,,0,3,/hongyishao/rf-version2,Optiver Realized Volatility Prediction
1990,68472339,390.0,,0,13,/gopalmahadevan/optiver-realized-volatility-prediction-safarii,Optiver Realized Volatility Prediction
1991,72229596,1330.0,,10,41,/ammarnassanalhajali/optiver-volatility-prediction-eda,Optiver Realized Volatility Prediction
1992,67295622,2242.0,,7,14,/jaredsavage/optiver-analysis-with-r,Optiver Realized Volatility Prediction
1993,67885464,514.0,,1,6,/junichiromorita/introduction-to-financial-concepts-and-data,Optiver Realized Volatility Prediction
1994,85488825,193.0,,4,23,/bryanb/turn-your-time-series-into-images,Optiver Realized Volatility Prediction
1995,72489106,1194.0,,0,1,/fushigen/training-cnn,Optiver Realized Volatility Prediction
1996,72785932,1336.0,,18,47,/elcaiseri/pytorch-optiver-realized-volatility-baseline,Optiver Realized Volatility Prediction
1997,72563171,1229.0,,16,62,/junjitakeshima/optiver-beginner-s-gradual-improvement-eng,Optiver Realized Volatility Prediction
1998,67210854,45.0,,6,50,/slawekbiel/naive-but-fast-submission,Optiver Realized Volatility Prediction
1999,75624135,1847.0,0.0,0,0,/boddusairamakrishna/190030176-optiver-realized-volatility-prediction,Optiver Realized Volatility Prediction
2000,74066915,827.0,,1,16,/takemi/ohlc-charts-candlestick-charts,Optiver Realized Volatility Prediction
2001,66962307,669.0,,3,9,/jarupula/eda-optiver,Optiver Realized Volatility Prediction
2002,74352194,12.0,,2,3,/alexandredurand/garch-coefficients-optimization,Optiver Realized Volatility Prediction
2003,75693944,1853.0,,0,0,/knrindhuknrindhu/190030718-optiver-realized-volatility-prediction,Optiver Realized Volatility Prediction
2004,74612728,3571.0,,0,1,/yaniv256/notebookc06b833e0f,Optiver Realized Volatility Prediction
2005,75286847,382.0,,1,5,/miyashitaryuma/groupkfold-stock-id,Optiver Realized Volatility Prediction
2006,75762178,3680.0,0.0,0,0,/nagarjuna2997/optiver-realized-volatility-prediction,Optiver Realized Volatility Prediction
2007,68387750,4.0,,70,411,/tommy1028/lightgbm-starter-with-feature-engineering-idea,Optiver Realized Volatility Prediction
2008,75799661,3659.0,,0,0,/nicstephens/validation-notebook,Optiver Realized Volatility Prediction
2009,67378465,188.0,,21,233,/chumajin/optiver-realized-eda-for-starter-version,Optiver Realized Volatility Prediction
2010,75769188,3334.0,0.0,0,0,/sredstone/onserver-test,Optiver Realized Volatility Prediction
2011,70703410,874.0,,0,7,/rajat95gupta/optiver-lgbm-two-seeds-inference,Optiver Realized Volatility Prediction
2012,75694598,1858.0,,1,0,/hemanth9kumar9reddy/optiver-dataset-eda,Optiver Realized Volatility Prediction
2013,73122109,2717.0,,0,2,/yaoching/introduction-to-financial-concepts-and-data,Optiver Realized Volatility Prediction
2014,75894417,154.0,,11,96,/stassl/recovering-time-id-order,Optiver Realized Volatility Prediction
2015,73995880,1591.0,,2,5,/pea98258/tick-size,Optiver Realized Volatility Prediction
2016,75611181,3681.0,,0,0,/nivasbodapati/introduction-to-financial-concepts-and-data,Optiver Realized Volatility Prediction
2017,75816066,1860.0,,0,0,/srinivastikkana/190031630-competition,Optiver Realized Volatility Prediction
2018,74489657,72.0,,5,39,/jogepari/feel-the-data-interactive-plotly-charts,Optiver Realized Volatility Prediction
2019,71207640,2644.0,,0,8,/alexyuehuang/lgb-starter,Optiver Realized Volatility Prediction
2020,70400011,1.0,0.6566796327284447,19,58,/nguyenbadung/siim-covid19-2021,SIIM-FISABIO-RSNA COVID-19 Detection
2021,65033595,4.0,,7,22,/awsaf49/siim-covid-19-yolov5-image-level-train,SIIM-FISABIO-RSNA COVID-19 Detection
2022,67293647,5.0,,0,1,/benihime91/siim-covid-19-stratified-kfolds-study-level,SIIM-FISABIO-RSNA COVID-19 Detection
2023,64159005,2.0,,0,0,/steamedsheep/siim-covid-19-convert-to-jpg-256px,SIIM-FISABIO-RSNA COVID-19 Detection
2024,66563035,33.0,,1,2,/namgalielei/siim-eda-data,SIIM-FISABIO-RSNA COVID-19 Detection
2025,65600218,17.0,,2,7,/jaideepvalani/basic-exploration-eda-duplicate-nonduplicate,SIIM-FISABIO-RSNA COVID-19 Detection
2026,68294442,8.0,,0,0,/jihunlorenzopark/multiprocess-siim-covid-19-convert-to-jpg-256px,SIIM-FISABIO-RSNA COVID-19 Detection
2027,66450933,42.0,,0,1,/bcwang/siim-covid-19-convert-to-jpg-256px,SIIM-FISABIO-RSNA COVID-19 Detection
2028,66293829,21.0,0.1786625876716878,5,14,/shangweichen/infer-covid-19-detection-using-yolov5,SIIM-FISABIO-RSNA COVID-19 Detection
2029,65031906,99.0,,0,4,/kwk100/siim-covid-19-comprehensive-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2030,67857438,32.0,,0,2,/drzhuzhe/siiim-covid-stratified-k-fold-and-create-mask,SIIM-FISABIO-RSNA COVID-19 Detection
2031,69062722,63.0,,0,0,/kunihikofurugori/siim-step1-get-imginfo,SIIM-FISABIO-RSNA COVID-19 Detection
2032,66240904,58.0,,0,2,/tomdarmon/siim-train-xception,SIIM-FISABIO-RSNA COVID-19 Detection
2033,68230241,55.0,,0,0,/darkravager/efficientnetv2-m-siim-fold-3,SIIM-FISABIO-RSNA COVID-19 Detection
2034,68062497,78.0,,0,0,/xuxiaoxi/siim-covid19-efnb7-train-2class-image,SIIM-FISABIO-RSNA COVID-19 Detection
2035,68088640,59.0,,13,20,/eakdag/external-data-included-dataset-study-only,SIIM-FISABIO-RSNA COVID-19 Detection
2036,63242903,116.0,,8,45,/piantic/siim-fisabio-rsna-covid-19-detection-basic-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2037,68928894,80.0,,4,18,/ks2019/siim-yolo-lung-detector,SIIM-FISABIO-RSNA COVID-19 Detection
2038,69445701,48.0,,0,0,/omararias86/covid19-det,SIIM-FISABIO-RSNA COVID-19 Detection
2039,63305929,115.0,,0,10,/h053473666/512-img-png-600-study-png,SIIM-FISABIO-RSNA COVID-19 Detection
2040,67384698,90.0,0.1754597818355916,5,9,/coldfir3/siim-covid19-inference-image-level,SIIM-FISABIO-RSNA COVID-19 Detection
2041,63251835,38.0,,0,5,/keremt/siim-covid-19-eda-part-1,SIIM-FISABIO-RSNA COVID-19 Detection
2042,66729187,75.0,,1,5,/tyaiga/make-mask-png,SIIM-FISABIO-RSNA COVID-19 Detection
2043,68974499,103.0,,16,52,/sreevishnudamodaran/siim-covid-19-resize-process-coco-dataset,SIIM-FISABIO-RSNA COVID-19 Detection
2044,64969716,120.0,,2,2,/sachinrastogi/siim-processed-resized-512-ar-tojpg,SIIM-FISABIO-RSNA COVID-19 Detection
2045,67932524,104.0,,0,0,/amar2102/efnet4-train,SIIM-FISABIO-RSNA COVID-19 Detection
2046,71052418,79.0,,1,8,/gdoong/self-efficientnetv2-image-2class,SIIM-FISABIO-RSNA COVID-19 Detection
2047,65163920,129.0,,0,4,/parzukrofila/siim-covid-19-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2048,67238723,140.0,,0,0,/kalabanga/siim-covid-19-convert-to-jpg-256px,SIIM-FISABIO-RSNA COVID-19 Detection
2049,68404996,1280.0,,0,0,/samrendraroy/fork-of-fork-of-psudo-40,SIIM-FISABIO-RSNA COVID-19 Detection
2050,69125718,138.0,,0,3,/dlidli/covid19-classification,SIIM-FISABIO-RSNA COVID-19 Detection
2051,69556900,146.0,,0,0,/ep18041/siim-covid19-efnb7-train-fold0-5-2class,SIIM-FISABIO-RSNA COVID-19 Detection
2052,127504323,487.0,,0,15,/jasonhuangcn/tf-with-efficientnet-train,SIIM-FISABIO-RSNA COVID-19 Detection
2053,66219725,165.0,,0,10,/givkashi/transferlearning-with-densenet169,SIIM-FISABIO-RSNA COVID-19 Detection
2054,65424296,162.0,,0,2,/duythanhng/siim-covid-19-convert-to-jpg-original,SIIM-FISABIO-RSNA COVID-19 Detection
2055,67003654,373.0,,0,2,/jhleeeee/siim-covid-19-convert-to-jpg-512px,SIIM-FISABIO-RSNA COVID-19 Detection
2056,63973264,363.0,,0,2,/ludovicchangeon/siim-covid19-exploration,SIIM-FISABIO-RSNA COVID-19 Detection
2057,69612350,305.0,,0,0,/aithammadiabdellatif/resnet152models,SIIM-FISABIO-RSNA COVID-19 Detection
2058,66373662,217.0,,2,20,/ajaypawar123/visualize-dicom-images,SIIM-FISABIO-RSNA COVID-19 Detection
2059,68085581,220.0,,4,23,/ammarnassanalhajali/siim-fisabio-rsna-covid-19-detection-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2060,65742240,234.0,0.4405754982527339,0,6,/kaplo79/covid-19-2-para,SIIM-FISABIO-RSNA COVID-19 Detection
2061,68438893,237.0,,0,1,/xinruizhan/store-data,SIIM-FISABIO-RSNA COVID-19 Detection
2062,68311297,303.0,,0,0,/deephackernn/siim-covid-19-yolo-txt,SIIM-FISABIO-RSNA COVID-19 Detection
2063,63573973,268.0,0.2309248399316079,0,1,/laxmikantnishad/siim-fisabio-2,SIIM-FISABIO-RSNA COVID-19 Detection
2064,66437695,281.0,,6,8,/tensorchoko/siim-pytorch-1-ssd,SIIM-FISABIO-RSNA COVID-19 Detection
2065,65252108,282.0,0.4405754982527339,1,5,/vidhenchauhan/covid-19-2-para,SIIM-FISABIO-RSNA COVID-19 Detection
2066,68386107,380.0,,0,1,/rajesh1226/visual-inspection-of-data-from-category-of-study,SIIM-FISABIO-RSNA COVID-19 Detection
2067,66369930,398.0,,0,4,/davidbroberts/measuring-bounding-boxes-on-cxr,SIIM-FISABIO-RSNA COVID-19 Detection
2068,63229640,343.0,,0,10,/mathurinache/siim-covid-19-convert-to-jpg-1024px,SIIM-FISABIO-RSNA COVID-19 Detection
2069,63799040,438.0,,0,6,/yhirakawa/train-covid-19-detection-using-yolov5,SIIM-FISABIO-RSNA COVID-19 Detection
2070,70571794,480.0,,0,0,/fisheryjn/image-detection-model-repeat,SIIM-FISABIO-RSNA COVID-19 Detection
2071,63697326,325.0,,0,7,/snnclsr/eda-hitchiker-s-guide-to-covid-19-detection,SIIM-FISABIO-RSNA COVID-19 Detection
2072,64482120,340.0,0.4307134071751505,2,9,/dashu1999/covid-19,SIIM-FISABIO-RSNA COVID-19 Detection
2073,66409802,349.0,,0,0,/haiyunhu/siim-covid19-dicom-to-png,SIIM-FISABIO-RSNA COVID-19 Detection
2074,67417300,500.0,,0,1,/rutunjay/rutunmaal-train,SIIM-FISABIO-RSNA COVID-19 Detection
2075,67635930,504.0,,0,7,/mikeb127/efficientdet-pytorch-training-starter,SIIM-FISABIO-RSNA COVID-19 Detection
2076,63349696,605.0,,4,14,/shanmukh05/siim-covid-19-detection-detectron2-training,SIIM-FISABIO-RSNA COVID-19 Detection
2077,69579411,607.0,,0,1,/alexeyfil/data-prepare,SIIM-FISABIO-RSNA COVID-19 Detection
2078,68894187,611.0,,0,1,/leakoil/siim-fasterrcnn,SIIM-FISABIO-RSNA COVID-19 Detection
2079,66161780,617.0,0.4155253744203371,2,15,/salmaneunus/siim-covid-19-detection-submisssion-2,SIIM-FISABIO-RSNA COVID-19 Detection
2080,64430536,741.0,,0,0,/hghghghgh1234/train-book,SIIM-FISABIO-RSNA COVID-19 Detection
2081,72009218,632.0,,0,2,/nishabalaji3/heatmaps1,SIIM-FISABIO-RSNA COVID-19 Detection
2082,63294033,770.0,,0,4,/agentili/read-dicom-metadate,SIIM-FISABIO-RSNA COVID-19 Detection
2083,64092686,702.0,,1,2,/thrineshduvvuru/siim-covid19-simple-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2084,63718601,743.0,,0,9,/sawradipsaha/siim-covid-19-ultimate-explained-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2085,69044121,752.0,,0,0,/santosh1974/siim-decease-type-classification-1,SIIM-FISABIO-RSNA COVID-19 Detection
2086,65157425,602.0,,0,5,/tt195361/siim-covid-19-eda-for-train-csv-files,SIIM-FISABIO-RSNA COVID-19 Detection
2087,70196580,811.0,,0,4,/malleshamanumula/train-yolov5-siim-covid-class-opacity-only,SIIM-FISABIO-RSNA COVID-19 Detection
2088,68808051,813.0,,0,0,/benedictshs/eighth,SIIM-FISABIO-RSNA COVID-19 Detection
2089,67641438,802.0,,0,0,/benedicths/second-image-processing,SIIM-FISABIO-RSNA COVID-19 Detection
2090,68606319,826.0,0.3917623856942092,0,0,/akshays12/objectinference-yolov5s-060721,SIIM-FISABIO-RSNA COVID-19 Detection
2091,66871638,843.0,,0,1,/ivgona/submission-testing,SIIM-FISABIO-RSNA COVID-19 Detection
2092,65025330,864.0,0.1776201344643821,0,0,/xiaoyj/sample-submission,SIIM-FISABIO-RSNA COVID-19 Detection
2093,67417789,881.0,,22,78,/avirdee/siim-covid-19-initial-pipeline-fastai,SIIM-FISABIO-RSNA COVID-19 Detection
2094,66463564,879.0,,2,2,/kiranpradeep1811/creating-tfrecords-for-siim-covid-19,SIIM-FISABIO-RSNA COVID-19 Detection
2095,69565560,882.0,,1,5,/amokranemancer/siim-fisabio-rsna-covid-19-detection-data,SIIM-FISABIO-RSNA COVID-19 Detection
2096,64681247,900.0,,0,0,/itsoution/siim-covid-19-512x512-tfrec-data-1,SIIM-FISABIO-RSNA COVID-19 Detection
2097,68197171,915.0,,0,2,/rpsantosakaggle/dicom-files-using-python-on-r-and-plot-ly-render,SIIM-FISABIO-RSNA COVID-19 Detection
2098,64977688,977.0,0.4405252065123424,1,5,/ferhat00/covid-19-2-para,SIIM-FISABIO-RSNA COVID-19 Detection
2099,72492440,992.0,,0,2,/hichemallou/siim-covid-19-data-preparation,SIIM-FISABIO-RSNA COVID-19 Detection
2100,63346168,999.0,,2,5,/saketkattuboina/siim-covid-19-detection-how-to-get-started,SIIM-FISABIO-RSNA COVID-19 Detection
2101,64640046,923.0,,0,0,/canonical/edit-canonical-siim-covid19-efnb7-train-study,SIIM-FISABIO-RSNA COVID-19 Detection
2102,78058115,931.0,,0,0,/abhisheksingh000261/major-project-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2103,64704119,953.0,,0,0,/ghaiyur/rsna-covid-vmad,SIIM-FISABIO-RSNA COVID-19 Detection
2104,67399741,959.0,,0,2,/rbhambri/covid-detection-studies-eda-viz,SIIM-FISABIO-RSNA COVID-19 Detection
2105,65444858,1023.0,,0,4,/devanshchowdhury/eda-understand-data,SIIM-FISABIO-RSNA COVID-19 Detection
2106,66438217,1033.0,,0,0,/polarbearafterlunch/data-exploration,SIIM-FISABIO-RSNA COVID-19 Detection
2107,65824809,1077.0,,2,3,/rerere/chest-x-ray-covid-19-detection-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2108,63384225,1087.0,,21,70,/ayuraj/visualize-bounding-boxes-interactively,SIIM-FISABIO-RSNA COVID-19 Detection
2109,66763034,1106.0,,0,0,/xanjay/siim-covid-19-detection-extract-dicom-images,SIIM-FISABIO-RSNA COVID-19 Detection
2110,70816065,1119.0,,1,3,/ajinkyadeshpande39/yolo-notebook,SIIM-FISABIO-RSNA COVID-19 Detection
2111,68313106,1118.0,,0,0,/ajinkyavnit/efficientnetb7-dataset,SIIM-FISABIO-RSNA COVID-19 Detection
2112,66138891,1127.0,,0,0,/jayanth0572/covidnew,SIIM-FISABIO-RSNA COVID-19 Detection
2113,65806712,1121.0,,0,0,/glebberjoskin/dicom-initial-preprocessing,SIIM-FISABIO-RSNA COVID-19 Detection
2114,64849066,1128.0,0.237533606815487,0,3,/jaidmin/inference-notebook,SIIM-FISABIO-RSNA COVID-19 Detection
2115,153071729,1143.0,,20,115,/muhammadimran112233/siim-a-data-science-approach-starter,SIIM-FISABIO-RSNA COVID-19 Detection
2116,70825640,1154.0,0.206761006861045,0,0,/collinzrj/siim-collin,SIIM-FISABIO-RSNA COVID-19 Detection
2117,67513953,1175.0,,0,0,/rajeshp8783/convert-x-ray-image-to-jpg-format,SIIM-FISABIO-RSNA COVID-19 Detection
2118,65775949,1169.0,,0,0,/chohyungkwon/train-covid-19-detection-using-yolov5-777,SIIM-FISABIO-RSNA COVID-19 Detection
2119,70637820,1165.0,,0,1,/liuyiming321/inference-of-yolov5,SIIM-FISABIO-RSNA COVID-19 Detection
2120,63304771,1179.0,,0,3,/msafi04/rsna-covid19-detection,SIIM-FISABIO-RSNA COVID-19 Detection
2121,67763485,1193.0,,0,0,/nathankang/covid-competition-eda,SIIM-FISABIO-RSNA COVID-19 Detection
2122,66079215,1194.0,,4,0,/dragoonaethis/train-covid-19-detection-using-yolov5,SIIM-FISABIO-RSNA COVID-19 Detection
2123,63679368,1198.0,,3,40,/drcapa/siim-fisabio-rsna-covid-19-detection-starter,SIIM-FISABIO-RSNA COVID-19 Detection
2124,64354009,1209.0,0.1040438356644497,1,5,/yasinnaal/covid-19-detection-on-chest-radiographs,SIIM-FISABIO-RSNA COVID-19 Detection
2125,65630351,1223.0,0.1040438356644497,1,2,/byungjunyoon/happyhappy-covid19-submission,SIIM-FISABIO-RSNA COVID-19 Detection
2126,67582306,1236.0,,0,1,/nabilbouamara/readdicom,SIIM-FISABIO-RSNA COVID-19 Detection
2127,67103516,1239.0,,0,0,/fabienbenot/train-covid-19-detection-using-yolov5,SIIM-FISABIO-RSNA COVID-19 Detection
2128,70052372,1265.0,0.1040438356644497,0,0,/daksh2599/notebook86f91d8ce0,SIIM-FISABIO-RSNA COVID-19 Detection
2129,70332898,1266.0,,0,1,/kaitohonda/eda-modeling,SIIM-FISABIO-RSNA COVID-19 Detection
2130,70931941,1271.0,,1,13,/jirkaborovec/covid-detection-with-lightning-flash,SIIM-FISABIO-RSNA COVID-19 Detection
2131,66010352,1275.0,0.0639947113329224,0,1,/adrienloridan/part3-siim-covid19-submission,SIIM-FISABIO-RSNA COVID-19 Detection
2132,63353053,1215.0,,4,23,/farhanhaikhan/pretrained-unet-lung-segmentation-dataset,SIIM-FISABIO-RSNA COVID-19 Detection
2133,68087356,1297.0,0.0,0,2,/andernzhu/train-covid-19-detection,SIIM-FISABIO-RSNA COVID-19 Detection
2134,64916840,228.0,,0,2,/hyejinch/0605-rnn,ECO3119 Final Competition
2135,66711794,11.0,,5,31,/seefun/seefun-baseline-using-torchutils-lb0-987,Classify Leaves
2136,66871821,5.0,0.9870454545454546,5,43,/wangtf96/0-98909-5th-place-solution,Classify Leaves
2137,67177026,8.0,0.9838636363636364,4,36,/wjfearth/8th-classify-leaves-with-tpu-5hrs-0-989,Classify Leaves
2138,66818251,12.0,,0,3,/wanglinchen/12th-private-score-0-98704-reference-to-seefun,Classify Leaves
2139,66773455,9.0,,6,19,/yichaohan/9th-classify-leaves-11-models,Classify Leaves
2140,66849220,13.0,0.9836363636363636,12,50,/kxlyhit/13th-code-and-summary,Classify Leaves
2141,67208813,17.0,,0,3,/fuziwang/17th-reference-to-seefun,Classify Leaves
2142,66881154,18.0,0.9797727272727272,2,16,/hughie00/0-98568-classify-resnest,Classify Leaves
2143,67061852,14.0,,1,8,/baishaothu/14th-classify-leaves-reference-to-xichao-wang,Classify Leaves
2144,66757975,19.0,0.9831818181818182,3,4,/liyihang970828/19th-credit-to-seefun,Classify Leaves
2145,67339543,23.0,0.8202272727272727,67,496,/nekokiku/simple-resnet-baseline,Classify Leaves
2146,66211228,30.0,0.9790909090909092,2,8,/crazywinds/copy-classes,Classify Leaves
2147,64913935,104.0,,2,16,/tunguz/adversarial-tps-june-2021,Tabular Playground Series - Jun 2021
2148,65565273,94.0,1.753000486334408,0,8,/chinmayjain767/h2o-ai-lb-score-1-753,Tabular Playground Series - Jun 2021
2149,66525290,95.0,,33,59,/d4rklucif3r/tps-6-eda-luciferml,Tabular Playground Series - Jun 2021
2150,64909170,31.0,1.7452231154106668,12,39,/oxzplvifi/tabular-residual-network,Tabular Playground Series - Jun 2021
2151,65907360,44.0,1.7441506972060998,18,40,/mehrankazeminia/1-tps-jun-21-histgradient-catboost-nn,Tabular Playground Series - Jun 2021
2152,64547737,14.0,,0,6,/yus002/will-i-overfit,Tabular Playground Series - Jun 2021
2153,64861585,85.0,1.7492733791410675,46,92,/pranjalverma08/catboost-with-optuna-starter-tps-06,Tabular Playground Series - Jun 2021
2154,67150601,82.0,,5,16,/jonaspalucibarbosa/tps06-21-starter-eda-base-lgbm,Tabular Playground Series - Jun 2021
2155,64532360,83.0,,7,23,/gomes555/tps-jun2021-r-eda-tidymodels-lightgbm-baseline,Tabular Playground Series - Jun 2021
2156,64989579,86.0,1.7477563597453398,0,1,/omarvivas/kerasmodel-tps-jun2021,Tabular Playground Series - Jun 2021
2157,65859769,40.0,,0,1,/mohit12562/one-vs-rest-classifier,Tabular Playground Series - Jun 2021
2158,64676417,45.0,,3,12,/sohommajumder21/neural-networks-no-complex-codes-tps-june-2021,Tabular Playground Series - Jun 2021
2159,66594736,46.0,1.74703739596348,0,8,/jarupula/tps-june2021,Tabular Playground Series - Jun 2021
2160,64544352,48.0,2.3593500657206694,7,11,/sauravmaheshkar/tps-june-2021-simple-tabnet-starter,Tabular Playground Series - Jun 2021
2161,66264131,49.0,1.764497956222093,0,6,/amritpal333/eda-to-automl-all-explained,Tabular Playground Series - Jun 2021
2162,65718230,74.0,,14,26,/vineethakkinapalli/tps-06-21-5-auto-ml-2-optuna,Tabular Playground Series - Jun 2021
2163,66181533,81.0,,2,25,/junhyeok99/tps-xgboost-catboost-ensemble,Tabular Playground Series - Jun 2021
2164,66056355,26.0,,0,0,/sayancht92/tabular-playground-june-eda-baseline,Tabular Playground Series - Jun 2021
2165,64932874,120.0,1.74772472101454,20,37,/remekkinas/tps-06-eda-mljar-automl-detailed-optuna,Tabular Playground Series - Jun 2021
2166,65106399,143.0,1.7456628949263566,13,34,/pourchot/blending-neural-networks-weights-optimization,Tabular Playground Series - Jun 2021
2167,65696592,182.0,1.7492999835396947,24,22,/ranjeetshrivastav/tps-june-21-plotly-xgboost,Tabular Playground Series - Jun 2021
2168,66970414,146.0,2.018758521472775,11,18,/sagnik1511/tps-june-data-processing-model-performance,Tabular Playground Series - Jun 2021
2169,66970414,146.0,2.120271508209048,11,18,/sagnik1511/tps-june-data-processing-model-performance,Tabular Playground Series - Jun 2021
2170,66970414,146.0,1.9056218066622683,11,18,/sagnik1511/tps-june-data-processing-model-performance,Tabular Playground Series - Jun 2021
2171,66970414,146.0,2.2049954691467204,11,18,/sagnik1511/tps-june-data-processing-model-performance,Tabular Playground Series - Jun 2021
2172,66970414,146.0,1.851399447211112,11,18,/sagnik1511/tps-june-data-processing-model-performance,Tabular Playground Series - Jun 2021
2173,65791020,169.0,,6,18,/kaustubh93/baseline-xgboost-catboost-optuna-shap-tps-06,Tabular Playground Series - Jun 2021
2174,64966070,122.0,1.74513358675342,29,61,/alexryzhkov/lightautoml-baseline-tps-june-2021,Tabular Playground Series - Jun 2021
2175,65963433,221.0,1.7445184369863311,11,28,/fusioncenter/residual-network-for-tabular-data,Tabular Playground Series - Jun 2021
2176,64817640,153.0,,4,12,/paddykb/tps-06-exploring-features-lasso,Tabular Playground Series - Jun 2021
2177,65737612,149.0,1.7567504150651063,0,1,/smita09/beginnerfriendlytps,Tabular Playground Series - Jun 2021
2178,64543564,234.0,1.759539093182006,0,2,/vivanvatsa/easy-sub-tps-june-21-v-init-1-0,Tabular Playground Series - Jun 2021
2179,66187695,173.0,1.7448192582147208,25,36,/bhavikjain/tps-june-21-eda-models,Tabular Playground Series - Jun 2021
2180,65798998,174.0,,1,4,/deb009/tps-june-2021-eda-baseline-optuna-lightgbm-model,Tabular Playground Series - Jun 2021
2181,64748925,255.0,,0,5,/munumbutt/kerastuner-autonn-with-tpu,Tabular Playground Series - Jun 2021
2182,65878196,203.0,1.7451005055052904,7,17,/lukaszborecki/tps-06-tensorflow-work-in-progress-book,Tabular Playground Series - Jun 2021
2183,65564693,180.0,,6,10,/tharunreddy/tps-june-xgboost-tutorial,Tabular Playground Series - Jun 2021
2184,64537312,481.0,1.7507158632512356,0,3,/brookie210/tps-june2021-catboost-baselinemodel,Tabular Playground Series - Jun 2021
2185,66945423,152.0,1.744738639990423,0,2,/ludovicbr/tpsjun21-simple-neural-network-modifications,Tabular Playground Series - Jun 2021
2186,64775383,106.0,1.751017017265077,0,6,/dlaststark/tps-june-xgb-model-baseline,Tabular Playground Series - Jun 2021
2187,64538545,223.0,1.7506215309288322,0,5,/soerendip/xgboost-on-gpu,Tabular Playground Series - Jun 2021
2188,65480702,220.0,,0,2,/boss0ayush/easy-implementation-using-one-vs-rest-classifier,Tabular Playground Series - Jun 2021
2189,66487894,233.0,1.744861338908951,0,1,/satwikd/tps-june-attempt1,Tabular Playground Series - Jun 2021
2190,65591737,193.0,,6,14,/elemento/tabplayjune-randomforest,Tabular Playground Series - Jun 2021
2191,64660804,253.0,1.7656505460835026,2,6,/maksymshkliarevskyi/tps-jun-starting-point-eda-baseline-cv,Tabular Playground Series - Jun 2021
2192,66428654,202.0,,2,13,/tensorchoko/lightautoml-tps-june-2021,Tabular Playground Series - Jun 2021
2193,65247168,251.0,1.7518771444288397,4,8,/akioonodera/tps-jun2021-lgbmclassifier,Tabular Playground Series - Jun 2021
2194,65103701,248.0,1.746860701562426,3,9,/antonellomartiello/tps-06-mljar-quick-approach-with-eda,Tabular Playground Series - Jun 2021
2195,65350188,266.0,1.7463550193139712,4,7,/daikiiwasaki/japan-ramen,Tabular Playground Series - Jun 2021
2196,65350188,266.0,1.7462935735453615,4,7,/daikiiwasaki/japan-ramen,Tabular Playground Series - Jun 2021
2197,65350188,266.0,1.7463550193139712,4,7,/daikiiwasaki/japan-ramen,Tabular Playground Series - Jun 2021
2198,65287409,282.0,,0,3,/scchuy/tabular-play-202106-baseline,Tabular Playground Series - Jun 2021
2199,67428034,239.0,,0,0,/lilkaskitc/tps-june-2021,Tabular Playground Series - Jun 2021
2200,65393314,247.0,1.7506831269479606,0,16,/alex97andreev/tps-jun-autogluon-with-sklearnex,Tabular Playground Series - Jun 2021
2201,65393314,247.0,1.7506831269479606,0,16,/alex97andreev/tps-jun-autogluon-with-sklearnex,Tabular Playground Series - Jun 2021
2202,64675530,284.0,1.7544413424647267,0,3,/jenssvensmark/scikit-stacking-tabular-play-june,Tabular Playground Series - Jun 2021
2203,67431689,302.0,1.7485570790972769,0,1,/valmetisrinivas/tabular-playground-series-jun-2021-vs,Tabular Playground Series - Jun 2021
2204,67431689,302.0,2.101063729872507,0,1,/valmetisrinivas/tabular-playground-series-jun-2021-vs,Tabular Playground Series - Jun 2021
2205,67431689,302.0,2.861066824795328,0,1,/valmetisrinivas/tabular-playground-series-jun-2021-vs,Tabular Playground Series - Jun 2021
2206,67431689,302.0,2.987850886955992,0,1,/valmetisrinivas/tabular-playground-series-jun-2021-vs,Tabular Playground Series - Jun 2021
2207,67431689,302.0,1.7485570790972769,0,1,/valmetisrinivas/tabular-playground-series-jun-2021-vs,Tabular Playground Series - Jun 2021
2208,67431689,302.0,2.101063729872507,0,1,/valmetisrinivas/tabular-playground-series-jun-2021-vs,Tabular Playground Series - Jun 2021
2209,66713144,286.0,1.7464544657323635,2,5,/bernhardklinger/june-tps-fastai-v2,Tabular Playground Series - Jun 2021
2210,65931905,298.0,,6,22,/melanie7744/tps6-eda-comparison-to-tps5,Tabular Playground Series - Jun 2021
2211,67089554,287.0,1.7464797762515492,0,2,/fanbyprinciple/fastai-june-tps-2021,Tabular Playground Series - Jun 2021
2212,64619274,328.0,,1,3,/jeongyoonlee/tps-6-adversarial-validation,Tabular Playground Series - Jun 2021
2213,66255938,318.0,,2,6,/kumarsrikant/tps-keras,Tabular Playground Series - Jun 2021
2214,67063896,295.0,1.7494595336445102,4,7,/maximkazantsev/tps-06-21-catboost-optuna-eda-anomalies-detection,Tabular Playground Series - Jun 2021
2215,64707400,291.0,,0,2,/bruceharold/eda-with-comparisons-to-may,Tabular Playground Series - Jun 2021
2216,65143284,322.0,1.824265099605196,0,4,/noussaons/beginners-simple-logistic-regression-pipelines,Tabular Playground Series - Jun 2021
2217,66462112,311.0,,64,140,/usharengaraju/tps-june-weights-and-biases,Tabular Playground Series - Jun 2021
2218,65271709,342.0,2.640161208631542,0,2,/tachunliu/kaggle-tabular-june-2021-test-file,Tabular Playground Series - Jun 2021
2219,65692830,355.0,1.7660132932179458,0,13,/hongpeiyi/a-simple-baseline-method-with-random-forest,Tabular Playground Series - Jun 2021
2220,65238520,347.0,1.7475121830724092,10,22,/optimo/tabnetbaseline,Tabular Playground Series - Jun 2021
2221,64694669,329.0,1.7475738250773154,2,6,/faelk8/tps-jun-2021-automl,Tabular Playground Series - Jun 2021
2222,67104506,372.0,,1,3,/kuntalbhowmick/tps6-impact-of-quantile-transformerwithtabnet,Tabular Playground Series - Jun 2021
2223,64644393,340.0,,0,3,/niloyswe/visualization-and-model,Tabular Playground Series - Jun 2021
2224,66000238,349.0,1.750664335573112,6,5,/shashwatwork/breaking-the-leaderboard-with-mljar-tps-june,Tabular Playground Series - Jun 2021
2225,66078336,383.0,1.7507075900242632,11,32,/desalegngeb/06-tps-eda-and-models-lightautoml,Tabular Playground Series - Jun 2021
2226,66117703,412.0,1.7506758607508752,8,16,/davidjlochner/jun21-tps-xgboost-gridsearch,Tabular Playground Series - Jun 2021
2227,65197862,397.0,1.749039281756305,2,9,/hayahiko/tps-6-easy-way-lgbm-optuna-step-by-step,Tabular Playground Series - Jun 2021
2228,65022703,414.0,,0,5,/ryanbarretto/feature-selection-and-time-usage-with-lightgbm,Tabular Playground Series - Jun 2021
2229,64719223,431.0,,0,0,/natthasit/tps-jun-lgbm,Tabular Playground Series - Jun 2021
2230,64733794,380.0,1.7548603779375491,8,18,/tomwarrens/eda-lgbm-optuna-tps-june,Tabular Playground Series - Jun 2021
2231,66819727,430.0,,0,1,/tarzon/tabular-playground-series-jun21,Tabular Playground Series - Jun 2021
2232,66530192,459.0,1.7492999835396947,14,16,/sureshmecad/tps-june-2021-lightautoml,Tabular Playground Series - Jun 2021
2233,66769766,446.0,,0,0,/okyanusoz/tps-jun-2021-xgboost,Tabular Playground Series - Jun 2021
2234,64660385,486.0,,2,9,/shreyanshkabra/tps-june-21-catboost-lgbm,Tabular Playground Series - Jun 2021
2235,65781951,453.0,2.0632796209407527,0,0,/animeshrockn/neural-network-implementation,Tabular Playground Series - Jun 2021
2236,67120500,447.0,1.7771982355935705,15,11,/tiwariayan/eda-features-catboost-beginner-s-guide,Tabular Playground Series - Jun 2021
2237,64700985,429.0,,0,7,/aerdem/tps-june-lgbm-optuna,Tabular Playground Series - Jun 2021
2238,64624201,467.0,1.7538119149175888,0,4,/jsmithperera/lgmb-optuna,Tabular Playground Series - Jun 2021
2239,66542844,490.0,1.7513813517949104,0,5,/michael127001/xgbclassifier-with-optuna-preprocessing,Tabular Playground Series - Jun 2021
2240,66144356,471.0,1.7500701836363317,1,2,/paramond/voting-ensemble-lightgbm-logisticregression,Tabular Playground Series - Jun 2021
2241,65477517,549.0,,0,4,/josephmittelstaedt/tps-june-2021-target-encoding-pca,Tabular Playground Series - Jun 2021
2242,66738521,509.0,,0,1,/hanseopark/classification-using-mutual-information,Tabular Playground Series - Jun 2021
2243,64928699,642.0,1.770786518331538,1,5,/jdunavin/june-2021-tps-eda-and-modeling,Tabular Playground Series - Jun 2021
2244,65484270,511.0,,3,8,/onielg/fastai-embeddings-to-catboost,Tabular Playground Series - Jun 2021
2245,64529295,475.0,1.776434542713368,4,7,/felipedutralisboa/tps-june-beginner-deaplearning,Tabular Playground Series - Jun 2021
2246,65651695,488.0,1.761843810743526,1,7,/docxian/tabular-playground-6-multiclass-prediction,Tabular Playground Series - Jun 2021
2247,67070737,635.0,,0,6,/bakar31/tps-jun-eda,Tabular Playground Series - Jun 2021
2248,64949549,544.0,,29,38,/amartyabhattacharya/tps-pca-eda-model-comparisons,Tabular Playground Series - Jun 2021
2249,66785217,541.0,1.75131651037878,5,8,/atharvchaudhari/tps-june,Tabular Playground Series - Jun 2021
2250,67109621,567.0,1.7513901441524724,1,17,/owerbat/tps-jun-fast-stacking-with-scikit-learn-intelex,Tabular Playground Series - Jun 2021
2251,66513820,536.0,1.7516050976863722,1,17,/masdevas/fast-ml-stack-with-scikit-learn-intelex,Tabular Playground Series - Jun 2021
2252,65046348,568.0,,7,7,/purvitsharma/tps-principal-component-analysis,Tabular Playground Series - Jun 2021
2253,65230146,585.0,,2,2,/advaitvagerwal/simple-random-forest,Tabular Playground Series - Jun 2021
2254,67100428,569.0,,2,7,/shritech1404/tabular-playground-series,Tabular Playground Series - Jun 2021
2255,66865667,608.0,,0,2,/anishjosh/simple-ensemble-nn-catboost-1-75,Tabular Playground Series - Jun 2021
2256,65204701,610.0,,0,3,/jotaro/good-starting-point-lightgbm-optuna-baseline,Tabular Playground Series - Jun 2021
2257,66071311,589.0,,0,0,/decatur/tabular-june-1st-try,Tabular Playground Series - Jun 2021
2258,65152042,593.0,,2,5,/stpeteishii/tabular-playground-june-2021-conv1d,Tabular Playground Series - Jun 2021
2259,65898657,629.0,1.754077982740593,1,2,/sylar68/tps-06-how-to-use-crossvalidation-for-beginners,Tabular Playground Series - Jun 2021
2260,64615626,643.0,1.7532363258344774,0,1,/trimparashut/boosting-ensemble-baseline,Tabular Playground Series - Jun 2021
2261,66864249,626.0,,0,3,/tariqchhussain/tabular-playground-june-2021-eda-xgboost-wip,Tabular Playground Series - Jun 2021
2262,67138927,636.0,,0,0,/greengamma/xgboost,Tabular Playground Series - Jun 2021
2263,65004140,654.0,1.830416418664604,0,3,/aniketsharma00411/tpsjune21-logreg,Tabular Playground Series - Jun 2021
2264,64611676,646.0,,0,1,/sankets15/tps-jun-lgbm1-with-cross-validation,Tabular Playground Series - Jun 2021
2265,66495141,658.0,,4,11,/rabeyaakter/tabular-playground-series-jun-2021,Tabular Playground Series - Jun 2021
2266,65451067,725.0,,2,5,/abhishekv5055/tps-jun-exploratory-data-analysis,Tabular Playground Series - Jun 2021
2267,66320546,676.0,,1,4,/vexxingbanana/simple-cnn-model,Tabular Playground Series - Jun 2021
2268,65765740,720.0,1.7562722372105737,0,1,/yznga98/machine-learning-algorithms,Tabular Playground Series - Jun 2021
2269,66240002,761.0,1.7588570859467307,3,25,/kppetrov/tps-jun-fast-logreg-with-scikit-learn-intelex,Tabular Playground Series - Jun 2021
2270,64724611,756.0,,0,0,/pierrejeanne/tps-jun-2021,Tabular Playground Series - Jun 2021
2271,64974571,753.0,1.7566676650605195,0,2,/hiroshi0530/first-sub-lgbm-optuna,Tabular Playground Series - Jun 2021
2272,65322156,713.0,,6,13,/williamojemann/basic-xgboost-implementation,Tabular Playground Series - Jun 2021
2273,66225727,736.0,1.7598719243565382,1,3,/hakanerdogan/tps-june-2021-very-simple-fast-code,Tabular Playground Series - Jun 2021
2274,66225727,736.0,1.7567443875719229,1,3,/hakanerdogan/tps-june-2021-very-simple-fast-code,Tabular Playground Series - Jun 2021
2275,64876264,782.0,,4,11,/siddharthpchauhan/tps-may-2021-eda-preprocessing-tensorflow-df,Tabular Playground Series - Jun 2021
2276,66084587,757.0,,0,1,/mohankrishnan02/tabular1,Tabular Playground Series - Jun 2021
2277,64717774,745.0,1.759539093182006,4,16,/hongjae6/baseline-for-beginners-using-lightgbm-d,Tabular Playground Series - Jun 2021
2278,67182724,868.0,,0,0,/ktamta/afsa-kaggle,Tabular Playground Series - Jun 2021
2279,64696601,798.0,,0,2,/tracyporter/jun-21-bayesianreg,Tabular Playground Series - Jun 2021
2280,65321739,837.0,,6,15,/bastian1206/tabular-playground-random-forest-baseline,Tabular Playground Series - Jun 2021
2281,65393345,824.0,,0,1,/luisbedia/tabular-playground-jun2021,Tabular Playground Series - Jun 2021
2282,67055732,846.0,1.7639833549274082,1,3,/yasinnaal/tabular-playground-series-jun-2021,Tabular Playground Series - Jun 2021
2283,67082017,828.0,,1,8,/prajittr/tps-simple-xgb-score-1-76414,Tabular Playground Series - Jun 2021
2284,64693901,863.0,,6,16,/altinsoyemrecan/tps-june-optuna-pytorch-starter,Tabular Playground Series - Jun 2021
2285,66414429,865.0,6.247764977383812,0,4,/sahib12/stacking-tps-june-2021,Tabular Playground Series - Jun 2021
2286,66746489,908.0,1.7704512662664864,0,1,/muhammadalaref/mha-tabular-playground-series-jun-2021,Tabular Playground Series - Jun 2021
2287,65944750,896.0,1.7708516980335869,2,8,/stautxie/tabular-jun-2021-baseline,Tabular Playground Series - Jun 2021
2288,67959555,907.0,,0,2,/suryaprakash71/tps-june2021-simple-feedforwad-n-w,Tabular Playground Series - Jun 2021
2289,64918688,883.0,,14,56,/jessemostipak/getting-started-with-tidymodels-and-xgboost,Tabular Playground Series - Jun 2021
2290,65055198,913.0,1.788965376789525,0,5,/krishnavaghosh/getting-started-with-keras-and-tensorflow,Tabular Playground Series - Jun 2021
2291,67517122,931.0,,0,1,/carlosluz/data-playground-with-random-forest-model,Tabular Playground Series - Jun 2021
2292,65591988,919.0,,0,0,/yvamshivardhan/random-search-in-neural-network,Tabular Playground Series - Jun 2021
2293,66301422,940.0,,22,30,/the0electronic0guy/data-visualisation-and-keras-net,Tabular Playground Series - Jun 2021
2294,65458816,966.0,1.782430125112941,0,2,/akashmathur2212/extensive-eda-multiple-models-tsa-jun-21,Tabular Playground Series - Jun 2021
2295,64545326,986.0,1.7938541355720123,1,2,/jackstapleton/tps-june-baseline,Tabular Playground Series - Jun 2021
2296,64642046,990.0,1.7945349466155929,2,8,/msafi04/tensorflow-decisionforests-demo-tps-june,Tabular Playground Series - Jun 2021
2297,67148766,995.0,,0,1,/nasil2/random-forest,Tabular Playground Series - Jun 2021
2298,66064439,1000.0,,8,9,/pranjalchatterjee/deep-learning-on-tabular-playground-jun-2021,Tabular Playground Series - Jun 2021
2299,66484704,1013.0,1.8234497305366728,1,2,/somesh25171/tabular-playground,Tabular Playground Series - Jun 2021
2300,66764481,1012.0,,1,7,/rsesha/june-tps-deep-learning-1-82-score,Tabular Playground Series - Jun 2021
2301,66766874,1038.0,1.8548913094160568,0,0,/scr0ll0/tabular-playground-series-june-2021,Tabular Playground Series - Jun 2021
2302,65387681,1046.0,1.858685527900576,0,1,/prakharprasad/tps-june-2021,Tabular Playground Series - Jun 2021
2303,64993017,1065.0,,0,3,/susree64/tabular-playground-june-2021,Tabular Playground Series - Jun 2021
2304,65601556,1066.0,,0,0,/himanshushekhardas/assignment-1,Tabular Playground Series - Jun 2021
2305,65187182,1067.0,1.9409733832051248,0,4,/prakashr7d/tabular-playground-june-2021,Tabular Playground Series - Jun 2021
2306,65140334,1071.0,,1,8,/donmarch14/tps-june-beginner-s-guide,Tabular Playground Series - Jun 2021
2307,66759783,1079.0,,0,10,/siddheshkadam/tps-eda-extratreesclassifier,Tabular Playground Series - Jun 2021
2308,66301546,1090.0,2.0234849374732446,0,1,/socathie/randomforestclassifier,Tabular Playground Series - Jun 2021
2309,64968214,1095.0,,0,2,/sardinetrawler/multinom-logistic-regression-pca-glmnet,Tabular Playground Series - Jun 2021
2310,65628240,1130.0,,0,1,/shantanusoni/multiclass-classifier-accuracies,Tabular Playground Series - Jun 2021
2311,65628605,434.0,,4,2,/iffranciscome/mlb-players-eda-short-version,MLB Player Digital Engagement Forecasting
2312,65452802,255.0,,2,34,/naotaka1128/creating-unnested-dataset,MLB Player Digital Engagement Forecasting
2313,65791133,314.0,0.0,4,9,/junichih/mlb-baseline-median-1-45,MLB Player Digital Engagement Forecasting
2314,66094002,294.0,0.0,25,159,/ryanholbrook/getting-started-with-mlb-player-digital-engagement,MLB Player Digital Engagement Forecasting
2315,66137813,340.0,0.0,0,4,/aladdinss/best-eda-model-prediction,MLB Player Digital Engagement Forecasting
2316,66194800,404.0,,3,11,/fumiyakomatsu/explanation-of-train-csv-each-variable-ver,MLB Player Digital Engagement Forecasting
2317,67107310,149.0,,0,1,/superkojiro/notebook833dd224ab,MLB Player Digital Engagement Forecasting
2318,66687496,394.0,,1,2,/rautaki0127/eda-top-engagement-players-bar-chart-race-movie,MLB Player Digital Engagement Forecasting
2319,69188600,301.0,,0,2,/shayansheikhakbari/2nd-asset,MLB Player Digital Engagement Forecasting
2320,67421226,178.0,,0,1,/pritommojumder/mlb-digital-forecasting,MLB Player Digital Engagement Forecasting
2321,67891168,410.0,,4,9,/garggirish/simple-ann-model-trial-version-mlb,MLB Player Digital Engagement Forecasting
2322,68331506,390.0,0.0,3,6,/krishnamore/simple-ann-mlb-player-digital-engagement,MLB Player Digital Engagement Forecasting
2323,68625410,389.0,0.0,0,2,/davidetedd/notebook87f79fcd5f,MLB Player Digital Engagement Forecasting
2324,65994737,45.0,,5,4,/xblade/mlb-player-digital-engagement-baseline,MLB Player Digital Engagement Forecasting
2325,67120372,370.0,,0,1,/developerjun/what-is-targets-mean,MLB Player Digital Engagement Forecasting
2326,66459299,367.0,,1,2,/echozuluecho/mlb-digital-engagement-train-data-to-sqlite,MLB Player Digital Engagement Forecasting
2327,65896391,83.0,,7,72,/columbia2131/mlb-lightgbm-starter-dataset-code-en-ja,MLB Player Digital Engagement Forecasting
2328,68763991,93.0,,0,7,/kaito510/mlbmarketscrape,MLB Player Digital Engagement Forecasting
2329,69594482,246.0,,0,1,/maron5/mlb-lightgbm-starting,MLB Player Digital Engagement Forecasting
2330,68848520,3.0,,10,50,/nyanpn/api-emulator-for-debugging-your-code-locally,MLB Player Digital Engagement Forecasting
2331,69331011,18.0,,4,23,/aerdem4/mlb-lofo-feature-importance,MLB Player Digital Engagement Forecasting
2332,69304373,401.0,0.0,0,0,/rachidrahal/notebookce5f7e9cef,MLB Player Digital Engagement Forecasting
2333,69073873,412.0,,2,4,/tomokikmogura/unpack-json-data,MLB Player Digital Engagement Forecasting
2334,68854822,382.0,,6,15,/ruriarmandhani/mlb-forecasting-ann,MLB Player Digital Engagement Forecasting
2335,69401239,86.0,,3,6,/something4kag/submitting-using-mlb-module-in-r,MLB Player Digital Engagement Forecasting
2336,66767835,57.0,,6,46,/ulrich07/baseline-model-player-mean-or-median,MLB Player Digital Engagement Forecasting
2337,67779775,36.0,,0,2,/tea0925ds/mlb-targetenc-season-train,MLB Player Digital Engagement Forecasting
2338,65537748,186.0,,1,36,/ks2019/mlb-baseline-with-truncated-validation,MLB Player Digital Engagement Forecasting
2339,76104428,2.0,,4,30,/analokamus/1d-cnn-densenet1d,G2Net Gravitational Wave Detection
2340,80297337,3.0,,41,126,/anjum48/continuous-wavelet-transform-cwt-in-pytorch,G2Net Gravitational Wave Detection
2341,68153842,9.0,,12,73,/kevinmcisaac/g2net-spectral-whitening,G2Net Gravitational Wave Detection
2342,74126225,8.0,,2,14,/titericz/simulated-gw,G2Net Gravitational Wave Detection
2343,74358508,13.0,,4,10,/callmeb/cwt-in-pytorch-that-actually-works-in-gpus,G2Net Gravitational Wave Detection
2344,67205392,12.0,,13,89,/yasufuminakama/g2net-spectrogram-generation-train,G2Net Gravitational Wave Detection
2345,76625063,32.0,,1,14,/jbomitchell/effb7-normalised-18-epochs,G2Net Gravitational Wave Detection
2346,73545905,38.0,,1,2,/jaideepvalani/g2net-tfrec-cqt-pytorch-inference-public,G2Net Gravitational Wave Detection
2347,72848341,30.0,0.8627420325253612,0,10,/snnclsr/g2net-pytorch-inference,G2Net Gravitational Wave Detection
2348,72775519,41.0,,1,6,/zarif98sjs/g-wave-seresnet50-inference,G2Net Gravitational Wave Detection
2349,74697304,60.0,0.8777031875290331,2,25,/leolu1998/my-blend-for-g2net,G2Net Gravitational Wave Detection
2350,76597240,55.0,,1,17,/meaninglesslives/self-supervised-method-for-gravitation-wave-det,G2Net Gravitational Wave Detection
2351,76192756,87.0,,0,1,/blankaf/g2net-train-eval-tpu,G2Net Gravitational Wave Detection
2352,75882461,91.0,,0,19,/cocoinit23/shake-estimation,G2Net Gravitational Wave Detection
2353,67172670,107.0,,0,7,/miklgr500/spector-power-tfrecords,G2Net Gravitational Wave Detection
2354,74460862,106.0,0.832488969232445,1,23,/scaomath/g2net-vision-transformer-starter,G2Net Gravitational Wave Detection
2355,73752909,138.0,,23,151,/allunia/signal-where-are-you,G2Net Gravitational Wave Detection
2356,71751433,129.0,,3,29,/hinamimi/visualization-gravitational-wave-with-librosa,G2Net Gravitational Wave Detection
2357,68687370,140.0,,1,6,/maxdner/signal-preprocessing-whitening-bandpass-filter,G2Net Gravitational Wave Detection
2358,72762310,189.0,0.8741745419558823,6,25,/kuroyuli/g2net-modified-smart-ensembling,G2Net Gravitational Wave Detection
2359,74697607,184.0,0.8759766539742359,5,33,/firefliesqn/g2net-tpu-newbie,G2Net Gravitational Wave Detection
2360,72210848,206.0,0.8747965119606117,91,136,/somayyehgholami/1-g2net-smart-ensembling,G2Net Gravitational Wave Detection
2361,76463079,271.0,,13,25,/mightyrains/gravitational-waves-but-as-anomalies,G2Net Gravitational Wave Detection
2362,67854880,344.0,0.8597131839431279,1,14,/yseeker/singlemodel-lb-0-859-efficientnetv2-rw-s-via-tez,G2Net Gravitational Wave Detection
2363,73621545,277.0,,0,9,/tensorchoko/g2net-gravitational-eda,G2Net Gravitational Wave Detection
2364,68479634,363.0,,6,15,/ammarnassanalhajali/g2net-eda-signal-transformations,G2Net Gravitational Wave Detection
2365,79755378,296.0,,1,10,/rhythmcam/pandas-basic-make-training-folds-csv,G2Net Gravitational Wave Detection
2366,71164757,297.0,0.8650712093156999,0,10,/vamsikrishnab/cqt-g2net-efficientnetb1-tpu-inference,G2Net Gravitational Wave Detection
2367,74585062,302.0,0.8754872692256142,6,26,/junhyeok99/g2net-efficientnetv2,G2Net Gravitational Wave Detection
2368,71023522,324.0,0.8552092276592439,3,26,/jcesquiveld/efficientnet-cqt-pytorch-lightning-starter,G2Net Gravitational Wave Detection
2369,67966636,359.0,,0,8,/muhakabartay/eda-g2net-gw-detection,G2Net Gravitational Wave Detection
2370,75665911,264.0,,0,2,/ssato1219/ensemble,G2Net Gravitational Wave Detection
2371,73833970,466.0,,0,1,/robertlangdonvinci/train-g2net-audio-wave-data,G2Net Gravitational Wave Detection
2372,73042986,491.0,0.8677615086916606,0,10,/dragonzhang/g2net-tf-effnetv2-cqt-tpu-inference,G2Net Gravitational Wave Detection
2373,72899020,537.0,,1,3,/wabinab/gnet-1,G2Net Gravitational Wave Detection
2374,67317926,559.0,0.8556945857375982,7,25,/kneroma/g2net-fast-and-almost-accurate-detector,G2Net Gravitational Wave Detection
2375,67748311,585.0,,2,5,/snkmr0221/g2net-visualize-fft-amplitude-phase-wavelet,G2Net Gravitational Wave Detection
2376,70379284,642.0,0.8395323971505415,0,1,/dankopenko/g2net-rnn-starter-from-spectrogram,G2Net Gravitational Wave Detection
2377,69232571,659.0,,0,1,/masatotaka/g2net-ligo-and-train-data-gw-detection,G2Net Gravitational Wave Detection
2378,67950798,695.0,,1,14,/abhishekprajapat/g2net-audio-spectrogram-transformer,G2Net Gravitational Wave Detection
2379,72478748,675.0,,2,3,/hzhaobang/g2net-pytorch-lightning-efficientnet,G2Net Gravitational Wave Detection
2380,72092328,780.0,,0,1,/mahmoudhelmy957/g2net-eda,G2Net Gravitational Wave Detection
2381,72215444,759.0,,0,2,/thimac/gravity-2-prepare-data,G2Net Gravitational Wave Detection
2382,72080311,772.0,,1,24,/artemzapara/g2net-clean-eda-cqt,G2Net Gravitational Wave Detection
2383,75442828,838.0,,0,0,/naoyakintoki/g2net-make-tfrecords-train1,G2Net Gravitational Wave Detection
2384,68204351,833.0,,0,3,/aramos/eda-g2net-gravitational-wave-detection-2021,G2Net Gravitational Wave Detection
2385,70852134,859.0,,0,5,/pranay1990/pranay-g2net-gw,G2Net Gravitational Wave Detection
2386,68887132,902.0,,9,36,/heyytanay/training-g2net-pytorch-trainer-kfolds-w-b,G2Net Gravitational Wave Detection
2387,71706459,882.0,,1,28,/lekynam2000/g2-net-effnet-minimal-version,G2Net Gravitational Wave Detection
2388,71283741,927.0,,5,8,/junlilu/train-bandpass-cwt-efficientnet,G2Net Gravitational Wave Detection
2389,68567548,977.0,0.8313730168048287,7,15,/rijuvaish/gravitational-wave-detection-ensemble-tf,G2Net Gravitational Wave Detection
2390,73005205,983.0,,3,26,/paulrohan2020/basic-eda-and-a-baseline-keras-model,G2Net Gravitational Wave Detection
2391,73417929,994.0,0.8552523790241913,4,12,/sourabhy/gravitational-wave-detection,G2Net Gravitational Wave Detection
2392,72278867,1007.0,0.854018210047621,0,7,/brandonbenton/gravitational-wave-detection,G2Net Gravitational Wave Detection
2393,67834113,1012.0,,1,5,/vincentdumetz/g2net-tf-dataset-starter,G2Net Gravitational Wave Detection
2394,75245661,1026.0,,0,0,/christophermcbride/g2net-gravwave-with-fastai,G2Net Gravitational Wave Detection
2395,68462811,1030.0,0.8422936367526679,0,2,/kad99kev/g2net,G2Net Gravitational Wave Detection
2396,75781543,1033.0,,0,6,/lakshit28/g2net-gravitational-wave-detection,G2Net Gravitational Wave Detection
2397,74895195,1035.0,0.8400327027406482,2,22,/esratmaria/gravitational-wave-detection-simple-cnn-model,G2Net Gravitational Wave Detection
2398,76958308,1051.0,,0,7,/nesterenkomarina/load-files-to-your-pc-g2net,G2Net Gravitational Wave Detection
2399,69025891,1058.0,0.7924348625785584,0,0,/vungocbinh/g2net-tensorflow-tfrec,G2Net Gravitational Wave Detection
2400,67404848,1073.0,0.8019587178213193,4,43,/xhlulu/g2net-rnn-starter-from-spectrogram,G2Net Gravitational Wave Detection
2401,71069720,1078.0,,0,11,/jamesmcguigan/gwpy-tutorial,G2Net Gravitational Wave Detection
2402,76034803,1103.0,,0,0,/energydatascientist/notebookb074aad9e6,G2Net Gravitational Wave Detection
2403,67189940,1106.0,0.502130443997357,5,5,/thedrcat/g2net-fastai-resnet34-starter,G2Net Gravitational Wave Detection
2404,75498672,1131.0,,0,3,/nesslc/ondas-grav,G2Net Gravitational Wave Detection
2405,68202710,1128.0,0.5023297290728939,2,15,/rawaaelghali/g2net-gravitational-starter-eda,G2Net Gravitational Wave Detection
2406,69481243,1139.0,,1,10,/drcapa/gt2net-starter,G2Net Gravitational Wave Detection
2407,67142794,1143.0,0.5,2,12,/tanyadayanand/gravitational-wave-detection-eda,G2Net Gravitational Wave Detection
2408,67156628,1148.0,0.5,0,0,/rikofadla/g2-starter-and-eda-riko-fadla,G2Net Gravitational Wave Detection
2409,72262662,1116.0,,0,2,/sapal6/g2gwd-base-model-fastai-resnet,G2Net Gravitational Wave Detection
2410,72190742,1217.0,,0,0,/jeanpaulyepes/entrega,G2Net Gravitational Wave Detection
2411,67515578,12.0,0.1946662759405992,64,118,/junhyeok99/automl-pycaret,Tabular Playground Series - Jul 2021
2412,67754178,27.0,0.2222893386688036,2,11,/alexryzhkov/tps-july-21-lightautoml-baseline,Tabular Playground Series - Jul 2021
2413,67162258,21.0,0.7369364026826651,7,12,/yus002/auto-arima-forecast-with-no-features,Tabular Playground Series - Jul 2021
2414,67612573,59.0,,0,7,/aayush26/tps-july-2021-auto-gluon,Tabular Playground Series - Jul 2021
2415,67265241,35.0,0.6294058159835811,1,3,/josepc/playground-july-sarima,Tabular Playground Series - Jul 2021
2416,68728924,56.0,0.2158172108014262,24,40,/mhslearner/starter-simple-models-xgb-lgb-cat,Tabular Playground Series - Jul 2021
2417,69235789,57.0,0.328729956928754,4,9,/tarunbisht11/tabular-playground-series-jul-2021,Tabular Playground Series - Jul 2021
2418,67489128,62.0,0.2135005215986762,9,24,/sauravjoshi23/tps-july2021-all-models,Tabular Playground Series - Jul 2021
2419,67517921,68.0,0.2392101014122176,4,7,/amritpal333/tps-autogluon-baseline,Tabular Playground Series - Jul 2021
2420,67394130,73.0,0.2174475918007259,7,24,/paddykb/tps-07-gam-baseline,Tabular Playground Series - Jul 2021
2421,69177664,30.0,0.2229831897552924,2,6,/rajat95gupta/autogluon-lightautoml,Tabular Playground Series - Jul 2021
2422,67451983,15.0,0.2445913808402793,0,1,/harshhzz/tps-july-competition-eda-model-xgb-cat-rf,Tabular Playground Series - Jul 2021
2423,69175060,112.0,,0,3,/skomuro/leaked-data-simple-regression,Tabular Playground Series - Jul 2021
2424,68485421,139.0,0.0880111743675119,17,24,/alekseyromanovich/leaked-data,Tabular Playground Series - Jul 2021
2425,68121337,103.0,,0,1,/dsantiago/tps-07-yet-another-lstm,Tabular Playground Series - Jul 2021
2426,68808190,111.0,,0,0,/brennolins/july-tps-air-quality,Tabular Playground Series - Jul 2021
2427,68503386,124.0,0.2855879195655716,2,3,/sureshmecad/tps-july21-h20-automl,Tabular Playground Series - Jul 2021
2428,68037229,135.0,,10,24,/anjalianupam/tps-july-eda,Tabular Playground Series - Jul 2021
2429,68169832,151.0,,20,23,/lukaszborecki/tensorflow-lstm-with-fold-5-benzene,Tabular Playground Series - Jul 2021
2430,83782510,137.0,,0,0,/yuqihanhan/tps-07-2021-catboost-analysis,Tabular Playground Series - Jul 2021
2431,68105308,247.0,0.2026447724652814,2,20,/alexeykolobyanin/tps-jul-rf-with-intel-extension-for-scikit-learn,Tabular Playground Series - Jul 2021
2432,68105308,247.0,0.2026447724652814,2,20,/alexeykolobyanin/tps-jul-rf-with-intel-extension-for-scikit-learn,Tabular Playground Series - Jul 2021
2433,68105308,247.0,0.2026447724652814,2,20,/alexeykolobyanin/tps-jul-rf-with-intel-extension-for-scikit-learn,Tabular Playground Series - Jul 2021
2434,68105308,247.0,0.2026447724652814,2,20,/alexeykolobyanin/tps-jul-rf-with-intel-extension-for-scikit-learn,Tabular Playground Series - Jul 2021
2435,68705384,141.0,0.1330905590286124,0,4,/adityab19/eda-average-weighted-ensemble,Tabular Playground Series - Jul 2021
2436,68860571,142.0,0.1644838858403973,0,4,/alvarofbudria/prophet-pseudo-labels-feature-engineering,Tabular Playground Series - Jul 2021
2437,67451894,525.0,,1,1,/nephesd/tps-july-fbprophet-baseline,Tabular Playground Series - Jul 2021
2438,67571264,364.0,0.1972004093617866,21,44,/mehrankazeminia/1-tps-jul-21-xgboost-leaveonegroupout,Tabular Playground Series - Jul 2021
2439,87538449,280.0,0.4417550250667627,40,68,/remekkinas/lstm-seq2seq-encoder-decoder,Tabular Playground Series - Jul 2021
2440,68008882,245.0,0.2334035249522668,11,14,/bakar31/tps-jul-eda-h2oautoml,Tabular Playground Series - Jul 2021
2441,69296356,239.0,0.1860901343456392,13,20,/keysersoze309/tps-jul-2021-single-catboost-model,Tabular Playground Series - Jul 2021
2442,68244178,242.0,,0,2,/maheshmj007/tabular-playground-series-jul-2021-first-submit,Tabular Playground Series - Jul 2021
2443,67488144,312.0,0.2828733748478007,0,2,/sahib12/stacking,Tabular Playground Series - Jul 2021
2444,67852588,535.0,,4,15,/gomes555/tps-jul2021-r-basic-cv-prophetcatboost,Tabular Playground Series - Jul 2021
2445,67701793,155.0,,11,27,/bruceharold/bad-sensor-values,Tabular Playground Series - Jul 2021
2446,67194409,296.0,,0,0,/sanskarjadhav/tabular-playground-july-2021,Tabular Playground Series - Jul 2021
2447,67176833,194.0,0.3363896605488867,0,2,/stpeteishii/tps0721-lightbgm-visualize-importance,Tabular Playground Series - Jul 2021
2448,67672392,188.0,0.2298698747835906,11,10,/andy6804tw/predicting-the-values-of-air-pollution-xgboost,Tabular Playground Series - Jul 2021
2449,68481683,1293.0,0.3329004663839314,9,61,/tunguz/tps-07-21-simple-linear-baseline,Tabular Playground Series - Jul 2021
2450,67616926,533.0,,0,0,/cashmesh/simple-ann-approach-0-275,Tabular Playground Series - Jul 2021
2451,69493531,160.0,0.1940438759417152,1,3,/nitinrajput47/pollution-prediction-seasonal-decompose,Tabular Playground Series - Jul 2021
2452,67628973,408.0,0.2674180405963404,4,9,/pourchot/simple-neural-network-tuned-for-regression,Tabular Playground Series - Jul 2021
2453,68047603,171.0,0.253042346106589,7,11,/bastian1206/tps-july-rf-with-timecv-feature-engineering,Tabular Playground Series - Jul 2021
2454,67400885,180.0,,8,8,/lokesharya99/tps-jul-21-data-exploration,Tabular Playground Series - Jul 2021
2455,68852707,208.0,,0,1,/jagunn/pycaret-tbs-july,Tabular Playground Series - Jul 2021
2456,68831280,248.0,,4,14,/onielg/simplecatboostwithclassifierchains,Tabular Playground Series - Jul 2021
2457,67486718,214.0,,3,7,/kaustubh93/baseline-eda-tps-07,Tabular Playground Series - Jul 2021
2458,67341180,223.0,,12,18,/nancydrew/basic-eda-and-xgboost-for-tps-july-2021,Tabular Playground Series - Jul 2021
2459,67460469,250.0,0.248475603406659,0,0,/markct/tps-202107,Tabular Playground Series - Jul 2021
2460,67432784,230.0,,0,7,/astashiro/tps-jul2021-01eda,Tabular Playground Series - Jul 2021
2461,68995737,290.0,0.2187903632104576,2,11,/bernhardklinger/tps-july-fast-ai,Tabular Playground Series - Jul 2021
2462,68706155,291.0,,1,4,/johnysinsdota/time-series-analytics-h2oautoml,Tabular Playground Series - Jul 2021
2463,68854990,205.0,,0,0,/sherrygow/tabular-july-pycaret,Tabular Playground Series - Jul 2021
2464,69470103,322.0,,0,3,/saruhangngr/leak-data-lstm-xgb-gb,Tabular Playground Series - Jul 2021
2465,69002475,991.0,0.2118818640318908,5,18,/sudharshanravi/playgroundseries-july2020,Tabular Playground Series - Jul 2021
2466,67465928,261.0,0.3052812867487491,0,0,/tun000/tps-july-2021-holiday-feature,Tabular Playground Series - Jul 2021
2467,67280786,288.0,,2,4,/taha07/tps-july-eda-with-baseline,Tabular Playground Series - Jul 2021
2468,69512045,915.0,0.2145383306061857,10,19,/jonaspalucibarbosa/tps07-21-eda-time-ft-xgboost-w-ft-eng,Tabular Playground Series - Jul 2021
2469,67740864,567.0,0.214625408836545,0,0,/saztorralba/airpollutionprediction-lightgbm-xgboost-fixes,Tabular Playground Series - Jul 2021
2470,70202274,330.0,,0,4,/garyyehyl/tbp-july-2021-catboost-divide-and-conquer,Tabular Playground Series - Jul 2021
2471,69327139,353.0,0.2392914662059597,0,2,/ivankontic/002-tps-jul-2021,Tabular Playground Series - Jul 2021
2472,67968844,379.0,,3,12,/roberterffmeyer/july-tps-random-forest-baselines,Tabular Playground Series - Jul 2021
2473,68670130,603.0,0.2175590694962249,0,0,/leeguanhua/david-s-eda-tabular-playground-series-july-2021,Tabular Playground Series - Jul 2021
2474,69122748,987.0,0.2186373583799706,6,34,/monogenea/tps-jul-2021-gradient-boosting,Tabular Playground Series - Jul 2021
2475,67575138,333.0,,0,4,/amiteshgangrade/gradient-boosting-algo,Tabular Playground Series - Jul 2021
2476,68978510,396.0,0.2221356599149308,10,11,/emrearuk/tabular-playground-series-xgbregressor-gridsearch,Tabular Playground Series - Jul 2021
2477,67357192,942.0,0.2559930711708589,5,8,/vernondsouza123/analysis-of-air-pollution,Tabular Playground Series - Jul 2021
2478,68305526,356.0,,0,1,/moritti373737/randomforestregressor,Tabular Playground Series - Jul 2021
2479,67699985,574.0,,0,1,/mohdali231993/tabularseriesjuly-eda-initialmodels,Tabular Playground Series - Jul 2021
2480,69504306,310.0,,0,2,/danielavadr/tabnet-tps-semi-supervised-deep-learning-solution,Tabular Playground Series - Jul 2021
2481,67315103,337.0,,0,2,/kirillshmilovich1995/pytorch-lightning-simple-mlp,Tabular Playground Series - Jul 2021
2482,69380754,1059.0,0.2324304594607505,10,13,/alankadiev/tps-2021-simplest-catboost-model,Tabular Playground Series - Jul 2021
2483,68690639,580.0,0.4086830515121867,0,2,/amarloni/fork-of-july-playground,Tabular Playground Series - Jul 2021
2484,69563885,382.0,,4,12,/reymaster/july-2021-tps-xgboost-feature-engineering,Tabular Playground Series - Jul 2021
2485,68258135,446.0,,14,20,/icrybaby/deep-analysis-prediction-model-for-air-pollutants,Tabular Playground Series - Jul 2021
2486,113504573,983.0,,4,3,/markbquant/lgbm-regressorchain-bayesianoptimisation-stacking,Tabular Playground Series - Jul 2021
2487,69067554,761.0,0.2431365879681208,1,1,/ankurgupta92/tps-jul-21-eda-prophet-forecast-catboost,Tabular Playground Series - Jul 2021
2488,67834529,426.0,0.2530606136850963,3,8,/okyanusoz/xgboost-feature-engineering-tps07,Tabular Playground Series - Jul 2021
2489,68010797,778.0,,19,28,/khushishahh/eda-and-lgbm,Tabular Playground Series - Jul 2021
2490,112649814,979.0,,0,1,/yvamshivardhan/gradient-boost-regressor,Tabular Playground Series - Jul 2021
2491,69452736,927.0,0.2398889900702085,1,6,/saikrishnaghanta/tps-july-time-series-different-regressions,Tabular Playground Series - Jul 2021
2492,68490486,400.0,,1,0,/caiquefcoelho/tabular-playground-may-july,Tabular Playground Series - Jul 2021
2493,69332853,730.0,0.3828890317565745,0,2,/pravali/tps-july-keras-tuner,Tabular Playground Series - Jul 2021
2494,67460662,391.0,0.3985223851515345,1,0,/aerdem/tps-jul-lgbmregressor-optuna,Tabular Playground Series - Jul 2021
2495,73530877,487.0,,0,0,/aymericpeltier/eda-feature-selection-late-post,Tabular Playground Series - Jul 2021
2496,67932899,650.0,0.2455455626079969,9,32,/docxian/tabular-playground-7-visualization-baseline,Tabular Playground Series - Jul 2021
2497,67412553,644.0,,0,9,/revathiprakash/tpa-jul-2021-automl-model-explainability,Tabular Playground Series - Jul 2021
2498,69745475,384.0,,0,0,/ferdinandkankanny/tabular-playground-series-jul-2021-with-pycaret,Tabular Playground Series - Jul 2021
2499,67158628,854.0,0.3231272559680011,2,5,/ryanbarretto/eda-simple-blend-starter,Tabular Playground Series - Jul 2021
2500,69416645,354.0,0.2563522036054051,1,5,/jsmithperera/tps-july-xgboost-optuna-5-fold,Tabular Playground Series - Jul 2021
2501,67458058,532.0,0.2507290005184724,3,3,/jonigooner/random-forest-fine-tunning,Tabular Playground Series - Jul 2021
2502,67948830,651.0,0.2503353137692897,10,15,/davidjlochner/vector-autoreg-lgb,Tabular Playground Series - Jul 2021
2503,69334686,433.0,0.2592606565169048,4,11,/prudhvinagula/five-regression-models,Tabular Playground Series - Jul 2021
2504,67901064,636.0,,0,5,/mayankvashisht/notebook51e26c99db,Tabular Playground Series - Jul 2021
2505,67561933,752.0,0.3729667424936854,1,3,/pratikkgandhi/baseline-lgb-model,Tabular Playground Series - Jul 2021
2506,67172368,755.0,0.7333082529678259,0,0,/hynsh96/tps-jul-2021-arima-no-features,Tabular Playground Series - Jul 2021
2507,67805786,640.0,,2,17,/pahandrovich/tps-jul-2021-fast-randomforest-with-sklearnex,Tabular Playground Series - Jul 2021
2508,68265328,355.0,0.254707080194236,0,0,/idaidai/apm-ml-with-different-models,Tabular Playground Series - Jul 2021
2509,68933330,556.0,0.2666762813342303,0,0,/subhomajumder/notebook3e4903b1a0,Tabular Playground Series - Jul 2021
2510,67549073,323.0,0.2564721911823107,4,5,/timothyabwao/tps-07-2021-extra-trees-regression-model,Tabular Playground Series - Jul 2021
2511,67296411,681.0,0.256917017754982,0,5,/tracyporter/jul-21-mlpr-reg-chain,Tabular Playground Series - Jul 2021
2512,67442376,633.0,0.258567225119982,5,12,/jarupula/tps-july-21,Tabular Playground Series - Jul 2021
2513,68165001,839.0,0.2580561171957458,4,8,/hakanerdogan/tps-july-2021-simple-fast-code,Tabular Playground Series - Jul 2021
2514,69527543,830.0,,0,3,/tusharsingh1999/noob-time-series-prediction,Tabular Playground Series - Jul 2021
2515,67207410,395.0,0.2595249501575362,12,20,/debarshichanda/tps-july-xgboost-optuna-5-fold,Tabular Playground Series - Jul 2021
2516,68369825,885.0,,8,10,/vaishakhshetty/tps-july-21-eda-h2oautoml,Tabular Playground Series - Jul 2021
2517,67864626,438.0,0.2604468672876595,1,0,/matteobuccirossi/pollution-prediction-with-random-forests,Tabular Playground Series - Jul 2021
2518,80938946,611.0,0.8342458794489449,0,0,/oskarstachowski/tps-vii-skni-praca-domowa,Tabular Playground Series - Jul 2021
2519,68757446,352.0,0.2703341013508389,2,6,/tetsuya777/tps-july-first-model-lightgbm-ipynb,Tabular Playground Series - Jul 2021
2520,67293556,746.0,0.2655780939528993,2,7,/l3llff/xgboost-optuna,Tabular Playground Series - Jul 2021
2521,67416555,471.0,,2,9,/gsdeepakkumar/tps-july-simple-eda-and-dirty-model,Tabular Playground Series - Jul 2021
2522,67436878,517.0,0.2782204017226291,32,59,/maksymshkliarevskyi/tps-july-eda-baseline-analysis-xgbregressor,Tabular Playground Series - Jul 2021
2523,69116414,962.0,0.3933148105087975,1,5,/arindam235/tabular-playground-jul2021,Tabular Playground Series - Jul 2021
2524,67178286,687.0,0.2694037151692779,0,5,/mikaildogruer/tps-july-2021-light-gbm,Tabular Playground Series - Jul 2021
2525,67185474,593.0,0.3451863890739484,5,6,/brookie210/linear-regression-baseline-eda-tps-july-2021,Tabular Playground Series - Jul 2021
2526,68011533,785.0,0.2696119066963826,1,1,/phileinsophos/tabular-data-july-2021,Tabular Playground Series - Jul 2021
2527,96749088,810.0,,13,62,/parulpandey/explainable-boosting-machines-for-tabular-data,Tabular Playground Series - Jul 2021
2528,69457095,474.0,0.2733888614727053,1,1,/raghavendergangula/kaggle-tabular-playground-july-21,Tabular Playground Series - Jul 2021
2529,67232702,671.0,0.2718579049088271,3,14,/kppetrov/tps-jul-2021-baseline-with-nusvr-model,Tabular Playground Series - Jul 2021
2530,69069814,476.0,,0,5,/azwan92/predict-using-random-forest-regressor-with-default,Tabular Playground Series - Jul 2021
2531,68400874,713.0,,0,1,/alexlichtenberg/playground-notebook,Tabular Playground Series - Jul 2021
2532,69237215,765.0,,0,4,/luiskalckstein/start2finnish-submission-poor-model,Tabular Playground Series - Jul 2021
2533,69181979,655.0,0.2754877020343885,4,7,/tariqchhussain/simple-eda-xgboost-implementation-tps-july-21,Tabular Playground Series - Jul 2021
2534,67245195,845.0,,0,0,/sayancht92/basic-eda-with-xgboost-tps-july,Tabular Playground Series - Jul 2021
2535,68205049,489.0,,1,1,/imad2b/simple-random-forest-approach,Tabular Playground Series - Jul 2021
2536,69182738,675.0,0.2770956463502088,0,1,/ryanglasnapp/july-2021-tps-support-vector-regression,Tabular Playground Series - Jul 2021
2537,67554229,698.0,0.3421943526219769,0,1,/ilikedeeplearning/tabular-playground-xgboost-v1,Tabular Playground Series - Jul 2021
2538,68118580,667.0,,0,0,/hirazawahiroshi/jul-2021-simple-baseline-xgboost,Tabular Playground Series - Jul 2021
2539,69342885,351.0,,0,0,/kaiellis/tab-data-playground-multigrad,Tabular Playground Series - Jul 2021
2540,67395758,712.0,0.2797227341169478,2,16,/yasserhessein/tabular-playground-with-sweetviz-h2o-gbm-xgb,Tabular Playground Series - Jul 2021
2541,67395758,712.0,0.30518968642892,2,16,/yasserhessein/tabular-playground-with-sweetviz-h2o-gbm-xgb,Tabular Playground Series - Jul 2021
2542,69004459,657.0,0.3947381521723911,0,2,/vickz53/tabularjuly2021,Tabular Playground Series - Jul 2021
2543,69218816,831.0,0.2837377178627034,0,0,/himankkavathekar/tps-july-xgboost-with-feature-engineering,Tabular Playground Series - Jul 2021
2544,67978873,872.0,,0,0,/bhavinmoriya/tabular-playground-catboost,Tabular Playground Series - Jul 2021
2545,69423874,896.0,0.2813712994274919,1,4,/yogaram/tabular-playground-submission,Tabular Playground Series - Jul 2021
2546,92609566,520.0,,0,2,/burkaykirnik/hack-bo-azi-i-modelling,Tabular Playground Series - Jul 2021
2547,69587590,559.0,,3,7,/tensorchoko/tabular-playground,Tabular Playground Series - Jul 2021
2548,91177913,584.0,,2,6,/edrickkesuma/tabular-playground-series-pollution-with-xgboost,Tabular Playground Series - Jul 2021
2549,68993121,875.0,,0,6,/elakapoor/july-kaggle-playground,Tabular Playground Series - Jul 2021
2550,68220532,900.0,,3,6,/valmetisrinivas/tabular-playground-series-jul-2021-eda-vs,Tabular Playground Series - Jul 2021
2551,67873070,836.0,,4,10,/shubhikant/dnn-regression,Tabular Playground Series - Jul 2021
2552,67267096,841.0,0.2995349896103795,3,9,/karinbondgaard/ml-your-grandmother-can-do,Tabular Playground Series - Jul 2021
2553,68298463,940.0,,17,21,/arnabbiswas1/visualizing-seasonality-with-w-o-statistics,Tabular Playground Series - Jul 2021
2554,70020101,888.0,,0,1,/gunater/tabular-playground-series-jul-2021,Tabular Playground Series - Jul 2021
2555,67164955,791.0,,17,17,/sohommajumder21/tps-july-2021-eda-visulaizations-predictions,Tabular Playground Series - Jul 2021
2556,67191758,843.0,0.4628135004538283,0,2,/horohoro/simple-linearregression,Tabular Playground Series - Jul 2021
2557,67616492,902.0,0.3332592926145186,1,2,/viktorurushkin/naive-svr,Tabular Playground Series - Jul 2021
2558,69155266,957.0,0.4019069524434656,0,8,/olehmezhenskyi/knn-regression-for-air-quality,Tabular Playground Series - Jul 2021
2559,70008628,1055.0,,0,7,/farelarden/tabular-jul-2021,Tabular Playground Series - Jul 2021
2560,69519382,864.0,,0,3,/akhil14shukla/tabular-playground-jul-21,Tabular Playground Series - Jul 2021
2561,69117321,805.0,0.7817481530287874,2,6,/rogerszzz/lstm-aqi,Tabular Playground Series - Jul 2021
2562,67194270,1072.0,,0,0,/dipromondal/tabular-playground-linear-regression,Tabular Playground Series - Jul 2021
2563,67229801,1073.0,,0,0,/rushikeshdarge/tps-july21-baseline-linear-regression,Tabular Playground Series - Jul 2021
2564,67352705,918.0,,0,6,/rajatpaliwal02/tps-july-fastai-decision-tress-random-forset,Tabular Playground Series - Jul 2021
2565,68012841,958.0,,19,32,/the0electronic0guy/visualization-basic-neural-net-score-0-3694,Tabular Playground Series - Jul 2021
2566,67911102,999.0,,6,9,/gauravduttakiit/sensor-data-prediction,Tabular Playground Series - Jul 2021
2567,68489122,1099.0,0.3778744442582047,0,0,/mohameddhameem/automl-with-pycaret-and-custom-featureextraction,Tabular Playground Series - Jul 2021
2568,73258958,933.0,,0,0,/aryarn/tabular-playground-series-jul-2021,Tabular Playground Series - Jul 2021
2569,69295663,1042.0,,0,0,/mike123/using-pycaret-catboost-catboost-catboost,Tabular Playground Series - Jul 2021
2570,68273585,1098.0,,40,53,/godzill22/tps-07-eda-statistical-analysis,Tabular Playground Series - Jul 2021
2571,67743122,1021.0,,7,15,/rsesha/july-tps-deep-autoviml-score-0-60,Tabular Playground Series - Jul 2021
2572,69436363,1169.0,,0,1,/akashanair92/air-pollution-measurements-lgbm-july,Tabular Playground Series - Jul 2021
2573,67177219,1200.0,,0,0,/padalatejasaikumar/simple-tps-july-2021,Tabular Playground Series - Jul 2021
2574,68624975,1223.0,,2,2,/kayleighmilewski/predicting-air-pollution,Tabular Playground Series - Jul 2021
2575,67283758,1116.0,0.5146337597315659,0,1,/jluza92/tps-xgbregressor-vs-multi-output-neural-network,Tabular Playground Series - Jul 2021
2576,67992328,1214.0,,0,4,/rakinaljubair/tabular-prediction-using-basic-nn,Tabular Playground Series - Jul 2021
2577,86687047,1237.0,,0,5,/kamaljp/tabular-data-competition,Tabular Playground Series - Jul 2021
2578,68973672,1240.0,0.7551674795923655,0,1,/sabyasachi96/tps-july-simple-sarima-model,Tabular Playground Series - Jul 2021
2579,68159494,1232.0,,0,0,/mdmustafijurrahman/tabular-series-july-21,Tabular Playground Series - Jul 2021
2580,69168956,596.0,,5,52,/osciiart/public-lb-simulation,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2581,75627640,1013.0,,5,12,/huyquoctrinh/stack-inference,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2582,75121654,1526.0,0.7156448202959831,0,3,/adityasharma01/rsna-ensemble-264fca,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2583,77478862,1025.0,,1,0,/v1olet1nor1/rsna-custom-train,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2584,75045933,927.0,,8,19,/ammarnassanalhajali/brain-tumor-3d-eda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2585,77268738,1021.0,,0,1,/satoshimts/2dcnn-score-0-746,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2586,71623691,989.0,,0,1,/louieshao/covid-nifti-preprocess-0-of-1,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2587,76074609,895.0,,0,7,/manithvazirani/dicom-2-nifti-and-animation,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2588,77446055,1454.0,,3,4,/trinayanbharadwaj/rsna-miccai-competition-0-57385-private,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2589,76425427,1184.0,,2,14,/zaakciiru/dicom-to-nifti-registration-captk,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2590,68334882,1240.0,,4,6,/lalehsfz/converting-dicom-to-numpy-by-vtk,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2591,72424911,396.0,,2,4,/snish9/rsna-gbm-reconstruct-data,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2592,75606847,1216.0,0.7304439746300211,1,2,/pvtien96/solution-ensemble,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2593,75981437,478.0,,4,14,/nishanthaddagatla/brain-tumor-3d-blender-b6280a,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2594,76873732,1270.0,0.5724101479915433,0,0,/tegzes/brain-tumor-kerastuner,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2595,73702339,1233.0,0.6937103594080338,0,4,/lonnieqin/brain-tumour-classification-v6,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2596,76164402,1245.0,0.7320295983086681,4,34,/luongduongminh/brain-tumor-3d,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2597,74021526,1262.0,,4,28,/junhyeok99/rsna-baseline,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2598,76799411,1265.0,,1,5,/rhythmcam/glob-glob-sort-filepath-read-dcm-by-pydicom,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2599,68913678,1482.0,,1,15,/tensorchoko/rsna-miccai-eda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2600,68930728,912.0,,29,143,/boojum/connecting-voxel-spaces,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2601,76985821,118.0,,0,2,/yutongkai/rsna-resnet50-training,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2602,76108610,1323.0,,0,1,/xiyoumocao/cnn-tensorflow-resnet50,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2603,71182557,1167.0,,0,0,/chamecall/braintumor-eda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2604,70073642,1373.0,,1,3,/santohide/roc-auc,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2605,73523098,1205.0,,4,7,/ivgona/rnsa-miccai-glioblastoma-eda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2606,76292740,1221.0,,1,8,/sandeep2812/brain-tumor,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2607,76414303,1298.0,,0,3,/scarere/rsna-miccai-create-tfrecord-dataset,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2608,76593778,1431.0,0.697938689217759,2,3,/yuujinleee/rsna-miccai-with-keras-blend,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2609,73534077,1364.0,0.3742071881606765,0,3,/dragonzhang/rsna-miccai-fastai-competition,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2610,69161061,693.0,0.5412262156448203,1,3,/zhangkaiyu/v2-model-result,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2611,77123509,121.0,0.6120507399577167,0,0,/pollakrit/brain-tumor-3d-prediction,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2612,76506959,1362.0,,0,2,/sushmit0109/xray-denoising-draft,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2613,74485711,876.0,,2,7,/bpetrb/3d-image-rotation,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2614,72024062,6.0,,0,0,/namgalielei/brainsavedata,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2615,74335574,119.0,,4,10,/sauravmaheshkar/rsna-miccai-the-random-seed-fluke,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2616,77899580,174.0,,25,72,/mikecho/rsna-miccai-monai-ensemble,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2617,73856792,1028.0,,0,3,/theunrealsamurai/rsna-brain-tumor,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2618,68539367,484.0,,8,27,/orkatz2/autofocus-layer-brain-tumor-segmentation,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2619,76358302,1552.0,0.6202431289640592,10,52,/mmellinger66/brain-tumor-basic-tensorflow-model,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2620,76070932,4.0,,14,117,/davidbroberts/determining-mr-image-planes,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2621,74439766,365.0,,1,17,/victorfernandezalbor/brats-20-win-nnunet-segment-with-brats-21-rsna,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2622,77107578,310.0,,0,0,/formtyan/train-densenet,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2623,73700011,93.0,0.5919661733615222,1,4,/nararyoya/nara-load-params,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2624,76169210,609.0,,0,0,/stelis/rsna-btrc-xception2d-imagenet,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2625,76636773,535.0,,0,1,/siddharthkirs/fork-of-mrichallengenote1,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2626,70163024,384.0,,0,1,/hazigin/create-tfrecord-for-rsna-radiogenomic,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2627,75750346,177.0,0.5652748414376322,0,0,/shaochiehlin/rsna-torchio-inference-baseline,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2628,75745097,570.0,0.5681818181818182,9,15,/avirdee/rsna-miccai-initial-fmi-fastai,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2629,68339599,52.0,,2,9,/yashvadi9274/3d-resized-images-in-numpy-array,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2630,73621126,839.0,,1,14,/rickandjoe/rsna-miccai-brain-tumor-domain-knowledge-eda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2631,73082630,113.0,,8,36,/kavehshahhosseini/rsna-brain-tumor-tensorflow-tpu-tfrecords-train,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2632,76987656,1484.0,0.5280126849894292,0,10,/shakshyathedetector/rsna-miccai-brain-tumor-radiogenomic,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2633,72118922,840.0,0.6334566596194503,6,9,/stpeteishii/rsna-brain-tumor-dicom-conv2d,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2634,76898304,1038.0,0.5126849894291755,0,0,/bilinli/inference-rsna,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2635,75892623,243.0,0.5988372093023255,0,6,/rameshsimhadri/single-pass-training,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2636,73414465,940.0,,3,9,/masatomurakawamm/tf-simple-prediction-with-vgg16,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2637,68940639,679.0,,0,0,/allanyiinai/rsna-miccai-brain-tumor-baseline,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2638,69914184,206.0,,0,9,/adhitio/display-middle-images-plane-adjust-contrast,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2639,74603634,655.0,,12,21,/d223chen/rsna-miccai-competition-middle-most-flair-scan,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2640,101820597,176.0,0.6358350951374208,0,1,/jiayukamessizhao/recitation-i-orc-common-experience,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2641,72170418,1527.0,,0,2,/evanyao27/team-9-week-1,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2642,71569055,620.0,,1,3,/siddharthtandon/rsna-miccai-data-analysis,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2643,77118556,3.0,0.6358350951374208,7,17,/cedricsoares/tf-efficientnet-transfer-learning-strat-split,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2644,77118556,3.0,0.6316067653276956,7,17,/cedricsoares/tf-efficientnet-transfer-learning-strat-split,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2645,77118556,3.0,0.6590909090909091,7,17,/cedricsoares/tf-efficientnet-transfer-learning-strat-split,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2646,68288856,89.0,,0,4,/craigwickizer/rsna-miccai-tensorflow-dicom-dataframe-flow,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2647,68333309,513.0,,2,6,/lucamtb/eda-save-file-brt-classification,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2648,68159425,862.0,,0,4,/ludovicchangeon/brain-tumor-exploration-dicom-to-video,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2649,74146614,78.0,0.4841437632135306,0,0,/chansocheattieng/brain-tumor-all-mri-3d-cnn-inference,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2650,74146614,78.0,0.4841437632135306,0,0,/chansocheattieng/brain-tumor-all-mri-3d-cnn-inference,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2651,77669486,662.0,,3,9,/anlthms/leaderboard-simulation,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2652,75572028,378.0,,0,4,/qitvision/public-lb-simulation,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2653,71190601,255.0,,0,2,/aryamansharma47/saving-images-as-numpy-for-faster-training,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2654,73264784,134.0,,4,14,/jirkaborovec/brain-tumor-classif-lightning-efficientnet3d,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2655,73374643,664.0,,0,1,/arunamenon/eda-data-processing-basic-cnn-tumor-classification,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2656,76647838,66.0,0.6501057082452432,0,0,/greylord1996/resnet34-all-mri,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2657,76986167,250.0,0.5306553911205074,0,0,/dhruvkhatri/rsna-1-tf,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2658,77747296,5.0,0.6173361522198731,0,3,/abhimanyukarshni/rsna-inference,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2659,70826469,124.0,,0,0,/mstkmyhr/2021-08-09-brain-tumor-count-of-images,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2660,89895413,567.0,,0,1,/fenofista/rsna-miccai,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2661,75657700,223.0,,0,2,/holliday/animation-of-torchio-preprocessing,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2662,76751115,314.0,,0,2,/jypysk/nokfold-test-submission-v0,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2663,70835410,730.0,,1,7,/kevinleekrus/rsna-miccai-understanding-the-data,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2664,75230622,793.0,,1,0,/walterok/batch-inference-making-masks-using-nnunet,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2665,77142650,191.0,,0,0,/gauravsawant/unet-segmentation-final,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2666,76711928,569.0,,0,0,/tanmayg25/rsna-competition,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2667,74022085,130.0,,14,66,/fepegar/preprocessing-mri-with-torchio,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2668,75967937,320.0,0.641384778012685,0,10,/lars123/leak-in-metadata,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2669,75255339,166.0,0.6210359408033826,3,9,/billqi/efficientnet-transfer-learning-model-full,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2670,69138288,851.0,,4,4,/abhijeetptl5/video-data-from-miccai-png,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2671,69008836,23.0,,16,23,/ranafago/preprocessing-dcm-to-nifti,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2672,68187611,637.0,,2,7,/ninjakx01/brain-mri-visualization,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2673,73499977,106.0,0.5761099365750528,0,3,/b3d1rhan/tumor-classifier,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2674,75401758,149.0,0.6326638477801269,0,0,/hamza3e/brain-tumor-radiogenomic-classification,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2675,70970330,75.0,,6,99,/arnabs007/part-1-rsna-miccai-btrc-understanding-the-data,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2676,75466374,248.0,,0,0,/slm37102/csv-folder-for-brain-tumor,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2677,70734499,204.0,,15,53,/josecarmona/btrc-eda-final,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2678,77082060,156.0,,0,0,/alexandrfrolov/preproc-funcs,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2679,81894921,340.0,,0,7,/ahemateja19bec1025/rsna-brain-tumor-conv-fda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2680,68196918,518.0,,3,7,/meenakshiramaswamy/rsna-miccai-mri-visualize-dicom,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2681,72407180,61.0,0.6242071881606766,0,0,/buketdarci/fast-3dcnn-model,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2682,87032335,402.0,,1,1,/sanjayanbu/rsna-competition,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2683,74728615,898.0,,0,0,/selvakumarperumal/btrc-pp,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2684,74519212,1.0,0.6078224101479915,3,32,/rinnqd/monai-simple-prediction-from-flair,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2685,68780450,568.0,,6,7,/aristotle609/basic-eda-rsna,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2686,73661831,271.0,0.4587737843551797,0,0,/glenndean/notebook051cf986c7,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2687,73981293,273.0,0.5433403805496829,2,6,/pranshu15/273rd-place-solution-skipping-slices-inference,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2688,76756629,537.0,,0,1,/qdstro/submission-test,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2689,89265055,681.0,,0,2,/toutatsu/brain-tumor-efficientnet-3d,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2690,75616260,978.0,0.6131078224101479,0,1,/krishna18vamsi/notebookf92e1ef218,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2691,73287828,207.0,,8,80,/spacedoge/task1-segmentation-interactive-3d-eda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2692,75726307,398.0,0.5338266384778013,4,40,/pranav2109/mri-classification-data-pipeline-pytorch,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2693,71224288,931.0,,0,4,/yeseulkim96/ys-preprocessing-2dver-v0,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2694,74513499,618.0,,3,9,/srikanthmachiraju/predict-genetic-biomarker-in-brain-tumor-eda,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2695,69093706,1467.0,,0,1,/ksmcg90/dataset-resizer-miccai,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2696,70925449,105.0,,0,0,/mananjhaveri/rsna-brain-train-baseline,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2697,71591099,930.0,,2,7,/arminajdehnia/brain-tumour-preprocessing,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2698,72452372,902.0,,0,0,/sdpatiba/rsna-miccai-brain-tumor-dataset,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2699,76770127,391.0,,1,2,/dylandehili/create-tfrecord-for-3d-image,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2700,77897011,7.0,,4,10,/igorlashkov/rsna-miccai-btumor-classification-finished,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2701,75314514,947.0,,3,6,/ohbewise/dicom-to-nifti-with-dcmstack,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2702,68322996,1457.0,,4,9,/aninda/rsna-radiogenomic-starter,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2703,68556173,60.0,,2,2,/favianh/simple-dicom-visualizer,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2704,70941593,621.0,,0,0,/amokranemancer/rsna-miccai-btr-classification-data-preparation,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2705,69174528,663.0,,10,27,/furcifer/no-baseline-pytorch-cnn-for-mri,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2706,68645453,408.0,0.5734672304439746,3,8,/hamzajebbar/brain-tumor-radiogenomic-classification,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2707,77702448,1442.0,0.4904862579281184,0,0,/panuvit/first-try,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2708,70966064,1388.0,,2,12,/hugovallejo/braintumormri-png-with-keras-preprocessing,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2709,77139973,1451.0,0.3808139534883721,3,9,/vexxingbanana/simple-pytorch-cnn,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2710,74903404,965.0,0.5,0,2,/samarthsharma1408/brain-tumor-classification-transfer-learning,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2711,71029026,973.0,,0,0,/somesh88/brain-tumor-classification,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2712,73386209,1495.0,,0,15,/marshath/btrg-dicom-to-nifti-using-sri24-to-resample,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2713,77680053,8.0,,1,5,/arturhcpereira/rsna-miccai-submission,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2714,70225369,870.0,,7,8,/zrafiws/brain-mri-visualisation-with-tensorflow-io,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2715,69099607,1074.0,,0,0,/alvarofbudria/rsne-cnn-rnn,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2716,70626529,488.0,,17,120,/chumajin/brain-tumor-eda-for-starter-version,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2717,76407807,667.0,,0,3,/nigelyaoj/pytorch-conv3d,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2718,70755995,1051.0,,2,6,/drcapa/rsna-miccai-brain-tumor-starter,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2719,153073285,1052.0,,17,98,/muhammadimran112233/transfer-learning-brain-tumor-classification,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2720,68493721,1061.0,,22,80,/mpwolke/glioblastoma-mri-dicom-format,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2721,77187016,1404.0,,0,2,/yshuang115/f-one,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2722,68177383,415.0,,4,19,/konradb/image-resizing,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2723,74723241,1029.0,,2,7,/normalkim0/rsna-brain-simple-eda-dataset,RSNA-MICCAI Brain Tumor Radiogenomic Classification
2724,70567689,3.0,7.862591584431693,24,114,/alexryzhkov/aug21-lightautoml-starter,Tabular Playground Series - Aug 2021
2725,69815292,2.0,7.89425891765102,12,33,/pourchot/only-one-hidden-layer-for-neural-network,Tabular Playground Series - Aug 2021
2726,72538056,1.0,7.87434703567359,6,12,/ivankontic/003-2-kmeans-and-gmm-feature-extraction-tps-aug,Tabular Playground Series - Aug 2021
2727,73256471,29.0,,10,33,/mhslearner/can-tabnet-do-better-eda-submission,Tabular Playground Series - Aug 2021
2728,71146386,161.0,7.855909091195812,58,84,/somayyehgholami/1-tps-aug-21-xgboost-catboost,Tabular Playground Series - Aug 2021
2729,73053825,182.0,,2,26,/akmalmir/baseline-with-automl-pycaret-rmse-score-7-89114,Tabular Playground Series - Aug 2021
2730,69559798,63.0,7.872614034146408,21,93,/pranjalverma08/tps-08-cb-lgbm-xgb-starter,Tabular Playground Series - Aug 2021
2731,69559798,63.0,7.875766216569727,21,93,/pranjalverma08/tps-08-cb-lgbm-xgb-starter,Tabular Playground Series - Aug 2021
2732,69559798,63.0,7.896956350894572,21,93,/pranjalverma08/tps-08-cb-lgbm-xgb-starter,Tabular Playground Series - Aug 2021
2733,70182892,117.0,,7,20,/junhyeok99/tps-pycaret-simple-baseline,Tabular Playground Series - Aug 2021
2734,73660233,115.0,7.849862486651503,11,42,/aayush26/tps-aug-2021-simple-weighted-ensemble,Tabular Playground Series - Aug 2021
2735,70303425,132.0,,9,10,/amiteshgangrade/eda-basic-neural-network,Tabular Playground Series - Aug 2021
2736,84615683,110.0,,0,3,/rhythmcam/tps-08-21-optuna-integration-oof,Tabular Playground Series - Aug 2021
2737,69922322,307.0,,3,3,/jonigooner/tensorflow-gradient-boost,Tabular Playground Series - Aug 2021
2738,73545820,123.0,,0,0,/farjanaemanishy/tab-simp,Tabular Playground Series - Aug 2021
2739,73268574,636.0,,0,11,/knightbearr/just-want-to-play-a-game,Tabular Playground Series - Aug 2021
2740,73660828,124.0,7.941062293396794,0,0,/rodrigocfaria/very-simple-bayesian-ridge-regression,Tabular Playground Series - Aug 2021
2741,72905530,101.0,,0,2,/sureshmecad/tps-aug21-ensemble-stacking-automl,Tabular Playground Series - Aug 2021
2742,73134789,125.0,7.86524725734104,0,0,/mirenaborisova/tabular-playground-aug-2021-02,Tabular Playground Series - Aug 2021
2743,73221254,144.0,,0,14,/vaby667/84996to-improve-your-ranking,Tabular Playground Series - Aug 2021
2744,72690303,148.0,7.949254492252377,3,14,/kavehshahhosseini/tabular-playground-neural-network,Tabular Playground Series - Aug 2021
2745,157847061,16.0,,0,1,/jonathanpaserman/figuring-out-catboost-optuna,Tabular Playground Series - Aug 2021
2746,70252174,9.0,,2,5,/kareem3egm/tps-aug-2021-with-h2oautoml,Tabular Playground Series - Aug 2021
2747,69812660,38.0,7.892134817661351,0,5,/krishnamore/simple-xgbclassifier,Tabular Playground Series - Aug 2021
2748,70192696,31.0,7.972341723889277,3,8,/srjchauhan/tps-08-eda-autokeras-neural-network,Tabular Playground Series - Aug 2021
2749,69666093,60.0,7.880006711559102,9,24,/dmitryuarov/tps-aug-2021-eda-cb-vs-xgb-vs-lgbm,Tabular Playground Series - Aug 2021
2750,69977653,70.0,,8,38,/bextuychiev/relevant-eda-xgboost,Tabular Playground Series - Aug 2021
2751,73262784,54.0,,1,7,/prajwalsood/auto-keras-example7-89-with-no-feature-engineering,Tabular Playground Series - Aug 2021
2752,76019685,48.0,,1,13,/shrutisaxena/tps-aug-2021-eda,Tabular Playground Series - Aug 2021
2753,73217007,135.0,,3,8,/arnabbiswas1/classification-approach-lgbm-log-loss,Tabular Playground Series - Aug 2021
2754,71453961,18.0,7.862480188767779,4,20,,Tabular Playground Series - Aug 2021
2755,88228539,128.0,,23,48,/devsubhash/tps-aug-21-ensemble-stackingcvregressor,Tabular Playground Series - Aug 2021
2756,69562958,53.0,,1,6,/vuxxxx/xgboost-lightgbm-kfold-baseline,Tabular Playground Series - Aug 2021
2757,73389398,41.0,7.94703789451053,11,20,/joonrisse/tps-particle-swarm-optimization-feature-selection,Tabular Playground Series - Aug 2021
2758,70539725,195.0,,4,15,/paddykb/tps-08-short-eda,Tabular Playground Series - Aug 2021
2759,70341902,35.0,7.94633162920948,4,7,/jenilsavani/ann-playground-series,Tabular Playground Series - Aug 2021
2760,72052065,398.0,7.947399840404035,0,0,/realtimshady/trying-7-cool-python-packages,Tabular Playground Series - Aug 2021
2761,71068731,20.0,7.946991792870435,5,14,/miguelquiceno/tps-basic-eda-nn-keras,Tabular Playground Series - Aug 2021
2762,72868387,142.0,7.890362778250955,1,6,/sankalpsrivastava26/catboost-optimization,Tabular Playground Series - Aug 2021
2763,71558042,87.0,7.890870311631067,2,12,/astashiro/tps-aug2021-01pycaret-shap,Tabular Playground Series - Aug 2021
2764,73412400,12.0,7.884797253452203,11,15,/kritidoneria/automl-mljar-fe-modelling-ensemble-tps-aug-21,Tabular Playground Series - Aug 2021
2765,70429578,133.0,7.870435379834474,29,60,/oxzplvifi/tabular-denoising-residual-network,Tabular Playground Series - Aug 2021
2766,73766192,449.0,,0,1,/aymericpeltier/ensembling-xgb-lgb-cat-nn,Tabular Playground Series - Aug 2021
2767,71021936,172.0,7.87550795534777,2,6,/tolgakurtulus/optuna-tuning-with-xgboost-catboost-lgbm,Tabular Playground Series - Aug 2021
2768,70336269,171.0,,9,27,/songwonmin/for-korean-tabular-aug-2021,Tabular Playground Series - Aug 2021
2769,69801009,177.0,,4,15,/skomuro/notebook-for-kaggle-beginners-like-me-ver-1-2,Tabular Playground Series - Aug 2021
2770,69825150,189.0,7.893090793753461,12,35,/boneacrabonjac/automl,Tabular Playground Series - Aug 2021
2771,70653023,202.0,7.980417132040082,2,5,/batprem/training-environment,Tabular Playground Series - Aug 2021
2772,70562455,208.0,7.888807482581407,5,10,/farelarden/tabular-playground-series-aug-2021,Tabular Playground Series - Aug 2021
2773,70441115,226.0,,1,2,/alvinb/submission,Tabular Playground Series - Aug 2021
2774,69627120,227.0,8.00841371201233,6,13,/kudasovdmitriy/cat-lgbm-xgb,Tabular Playground Series - Aug 2021
2775,70305061,232.0,7.939381872547038,16,24,/yogidsba/tps-aug-eda-basemodel,Tabular Playground Series - Aug 2021
2776,69630325,229.0,7.983712169160409,2,10,/jarupula/tps-aug-2021-eda-rf,Tabular Playground Series - Aug 2021
2777,73600754,228.0,,0,0,/data2science/xgb-and-catboost-optuna-tuning-basic-blend,Tabular Playground Series - Aug 2021
2778,69544224,244.0,,2,11,/munumbutt/comparing-boosted-tree-algorithms,Tabular Playground Series - Aug 2021
2779,72657288,240.0,,3,5,/jchang4/playgroundtabular-aug-fast-ai-optuna,Tabular Playground Series - Aug 2021
2780,70189921,237.0,,5,15,/shivansh002/tps-august-eda,Tabular Playground Series - Aug 2021
2781,71623017,267.0,7.862363903777131,10,36,/tensorchoko/tabular-aug-2021-lightgbm,Tabular Playground Series - Aug 2021
2782,76780721,268.0,,1,10,/raahulsaxena/tps-aug-21-introduction-to-simple-voting,Tabular Playground Series - Aug 2021
2783,76481380,287.0,,0,10,/haruomiyoshikawa/tps-8-lightgbm-stratifiedkfold,Tabular Playground Series - Aug 2021
2784,70933320,285.0,,0,0,/yuqihanhan/tps-08-2021-xgboost-analysis-eda,Tabular Playground Series - Aug 2021
2785,73783164,294.0,,3,12,/lukaszborecki/tf-binning-embedding-huber-loss-fold-5,Tabular Playground Series - Aug 2021
2786,71742327,313.0,,1,7,/alenic/stratifiedkfold-lgbm-optuna-7-88214,Tabular Playground Series - Aug 2021
2787,70811066,309.0,7.910670777064804,6,14,/bhuppi2898/tps-august-with-pycaret-for-newbies,Tabular Playground Series - Aug 2021
2788,73607453,304.0,,6,12,/udbhavpangotra/eda-optuna-an-attempt-at-a-clean-notebook,Tabular Playground Series - Aug 2021
2789,73199044,305.0,,1,2,/ratorato/tabular-playground-aug-2021-tabnet-and-pycaret,Tabular Playground Series - Aug 2021
2790,73122515,300.0,7.8686210766231985,16,42,/ranjeetshrivastav/tps-aug-21-optuna-lgb-xgb-cb,Tabular Playground Series - Aug 2021
2791,73122515,300.0,7.8686210766231985,16,42,/ranjeetshrivastav/tps-aug-21-optuna-lgb-xgb-cb,Tabular Playground Series - Aug 2021
2792,71581358,330.0,7.879419696294496,13,73,/michael127001/xgbregressor-with-optuna-tuning,Tabular Playground Series - Aug 2021
2793,69957392,427.0,7.879985347896297,5,12,/azzamradman/tps-08-lightgbm-simple-eda,Tabular Playground Series - Aug 2021
2794,73041232,337.0,7.882758794134511,0,2,/nitinrajput47/stacking-regressor,Tabular Playground Series - Aug 2021
2795,70295871,358.0,,1,4,/mustafacicek/xgboost-train-and-fit-comparison,Tabular Playground Series - Aug 2021
2796,70106269,341.0,7.882685161933972,0,4,/hrbukhari/optuna-tuned-boosting-models-cat-xgb,Tabular Playground Series - Aug 2021
2797,71761374,347.0,7.879011437372888,11,23,/abhijeet29/1st-competition-xgboost-optuna,Tabular Playground Series - Aug 2021
2798,73234608,355.0,,0,3,/vishalmishra1400/xgbregressor,Tabular Playground Series - Aug 2021
2799,70334281,349.0,7.87094720432799,9,30,/ryanbarretto/two-stage-stacking-ensemble,Tabular Playground Series - Aug 2021
2800,69681498,364.0,7.939487467758973,0,3,/docxian/tabular-playground-8-linear-baseline,Tabular Playground Series - Aug 2021
2801,71441015,428.0,7.878724347189938,6,1,/yuujinleee/tabular-aug-2021,Tabular Playground Series - Aug 2021
2802,72000645,382.0,,5,15,/joatom/model-allocation,Tabular Playground Series - Aug 2021
2803,70059306,415.0,,34,105,/subinium/tps-aug-simple-eda,Tabular Playground Series - Aug 2021
2804,71950912,425.0,,9,24,/tunguz/tps-08-2021-simple-linear-baseline,Tabular Playground Series - Aug 2021
2805,73445095,393.0,,1,3,/scr0ll0/august-2021-lgbm-xgb-catboost-optuna,Tabular Playground Series - Aug 2021
2806,69597060,381.0,7.905102286458116,0,7,/gomes555/tps-aug2021-eda-sweetviz-pycaret-baseline,Tabular Playground Series - Aug 2021
2807,91178914,396.0,,0,5,/edrickkesuma/yeo-johnson-optuna-kfold-cv-xgbregressor,Tabular Playground Series - Aug 2021
2808,69766527,392.0,7.873853317158288,31,55,/maximkazantsev/tps-08-21-catboost,Tabular Playground Series - Aug 2021
2809,73436203,443.0,7.8731187412053,2,9,/aleksandraposka/automl-mljar-by-ola-optuna-tune-tps-aug-21,Tabular Playground Series - Aug 2021
2810,71256319,413.0,7.885782708864055,4,15,/aymanlafaz/tps-lda-catboost,Tabular Playground Series - Aug 2021
2811,71486300,476.0,7.876297027482643,4,8,/ranjeer/xgboost-for-tabular-playground,Tabular Playground Series - Aug 2021
2812,70161584,424.0,7.879991431558801,0,3,/ezekielknight/tps-aug-2021-autogluon-baseline,Tabular Playground Series - Aug 2021
2813,73639928,387.0,7.87904340273406,1,0,/inhack/tps-aug-21-eda-basemodel-xgb-lgbm-optuna,Tabular Playground Series - Aug 2021
2814,73639928,387.0,7.879185725556347,1,0,/inhack/tps-aug-21-eda-basemodel-xgb-lgbm-optuna,Tabular Playground Series - Aug 2021
2815,70565063,450.0,,3,6,/catadanna/tab-aug-folds,Tabular Playground Series - Aug 2021
2816,73354478,411.0,,6,14,/nancysamuel/tps-aug2021-xgboost-kfold,Tabular Playground Series - Aug 2021
2817,72400992,469.0,,0,5,/ted0071/tps-aug-2021,Tabular Playground Series - Aug 2021
2818,72525265,542.0,,1,0,/khule28/notebook3cde976ec3,Tabular Playground Series - Aug 2021
2819,70569074,630.0,7.937019266009754,1,2,/navidalazim/tabular-playground-tabnet,Tabular Playground Series - Aug 2021
2820,72910446,507.0,7.934585424737698,1,3,/danieleongari/tps-08-21-xgboost-compared-with-mean-baseline,Tabular Playground Series - Aug 2021
2821,74394331,503.0,,0,0,/davidaheredia/tps-aug-2021,Tabular Playground Series - Aug 2021
2822,73521713,497.0,,0,0,/yvamshivardhan/aug2021-optuna-xgboost,Tabular Playground Series - Aug 2021
2823,70438871,504.0,7.878360984019378,13,26,/riyajm/gpu-based-xgb-hyperopt-optimization,Tabular Playground Series - Aug 2021
2824,72046672,541.0,,0,0,/jiangtt/tps-aug-adversarial-validation,Tabular Playground Series - Aug 2021
2825,70843740,558.0,7.906214863238906,6,20,/l0glikelihood/nn-starter-keras,Tabular Playground Series - Aug 2021
2826,69670007,533.0,,7,15,/amritpal333/tps-aug-eda-baseline-model,Tabular Playground Series - Aug 2021
2827,73074546,529.0,7.9160535165028945,0,4,/himanshunitrr/tps-aug,Tabular Playground Series - Aug 2021
2828,71495774,548.0,24518873.01458329,0,2,/smita09/tps-august-baseline-model,Tabular Playground Series - Aug 2021
2829,72741032,505.0,7.921936631910154,0,3,/christoforum/lightgbm-optuna,Tabular Playground Series - Aug 2021
2830,72729585,568.0,7.905006916215323,8,3,/flafuji/lightxgboost-playground-explained-in-3-minutes,Tabular Playground Series - Aug 2021
2831,72729585,568.0,7.905006916215323,8,3,/flafuji/lightxgboost-playground-explained-in-3-minutes,Tabular Playground Series - Aug 2021
2832,69534668,579.0,7.949090401298183,0,12,/andy6804tw/tps-08-21-xgboost,Tabular Playground Series - Aug 2021
2833,73519568,632.0,,0,0,/lukaszsajkowski/blending-looking-for-weights-tps-aug-2021,Tabular Playground Series - Aug 2021
2834,69981751,561.0,7.939421906524951,7,14,/balavashan/tps-aug-2021-using-linearregression,Tabular Playground Series - Aug 2021
2835,73645858,627.0,7.884513566973346,0,1,/ujoshi076/tps-xgboost-hp-tuning-with-optuna,Tabular Playground Series - Aug 2021
2836,69518288,566.0,7.930688641812576,0,12,/maksymshkliarevskyi/tps-aug-eda-baselines-xgb-keras-nn,Tabular Playground Series - Aug 2021
2837,73291310,643.0,7.885488549259175,0,0,/truongdang1311/optuna-and-stacking-model-xgb-lgbm,Tabular Playground Series - Aug 2021
2838,69802323,608.0,7.88328027714869,1,7,/sami116/baseline-model-xgb,Tabular Playground Series - Aug 2021
2839,73119568,663.0,7.883301779108352,1,6,/karad1818/tabular-data-xgb,Tabular Playground Series - Aug 2021
2840,71455625,648.0,7.883357420769965,0,0,/shugo15/tps-aug-21-lgbm,Tabular Playground Series - Aug 2021
2841,69581877,649.0,,0,1,/saruhangngr/playgraund-pred-aug,Tabular Playground Series - Aug 2021
2842,73675081,588.0,,4,0,/sergeyzemskov/tps-08-21-cross-val-catboost-eda,Tabular Playground Series - Aug 2021
2843,73401464,641.0,7.883976702771319,0,4,/viveksalunkhe/tabular-playground-aug-2021-xgb-cat,Tabular Playground Series - Aug 2021
2844,71172263,660.0,7.886331239452182,17,11,/faelk8/tps-aug-21-eda-lightautoml,Tabular Playground Series - Aug 2021
2845,102022504,667.0,,2,4,/markbquant/aug-21-alternative-h2o-stacking-and-blending,Tabular Playground Series - Aug 2021
2846,70338723,681.0,,1,2,/hoangminhquanlhsdt/tps-08-lightgbm,Tabular Playground Series - Aug 2021
2847,73674295,692.0,7.888666878255726,0,5,/swagician/august-r-bayesian-additive-regression-trees,Tabular Playground Series - Aug 2021
2848,70715953,695.0,7.911376566517273,4,10,/volkandl/tps-08-eda-xgboost,Tabular Playground Series - Aug 2021
2849,72449422,755.0,7.890247489998115,1,3,/jzeferino/playg-8-21-lightgbm-random-search-cv,Tabular Playground Series - Aug 2021
2850,70940249,731.0,7.888811894940154,1,3,/vbloise/tps-aug-21-xgboost-implementation,Tabular Playground Series - Aug 2021
2851,73488159,760.0,7.889255159322356,2,6,/akioonodera/tps-aug2021-lgbm-regression,Tabular Playground Series - Aug 2021
2852,70628586,737.0,,7,35,/stpeteishii/tps0821-xgbclassifier-predict-proba,Tabular Playground Series - Aug 2021
2853,73591490,699.0,,0,0,/aquaregis32/tps-aug-21-xgb-ctb-lgb,Tabular Playground Series - Aug 2021
2854,73574504,782.0,7.890762845963586,0,0,/shrestha90314/xgbregressor-with-normalized,Tabular Playground Series - Aug 2021
2855,70187532,781.0,,1,4,/gokulprakash/ensemble,Tabular Playground Series - Aug 2021
2856,73642119,750.0,,1,4,/olehmezhenskyi/tweedie-xgboost,Tabular Playground Series - Aug 2021
2857,70303562,792.0,,1,3,/jackmarsch/tps-08-lgbm-bayesian-optimization,Tabular Playground Series - Aug 2021
2858,73676336,774.0,7.892227868780022,0,0,/willemtraupel/xgboost-with-optuna-study-params,Tabular Playground Series - Aug 2021
2859,70208217,936.0,7.93978391916482,0,1,/prajeetguha/tabular-playground,Tabular Playground Series - Aug 2021
2860,73119967,844.0,,0,1,/abhijeet888/tabular-playground-series-aug-2021,Tabular Playground Series - Aug 2021
2861,71763338,724.0,8.025616612664665,4,12,/tuannguyenvananh/tps-aug-catboost-mlperceptron-gradientdescent,Tabular Playground Series - Aug 2021
2862,71804599,813.0,7.893581460510969,3,7,/davidjlochner/feat-eng-bayesopt-lgb,Tabular Playground Series - Aug 2021
2863,70204908,906.0,7.898255870434933,6,7,/melanie7744/tps8-pycaret-commented,Tabular Playground Series - Aug 2021
2864,73539579,876.0,,0,1,/sanjeevsahu/august-2021-catboost-7-8212-rmse,Tabular Playground Series - Aug 2021
2865,71846129,817.0,,5,17,/khkuggle/eda-modeling-for-beginners-stacking,Tabular Playground Series - Aug 2021
2866,78869007,820.0,,4,23,/aryakrishnanar/tabular-playground-series-aug-2021,Tabular Playground Series - Aug 2021
2867,71367491,865.0,7.934422079296341,5,3,/sabyasachi96/tps-aug-random-forest,Tabular Playground Series - Aug 2021
2868,73615118,880.0,7.89481386607077,1,4,/keenborder/h20-automl-and-boosting-stacking-bagging-models,Tabular Playground Series - Aug 2021
2869,71924005,802.0,7.940386974545323,2,8,/shameinew/loss-prediction-tps,Tabular Playground Series - Aug 2021
2870,71182017,887.0,,10,11,/khushishahh/eda-lgbm-catboost-xgboost,Tabular Playground Series - Aug 2021
2871,73533498,879.0,,1,3,/luisbedia/tps-aug2021-cat-lgbm,Tabular Playground Series - Aug 2021
2872,71332108,985.0,7.897216228633679,0,2,/ilyabrudno/xgboostregressor-simple-version-1,Tabular Playground Series - Aug 2021
2873,72144622,900.0,,4,9,/elemento/tabplayaugust,Tabular Playground Series - Aug 2021
2874,73575780,965.0,7.898796900199169,0,2,/dylanlau/tps-aug-xgbr-hyperparameter-tuning,Tabular Playground Series - Aug 2021
2875,73663114,946.0,,0,1,/tariqchhussain/simple-eda-xgboost-implementation-tps-aug-21,Tabular Playground Series - Aug 2021
2876,70769656,974.0,,0,1,/yadukaggle/tabular-august,Tabular Playground Series - Aug 2021
2877,69567631,927.0,7.9000756166452835,8,34,/jeongbinpark/tps-aug-h2o-automl-for-beginner,Tabular Playground Series - Aug 2021
2878,72871568,968.0,,8,10,/lonnieqin/tabular-playground-series-prediction,Tabular Playground Series - Aug 2021
2879,70658949,949.0,,0,0,/vungocbinh/tabular-playground-august-autokeras,Tabular Playground Series - Aug 2021
2880,73122988,938.0,7.902573439842022,0,1,/prathameshmane3/sales-price-prediction,Tabular Playground Series - Aug 2021
2881,73154586,1085.0,,0,1,/metselaar/betabinomialwith-inla,Tabular Playground Series - Aug 2021
2882,70757673,1095.0,,0,0,/pritampaulcrow/tabular-playground,Tabular Playground Series - Aug 2021
2883,86686976,1052.0,,2,12,/kamaljp/august-2021-eda,Tabular Playground Series - Aug 2021
2884,70037775,1089.0,7.914274114769896,2,5,/kotrying/tps-aug-tpot,Tabular Playground Series - Aug 2021
2885,72270492,1149.0,7.912091990279847,1,22,/alexeykolobyanin/tps-aug-nusvr-with-intel-extension-for-sklearn,Tabular Playground Series - Aug 2021
2886,73028716,1122.0,,0,2,/jiahong07/simple-xgboost-regression-model,Tabular Playground Series - Aug 2021
2887,72506035,1128.0,7.939897234687459,4,4,/hicham1984/tabular-ground-ply-gradientboostingregressor-pca,Tabular Playground Series - Aug 2021
2888,72506035,1128.0,7.939897234687459,4,4,/hicham1984/tabular-ground-ply-gradientboostingregressor-pca,Tabular Playground Series - Aug 2021
2889,73942761,1169.0,,0,0,/taisiyastaroverova/playground-aug-loss-prediction,Tabular Playground Series - Aug 2021
2890,73521859,1190.0,7.986385554430923,0,1,/aditya08/tps-august-cnn-baseline,Tabular Playground Series - Aug 2021
2891,72700756,1174.0,,1,2,/ztrimus/tps-aug21-features-reduction-selection,Tabular Playground Series - Aug 2021
2892,73152323,1195.0,7.925948541489418,0,0,/gman123/xgboost-regression-normalizer,Tabular Playground Series - Aug 2021
2893,73206197,1225.0,7.939855276205223,12,18,/hongpeiyi/poisson-regression-with-statsmodels,Tabular Playground Series - Aug 2021
2894,72141933,1223.0,,6,7,/ajaysamp/tab-aug-eda-models-optuna-boruta,Tabular Playground Series - Aug 2021
2895,72565169,1216.0,8.052245649506727,6,12,/jsmithperera/xgboot,Tabular Playground Series - Aug 2021
2896,73272287,1284.0,7.934962314634688,2,5,/isyedsalmanali/tps-august-2021-predicting-loss,Tabular Playground Series - Aug 2021
2897,123087431,1251.0,,0,0,/mdmustafijurrahman/tabular-playground-august-21,Tabular Playground Series - Aug 2021
2898,73461521,1276.0,,0,2,/zhiminzou/pytorch-autoquerynet-attention-tps-aug-2021,Tabular Playground Series - Aug 2021
2899,71186811,1317.0,,2,5,/hardikjain10/tabular-playground-aug-2021,Tabular Playground Series - Aug 2021
2900,69649760,1374.0,7.939272165542777,4,9,/alimohammedbakhiet/tabular-playground-series-for-beginners,Tabular Playground Series - Aug 2021
2901,73515312,1389.0,,0,6,/datajmcn/tabular-aug-eda-model,Tabular Playground Series - Aug 2021
2902,69812796,1272.0,7.9393722351828515,0,4,/yashaswy/tps-aug-tf-decision-forest-rf-baseline,Tabular Playground Series - Aug 2021
2903,71511588,1297.0,,2,6,/arenddejong/tps-08-2021-eda,Tabular Playground Series - Aug 2021
2904,72267565,1312.0,,2,5,/yamahisa/tps-aug-21-beginner-s,Tabular Playground Series - Aug 2021
2905,70103269,1315.0,,4,15,/katepod/tps-lassoreg,Tabular Playground Series - Aug 2021
2906,70728164,1324.0,,2,3,/aniketsatapathy/tabular-playground,Tabular Playground Series - Aug 2021
2907,70312465,1326.0,7.975582773503669,1,1,/jamesbond00700/tabular-aug-21-xgboost,Tabular Playground Series - Aug 2021
2908,69963870,1333.0,,0,0,/yasassandeepa/tabular-playground-series-aug-2021-yasas,Tabular Playground Series - Aug 2021
2909,69544577,1381.0,7.966692860939044,0,3,/tracyporter/aug-21-selectkbest,Tabular Playground Series - Aug 2021
2910,72356533,1393.0,7.948954564024033,4,3,/kaushalkrishna2000/tabular-playground-notebook,Tabular Playground Series - Aug 2021
2911,71483228,1398.0,7.940386974545323,0,8,/vamsikrishnab/notebook8a1f2608de,Tabular Playground Series - Aug 2021
2912,72330757,1449.0,,1,3,/panjihusnipadhila/elm-from-scratch-tps-aug-2021,Tabular Playground Series - Aug 2021
2913,71825710,1405.0,,0,1,/romanianvarev/tp-aug-2021-eda,Tabular Playground Series - Aug 2021
2914,70709692,1419.0,,0,0,/lizhangzheng/notebooke58d9464de,Tabular Playground Series - Aug 2021
2915,73011705,1270.0,7.941399863422154,1,1,/joelpeter/gradient-boost-regressor-with-7-94-accuracy,Tabular Playground Series - Aug 2021
2916,71652083,1502.0,,1,4,/liuyixi/tps-aug-tensorflow-simple-dnn,Tabular Playground Series - Aug 2021
2917,71798366,1470.0,7.952462511700386,8,20,/abhisheksisodiya/tps-aug-21-xgboost-hyperparameter-rfe,Tabular Playground Series - Aug 2021
2918,70246312,1536.0,,0,8,/jeongkyulim/r-3-models-rf-h20-catboost-under-8-0,Tabular Playground Series - Aug 2021
2919,73294303,1522.0,7.985108924382409,0,0,/sonjabutler/cnn-with-tabular-playground-dataset,Tabular Playground Series - Aug 2021
2920,71281232,1527.0,7.967256551348266,3,4,/sciffany/aug-2021-loss-tabular-playground,Tabular Playground Series - Aug 2021
2921,69846854,1523.0,7.969188627208038,0,3,/prutsaowaprut/decision-trees-just-like-kaggle-s-intro-to-ml,Tabular Playground Series - Aug 2021
2922,70408339,1524.0,8.00176728083582,2,6,/sunathra/gaussian-mixture-models,Tabular Playground Series - Aug 2021
2923,69945069,1545.0,7.977069029126071,1,1,/dennisho/tabular-playground-aug-2021-random-forest,Tabular Playground Series - Aug 2021
2924,73093165,1548.0,7.979243627774796,0,1,/derkmingfong/1st-comp-tabular-play-with-xgboost,Tabular Playground Series - Aug 2021
2925,73574921,1586.0,,1,0,/baebyunghyun/tabular-playground-series-aug-2021-dnn,Tabular Playground Series - Aug 2021
2926,70964295,1607.0,,1,6,/shub99/tps-aug-21-first,Tabular Playground Series - Aug 2021
2927,69556635,1609.0,8.009326544253158,12,14,/sunilhule/tps-aug-2021-eda-baseline,Tabular Playground Series - Aug 2021
2928,69700322,1619.0,,9,16,/roberterffmeyer/glms-zero-inflated-negative-binomial-regression,Tabular Playground Series - Aug 2021
2929,73025798,1661.0,8.299190708306206,0,0,/samduffield/tps-aug-2021-haiku-optax,Tabular Playground Series - Aug 2021
2930,73329670,1663.0,,0,1,/abhijitsontakey/notebookb0d2fa3e02,Tabular Playground Series - Aug 2021
2931,71247380,1669.0,8.378011494382138,17,34,/josetorrado/rookie-smarts-a-beginner-s-perspective,Tabular Playground Series - Aug 2021
2932,73012755,1700.0,,0,3,/aravind2608/tabular-playground,Tabular Playground Series - Aug 2021
2933,69722664,1720.0,,1,18,/mohamedbakrey/eda-for-tps-aug2021-and-visualized-and-make-prd,Tabular Playground Series - Aug 2021
2934,70330270,1726.0,,0,1,/nanosoft/tps-aug-simple-visualization,Tabular Playground Series - Aug 2021
2935,69561431,1748.0,,1,6,/hideeplearner/random-forest-for-regression-competition,Tabular Playground Series - Aug 2021
2936,76418482,1.0,,0,11,/joaopmpeinado/1st-place-lightgbm-0-7007-private,Porto Seguro Data Challenge
2937,76086254,3.0,,6,40,/gomes555/porto-seguro-r-an-lise-explorat-ria-dos-dados,Porto Seguro Data Challenge
2938,74466512,11.0,,0,8,/rapela/porto-seguro-data-challenge-nn-tensorflow,Porto Seguro Data Challenge
2939,83544049,6.0,,14,36,/jonaspalucibarbosa/porto-seguro-xgboost-10seeds-avg-6th-place,Porto Seguro Data Challenge
2940,158237386,20.0,,3,18,/gabrieltardochi/xgboost-tree-based-optimization-lr-decay,Porto Seguro Data Challenge
2941,76619315,85.0,,3,8,/felipefiorini/lgbm-baseline,Porto Seguro Data Challenge
2942,73462391,73.0,,0,0,/denychaen/simple-full-starter,Porto Seguro Data Challenge
2943,94493328,123.0,,0,0,/brunovpm/porto-seguro-challenge,Porto Seguro Data Challenge
2944,76416710,132.0,,0,7,/mcarujo/porto-seguro-data-challenge,Porto Seguro Data Challenge
2945,70163058,140.0,0.6140910408814149,4,14,/leomauro/classifica-o-porto-seguro-data-challenge,Porto Seguro Data Challenge
2946,70163058,140.0,0.3512598721323806,4,14,/leomauro/classifica-o-porto-seguro-data-challenge,Porto Seguro Data Challenge
2947,82488223,5.0,,0,1,/ironbar/select-agents-for-downloading-matches,Lux AI
2948,82808816,6.0,,3,18,/zaharch/bradley-terry-rating-system-for-kaggle-sim-comps,Lux AI
2949,76459935,44.0,,25,127,/robga/simulations-episode-scraper-match-downloader,Lux AI
2950,75978021,98.0,,3,10,/takemi/lux-ai-season-1-jupyter-notebook-quickstart,Lux AI
2951,73142958,101.0,,7,17,/horohoro/simple-visualization-of-each-item,Lux AI
2952,89521549,321.0,,5,14,/maulberto3/luxai-a-simple-rl-approach,Lux AI
2953,76398115,399.0,,1,4,/wavefunctioncollapse/inspecting-maps-for-lux-ai,Lux AI
2954,74746621,438.0,,25,97,/aithammadiabdellatif/lux-ai-reinforcement-learning,Lux AI
2955,73050236,547.0,593.9317893976984,9,91,/ilialar/lux-ai-risk-averse-baseline,Lux AI
2956,72252339,561.0,611.5077082888274,0,12,/victorsullivan/lux-ai,Lux AI
2957,73199608,600.0,,2,20,/nathankang/lux-ai-demo-helper-functions,Lux AI
2958,74060241,631.0,348.2359308729193,25,142,/stonet2000/lux-ai-season-1-jupyter-notebook-tutorial,Lux AI
2959,74060241,631.0,346.65483831083515,25,142,/stonet2000/lux-ai-season-1-jupyter-notebook-tutorial,Lux AI
2960,81316754,646.0,,0,6,/yuko1658/lux-ai-random-move,Lux AI
2961,73617301,744.0,,2,11,/jnesbit6/pytorch-deep-q-learning-train,Lux AI
2962,75137150,765.0,,2,7,/konstantinklepikov/resource-distribution,Lux AI
2963,73552068,872.0,197.790277052338,1,9,/durbin164/keras-lux-ai-reinforcement-learning,Lux AI
2964,78762211,940.0,356.1530033427984,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2965,78762211,940.0,344.2577411267949,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2966,78762211,940.0,338.0691990551155,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2967,78762211,940.0,347.28021049784826,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2968,78762211,940.0,345.3859968036899,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2969,78762211,940.0,346.8881470267338,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2970,78762211,940.0,352.139862376479,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2971,78762211,940.0,348.64860949374605,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2972,78762211,940.0,352.7052414062502,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2973,78762211,940.0,347.15738074116524,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2974,78762211,940.0,350.3548292205574,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2975,78762211,940.0,346.24604093793016,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2976,78762211,940.0,330.96443512215694,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2977,78762211,940.0,355.0973890763709,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2978,78762211,940.0,338.6538849249986,1,7,/gopalkk1/notebookcdf4fc8f42,Lux AI
2979,74474196,1018.0,,2,4,/ruizjme/lux-ai-random-agent,Lux AI
2980,81507665,1031.0,354.6843268901742,2,3,/saraswatitiwari/lux-artificial-intelligence,Lux AI
2981,75994450,1040.0,122.30421021563706,0,9,/thalesgaluchi/lux-ai-first-approach,Lux AI
2982,75729508,12.0,,0,0,/ryotayoshinobu/submission-from-editor,NFL Health & Safety - Helmet Assignment
2983,71428456,14.0,,1,16,/bamps53/create-image-dataset,NFL Health & Safety - Helmet Assignment
2984,76883894,22.0,,0,11,/ptran1203/fairmot-train,NFL Health & Safety - Helmet Assignment
2985,72801168,25.0,,13,31,/coldfir3/eda-helmet-keypoint-tracking-data-comparison,NFL Health & Safety - Helmet Assignment
2986,77525492,55.0,,0,0,/duythanhng/yolov5-v6-0-helmet-detection,NFL Health & Safety - Helmet Assignment
2987,72935914,40.0,,6,22,/jinssaa/sideline-perspective-transformation-homography,NFL Health & Safety - Helmet Assignment
2988,77485789,64.0,,0,3,/alvinai9603/extract-jersey-colour-for-team-clustering,NFL Health & Safety - Helmet Assignment
2989,73526163,58.0,0.2489084485044529,5,20,/columbia2131/speed-up-simple-helmet-mapping-nfl,NFL Health & Safety - Helmet Assignment
2990,75109359,418.0,,11,77,/jianghanhan/tuning-deepsort-helmet-mapping-high-score,NFL Health & Safety - Helmet Assignment
2991,77560407,122.0,0.5848425319829794,0,14,/adityasharma01/aditya-s-submission-in-tuning,NFL Health & Safety - Helmet Assignment
2992,78441257,374.0,0.6280186865286232,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
2993,78441257,374.0,0.6229027981202407,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
2994,78441257,374.0,0.6185157676262139,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
2995,78441257,374.0,0.614212035179542,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
2996,78441257,374.0,0.6270885249998265,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
2997,78441257,374.0,0.6223544193084873,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
2998,78441257,374.0,0.6160792997410819,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
2999,78441257,374.0,0.6154337398740811,3,20,/zhuwanglju/tuning-deepsort-helmet-mapping-lucky,NFL Health & Safety - Helmet Assignment
3000,73524615,224.0,0.5315178986679254,8,38,/syerwin/update-helper-code-helmet-mapping-deepsort,NFL Health & Safety - Helmet Assignment
3001,78070785,453.0,,6,3,/zhangkaiyu/test-baseline-helmets-csv-autogenerated-deepsort,NFL Health & Safety - Helmet Assignment
3002,77831619,543.0,,0,0,/nvk777/how-to-use-detectron2,NFL Health & Safety - Helmet Assignment
3003,71161506,337.0,,7,45,/frlemarchand/helmet-detection-using-maskrcnn-w-o-downscaling,NFL Health & Safety - Helmet Assignment
3004,77572444,223.0,0.6259362353447498,0,0,/yuqiangfeng96/tuning-deepsort-helmet-mapping,NFL Health & Safety - Helmet Assignment
3005,73533787,461.0,0.5784979973761115,1,7,/pvtien96/helper-code-helmet-mapping-deepsort,NFL Health & Safety - Helmet Assignment
3006,74560801,520.0,0.6108037567419357,22,88,/firefliesqn/tuning-deepsort-helmet-mapping,NFL Health & Safety - Helmet Assignment
3007,73695603,513.0,0.6267345082985679,0,2,/finlay/tuning-deepsort-helmet-mapping,NFL Health & Safety - Helmet Assignment
3008,75999113,489.0,0.6143578067624131,1,3,/kumudsingh9/nfl-health-and-safety-helmet,NFL Health & Safety - Helmet Assignment
3009,78443826,494.0,0.6223127702848099,0,27,/parikshitsharma2001/tuning-deepsort-helmet-mapping-high-score,NFL Health & Safety - Helmet Assignment
3010,75253599,362.0,0.6186060071775151,0,4,/youchenyue/nfl-nature,NFL Health & Safety - Helmet Assignment
3011,74633367,381.0,0.6179118567828906,0,8,/sardiirfansyah/tuning-deepsort-helmet-mapping,NFL Health & Safety - Helmet Assignment
3012,74848323,766.0,,3,5,/riadalmadani/cnn-lstm-for-nfl,NFL Health & Safety - Helmet Assignment
3013,72349856,660.0,0.3527533475402781,0,7,/victorsullivan/nfl-health-safety-helmet-assignment,NFL Health & Safety - Helmet Assignment
3014,72267959,783.0,,0,3,/akshatgupta2810/notebook11c927a5d8,NFL Health & Safety - Helmet Assignment
3015,72719642,784.0,,2,7,/ashutosh7/demystifying-nfl-data-eda,NFL Health & Safety - Helmet Assignment
3016,73322165,820.0,,3,6,/fletchersarip/nfl-helmet-assignment-extract-all-video-frames,NFL Health & Safety - Helmet Assignment
3017,104345350,12.0,0.2148096123467612,4,56,/wowfattie/delg-global-baseline,Google Landmark Retrieval 2021
3018,76171131,13.0,,0,15,/prateekagnihotri/curricularface-and-gradient-accumulation,Google Landmark Retrieval 2021
3019,73631579,18.0,,3,13,/deepkim/fold3-eda-landmark-retrieval-eda-stratify,Google Landmark Retrieval 2021
3020,73569622,36.0,,10,88,/hidehisaarai1213/glret21-efficientnetb0-baseline-training,Google Landmark Retrieval 2021
3021,76151167,52.0,0.3330831751024303,0,3,/fgtohru/glret21-efficientnet-m-baseline-inference,Google Landmark Retrieval 2021
3022,76010233,72.0,0.3194005377125184,0,1,/takahiroyoshida012/glret21-efficientnetb7-inference,Google Landmark Retrieval 2021
3023,144324293,65.0,,2,26,/sayantankirtaniya/efficientnet-inference-fork,Google Landmark Retrieval 2021
3024,75984403,79.0,0.2489025945488429,0,1,/phillipalan/glret21-efficientnetb7-baseline-inference-fa0788,Google Landmark Retrieval 2021
3025,74146258,75.0,,11,71,/debarshichanda/pytorch-w-b-glret-2021,Google Landmark Retrieval 2021
3026,72620282,234.0,,1,6,/ronigur/landmark-retrieval-random-basline,Google Landmark Retrieval 2021
3027,72284211,6.0,0.2024589941119316,2,18,/narsil/host-baseline-2020,Google Landmark Recognition 2021
3028,72254522,13.0,,4,13,/hdsk38/pytorch-starter-train-efficientnet,Google Landmark Recognition 2021
3029,75523528,19.0,0.2427919752281456,11,46,/takedarts/inference-and-submission-pytorch-resnet34,Google Landmark Recognition 2021
3030,72629668,42.0,,1,21,/enric1296/model-starter-tensorflow-gem-pool-mixedprec,Google Landmark Recognition 2021
3031,73052225,55.0,,0,1,/lilinchen/lanmark-inference-test,Google Landmark Recognition 2021
3032,72902722,84.0,,0,15,/markwijkhuizen/google-landmark-recognition-2021-tfrecords-res-384,Google Landmark Recognition 2021
3033,74469642,89.0,,1,6,/tensorchoko/google-landmark-recognition-2021-eda,Google Landmark Recognition 2021
3034,109416140,126.0,,0,3,/borderb/landmark-recognition-v3,Google Landmark Recognition 2021
3035,75278835,141.0,0.2228169017430285,1,27,/parikshitsharma2001/base-glr-2021-to-submit,Google Landmark Recognition 2021
3036,103684047,91.0,,0,2,/motono0223/guie-generate-tfrecord-glr2021-512pix-mini7k,Google Landmark Recognition 2021
3037,72390842,257.0,0.0041720122897919,0,3,/victorsullivan/google-landmark-recognition,Google Landmark Recognition 2021
3038,74599767,265.0,,1,4,/aryannath/glr-2021-using-fast-ai-for-beginners,Google Landmark Recognition 2021
3039,73650091,269.0,0.2183142531936273,2,6,/nishanthaddagatla/base-glr-2021-to-submit,Google Landmark Recognition 2021
3040,74178010,292.0,,0,1,/nizado/google-landmark-recognition,Google Landmark Recognition 2021
3041,75587876,340.0,,0,3,/nameytg/train-inference-glr-based-on-pytorch,Google Landmark Recognition 2021
3042,73447133,347.0,,0,2,/mayur7garg/glr-2021-basic-eda,Google Landmark Recognition 2021
3043,73731331,355.0,2.179866864871301e-06,2,3,/wzhwoody/simplified-resnet-image-augmentation,Google Landmark Recognition 2021
3044,73346066,359.0,,6,33,/drcapa/landmark-recognition-2021-starter,Google Landmark Recognition 2021
3045,71288616,360.0,0.0,12,41,/mrigendraagrawal/glr-eda-and-starter,Google Landmark Recognition 2021
3046,71794934,363.0,,6,14,/datafool/pytorch-starter,Google Landmark Recognition 2021
3047,71874350,366.0,,0,2,/ysprakash/glr-2021-starter-using-fastai,Google Landmark Recognition 2021
3048,76139313,358.0,0.0,0,6,/stpeteishii/landmark-recognition-conv2d,Google Landmark Recognition 2021
3049,74347995,2.0,,0,0,/tkm2261/exp33,chaii - Hindi and Tamil Question Answering
3050,71505522,1.0,0.7286850810050964,31,193,/thedrcat/chaii-eda-baseline,chaii - Hindi and Tamil Question Answering
3051,78446522,16.0,,0,1,/jdoesv/custom-ensemble-outputs,chaii - Hindi and Tamil Question Answering
3052,82264446,6.0,,0,0,/chamecall/chaiiqa-sampling,chaii - Hindi and Tamil Question Answering
3053,71457936,5.0,0.7231242060661316,8,54,/abhishek/chaii-chaii,chaii - Hindi and Tamil Question Answering
3054,75151922,4.0,,0,1,/zacchaeus/chaii-tfds-wiki,chaii - Hindi and Tamil Question Answering
3055,79511592,25.0,,7,9,/ajax0564/know-your-train-jaccard,chaii - Hindi and Tamil Question Answering
3056,79887780,3.0,,4,3,/nguyenduongthanh/chaii-qa-10-folds-of-muril-large,chaii - Hindi and Tamil Question Answering
3057,79090090,21.0,,3,23,/forcewithme/blend-of-different-seed,chaii - Hindi and Tamil Question Answering
3058,79169029,214.0,0.7447890639305115,0,0,/handudu/muriltuiduan,chaii - Hindi and Tamil Question Answering
3059,75335547,711.0,,1,4,/saiyanwarrior/beginner-friendly-custom-pipeline-train,chaii - Hindi and Tamil Question Answering
3060,79403439,18.0,0.004369300790131,0,0,/guchio3/fill-sub-by-train,chaii - Hindi and Tamil Question Answering
3061,81178894,302.0,0.6933368444442749,0,1,/tuozhenliu/chaii-qa-v2-infer,chaii - Hindi and Tamil Question Answering
3062,73767794,329.0,,0,1,/wicharnrueangkhajorn/pluem-chaii-1-starter-notebook,chaii - Hindi and Tamil Question Answering
3063,75456493,316.0,0.7694052457809448,2,6,/adityasharma01/post-processing-by-aditya,chaii - Hindi and Tamil Question Answering
3064,71933504,22.0,,3,7,/watzisname/comprehensive-eda-chaii-hindi-tamil-qa,chaii - Hindi and Tamil Question Answering
3065,74383592,216.0,0.7729748487472534,5,16,/mihtw1/chaii-with-postprocess,chaii - Hindi and Tamil Question Answering
3066,80040572,358.0,,4,16,/adldotori/notebook-to-read-before-start-nlp-step-0,chaii - Hindi and Tamil Question Answering
3067,75447693,310.0,0.7332939505577087,0,8,/starkking07/just-exploring-eda-xlm-baseline,chaii - Hindi and Tamil Question Answering
3068,95780054,252.0,,2,34,/lunapandachan/chaii-eda-baseline,chaii - Hindi and Tamil Question Answering
3069,73893793,389.0,0.7279342412948608,0,2,/rickykonwar/chaii-qna-transformers-xlmroberta,chaii - Hindi and Tamil Question Answering
3070,71348566,312.0,,6,30,/au1206/chaii-starterkit-eda-baseline,chaii - Hindi and Tamil Question Answering
3071,77858944,400.0,0.7723886966705322,0,0,/riow1983/reproduction-of-0-792-notebook,chaii - Hindi and Tamil Question Answering
3072,79251644,111.0,,2,7,/khankamranali/chaii-qa-simple-bert-tensorflow,chaii - Hindi and Tamil Question Answering
3073,72526892,297.0,,9,15,/doanquanvietnamca/better-loss-functions,chaii - Hindi and Tamil Question Answering
3074,74738696,217.0,0.7526925206184387,1,11,/harshwalia/chaii-easy-explanation-of-highest-voted-code-0-752,chaii - Hindi and Tamil Question Answering
3075,72087731,465.0,,4,16,/kritidoneria/chaii-hindi-wordclouds,chaii - Hindi and Tamil Question Answering
3076,77075993,466.0,0.3159683048725128,1,0,/kobebeanbryant/chaii-1-inference,chaii - Hindi and Tamil Question Answering
3077,79663428,193.0,0.7747551798820496,0,3,/vineethakkinapalli/chaii-abhishek-8-models,chaii - Hindi and Tamil Question Answering
3078,78039989,506.0,0.7927004098892212,0,3,/pranithchowdary/google-chaii-v2,chaii - Hindi and Tamil Question Answering
3079,79702013,519.0,0.0102436551824212,0,2,/houssemayed/q-a-xlm-model-fine-tunning-with-trainer-api,chaii - Hindi and Tamil Question Answering
3080,78253888,536.0,0.7927004098892212,21,57,/jillanisofttech/chaii-pe-lo-g-with-acc-0-792,chaii - Hindi and Tamil Question Answering
3081,71371901,47.0,0.4220139682292938,8,40,/heyytanay/chaii-understanding-the-comp-eda-baseline,chaii - Hindi and Tamil Question Answering
3082,78089342,200.0,0.7167447209358215,0,0,/dhanyasabari/muril-infer,chaii - Hindi and Tamil Question Answering
3083,71742439,79.0,,2,9,/towhidultonmoy/chaii-eda-multilingual-pretrained-baseline,chaii - Hindi and Tamil Question Answering
3084,71742439,79.0,,2,9,/towhidultonmoy/chaii-eda-multilingual-pretrained-baseline,chaii - Hindi and Tamil Question Answering
3085,75684955,175.0,,0,8,/vivmankar/simple-eda,chaii - Hindi and Tamil Question Answering
3086,77301324,695.0,,4,16,/maunish/chaii-pytorch-train-xlmroberta-large,chaii - Hindi and Tamil Question Answering
3087,79035067,680.0,0.7653695940971375,0,0,/sarwarbeing/chaii-hindi-tamil-inference-validation,chaii - Hindi and Tamil Question Answering
3088,72771158,78.0,,16,37,/adityaecdrid/translate-them-to-tamil-language-external-data,chaii - Hindi and Tamil Question Answering
3089,74199936,82.0,0.7713537812232971,0,5,/swaana/hello-friends-chaii-pi-lo,chaii - Hindi and Tamil Question Answering
3090,72263540,102.0,0.7499143481254578,0,3,/victorsullivan/chaii,chaii - Hindi and Tamil Question Answering
3091,79055336,124.0,0.7713537812232971,0,0,/ashwins19blc1169/data-analytics-project,chaii - Hindi and Tamil Question Answering
3092,73353380,190.0,0.6380010843276978,0,1,/shaktisd/chaii-eda-baseline,chaii - Hindi and Tamil Question Answering
3093,72677869,65.0,,2,8,/vigneshwarann/eda-tokenizers,chaii - Hindi and Tamil Question Answering
3094,73119647,220.0,,1,8,/alessiopeluso/chaii-transformers,chaii - Hindi and Tamil Question Answering
3095,74946049,231.0,,5,29,/firefliesqn/chaiii-qa-starter,chaii - Hindi and Tamil Question Answering
3096,79597352,736.0,0.7298523187637329,0,0,/shreyasumbetla/buscuit-badshah-train,chaii - Hindi and Tamil Question Answering
3097,72419011,650.0,0.7517038583755493,14,110,/rhtsingh/chaii-qa-5-fold-xlmroberta-torch-infer,chaii - Hindi and Tamil Question Answering
3098,72439231,637.0,,2,9,/oleksandrsirenko/chaii-fine-tuning-model,chaii - Hindi and Tamil Question Answering
3099,79678765,776.0,0.7366722822189331,0,0,/ruhong/chaii,chaii - Hindi and Tamil Question Answering
3100,79187267,678.0,,0,2,/sharpshim/chaii-xlm-r-single-model-train-pytorch,chaii - Hindi and Tamil Question Answering
3101,71465213,777.0,,2,3,/msafi04/tamil-and-hindi-qa-wip,chaii - Hindi and Tamil Question Answering
3102,71685977,760.0,,1,6,/bhavikardeshna/chaii-eda-baseline,chaii - Hindi and Tamil Question Answering
3103,72541805,797.0,,2,10,/durbin164/chaii-baseline-training,chaii - Hindi and Tamil Question Answering
3104,76766449,751.0,0.7300556302070618,0,6,/dormantscientist/baseline-model-chaii-0-73,chaii - Hindi and Tamil Question Answering
3105,72202791,804.0,0.7286850810050964,0,7,/yogeshkulkarni/chai-qna-huggingface-transformers,chaii - Hindi and Tamil Question Answering
3106,75386781,817.0,0.7286850810050964,5,30,/theamitnikhade/question-answering-starter-roberta,chaii - Hindi and Tamil Question Answering
3107,72232835,843.0,,2,16,/vaibhavrmankar/simple-start-eda-submission,chaii - Hindi and Tamil Question Answering
3108,74193447,841.0,,13,26,/esratmaria/chaii-question-answering-xlmroberta-large,chaii - Hindi and Tamil Question Answering
3109,73649561,835.0,0.6867704391479492,11,23,/rizdelhi/chaii-hindi-tamil-queans,chaii - Hindi and Tamil Question Answering
3110,79169236,874.0,0.6343744397163391,0,0,/jagadeesh6226/notebook95ff40c627,chaii - Hindi and Tamil Question Answering
3111,72293941,873.0,0.1289589405059814,2,9,/vrindaprabhu/chaii-with-keras,chaii - Hindi and Tamil Question Answering
3112,78306897,891.0,,0,5,/layyer/use-huggingface-transformers-pretrained-qa,chaii - Hindi and Tamil Question Answering
3113,79867304,890.0,0.5712791681289673,0,5,/haozhang607/chaii-hindi-and-tamil-question-answering,chaii - Hindi and Tamil Question Answering
3114,79583256,906.0,,0,0,/sagardollin/parlegpt-train,chaii - Hindi and Tamil Question Answering
3115,72574419,920.0,0.1175047531723976,2,6,/aninda/keras-chaii,chaii - Hindi and Tamil Question Answering
3116,71255883,921.0,0.067774198949337,2,5,/opanichev/baseline-answering-with-numbers,chaii - Hindi and Tamil Question Answering
3117,76635456,926.0,,0,0,/gabrieldhofer/hindi-and-tamil-question-answering,chaii - Hindi and Tamil Question Answering
3118,73830971,2.0,,0,14,/aayush9753/datasetcreation,Beyond Analysis
3119,73883590,14.0,66.29395075137764,1,2,/farji402/ba-baseline,Beyond Analysis
3120,73883590,14.0,66.57748570950439,1,2,/farji402/ba-baseline,Beyond Analysis
3121,74266851,52.0,,0,3,/priyaduttbhatt/estimating-customer-value,Beyond Analysis
3122,78017560,71.0,,1,13,/gaurangthakur/beyond-analysis-1,Beyond Analysis
3123,73652380,54.0,68.96469074905424,1,4,/atiknageshwar/beyond-analysis-yb-copy2,Beyond Analysis
3124,78581207,73.0,,1,10,/nidhi1502/beyond-analysis,Beyond Analysis
3125,73530853,116.0,90.96036295006712,0,1,/rohandaniel/beyond-analysis-rd,Beyond Analysis
3126,73977411,135.0,79.48960775273595,0,0,/gowrishankarp/deepneuralnetwork-multitasking,Beyond Analysis
3127,75264155,14.0,0.8180208575676028,1,6,/martynovandrey/tps-september-lgbm,Tabular Playground Series - Sep 2021
3128,74299980,78.0,,0,2,/ivankontic/004-1o-sketchup1-and-ann-dataset,Tabular Playground Series - Sep 2021
3129,74150528,17.0,,1,2,/lilkaskitc/tps-sep-2021-kmeans-gmm-features-extraction,Tabular Playground Series - Sep 2021
3130,75072048,88.0,0.8081701135193836,2,7,/omarvivas/torch-tps-sep2021,Tabular Playground Series - Sep 2021
3131,74213843,63.0,0.818179598070659,22,30,/somayyehgholami/1-tps-sep-21-autogluon-missing-values,Tabular Playground Series - Sep 2021
3132,74213843,63.0,0.8164733123725753,22,30,/somayyehgholami/1-tps-sep-21-autogluon-missing-values,Tabular Playground Series - Sep 2021
3133,91182150,20.0,,2,9,/edrickkesuma/eda-cleaning-baseline-classifiers,Tabular Playground Series - Sep 2021
3134,73994815,39.0,0.8180852440266637,12,26,/yus002/random-weights-blending-tool-tps-sep-2021,Tabular Playground Series - Sep 2021
3135,76023520,28.0,0.8184293124924142,0,0,/woodiedudy/just-boost,Tabular Playground Series - Sep 2021
3136,74126460,59.0,,18,36,/mhslearner/simple-eda-h2oautoml,Tabular Playground Series - Sep 2021
3137,73965986,61.0,0.8158533559630216,1,6,/munumbutt/automl-autogluon,Tabular Playground Series - Sep 2021
3138,76004485,54.0,,0,3,/ayoubberdeddouch/tps-sep21-aberd,Tabular Playground Series - Sep 2021
3139,73688139,124.0,0.7908528491814929,1,3,/smiles28/tps-september-lgbm,Tabular Playground Series - Sep 2021
3140,76143410,103.0,,22,26,/bakar31/tps-sept-baseline,Tabular Playground Series - Sep 2021
3141,74310933,13.0,0.8179443064902315,1,10,/javiervallejos/tps-sep-21-lightgbm-tuned,Tabular Playground Series - Sep 2021
3142,73702535,25.0,,0,2,/realtimshady/quick-eda-autoviz,Tabular Playground Series - Sep 2021
3143,73937976,223.0,,7,14,/snikhil17/stratified-kfolds,Tabular Playground Series - Sep 2021
3144,73712651,90.0,,1,8,/saiabhitejachepuri/tps-sep-eda,Tabular Playground Series - Sep 2021
3145,76046557,118.0,,0,3,/wumingyang/0-81793-0-81825-by-greedyensemble,Tabular Playground Series - Sep 2021
3146,73899591,110.0,,2,9,/data2science/tps-sept21-xgb-cat-baseline-median-impute,Tabular Playground Series - Sep 2021
3147,75055661,163.0,,1,13,/hrshuvo/stack,Tabular Playground Series - Sep 2021
3148,75082039,175.0,,2,6,/shahedislam/blend-gdc,Tabular Playground Series - Sep 2021
3149,74197925,172.0,0.8147696988350996,2,13,/paddykb/tps-09-additive-baseline,Tabular Playground Series - Sep 2021
3150,73940928,184.0,0.8180913580016795,0,3,/mohitsahal/random-weights-blending-tool-tps-sep-2021,Tabular Playground Series - Sep 2021
3151,73691951,185.0,,0,13,/mlanhenke/tps-09-spot-check-xgb-lgbm-catb-gpu,Tabular Playground Series - Sep 2021
3152,94925481,153.0,,19,55,/devsubhash/tps-lightautoml-h2o,Tabular Playground Series - Sep 2021
3153,73762862,209.0,0.8015057002476795,7,18,/hamzaghanmi/tps-sep-starter-eda-xgboost,Tabular Playground Series - Sep 2021
3154,74081351,157.0,,0,13,/kalilurrahman/kaggle-sep2021-tabular-playground-eda,Tabular Playground Series - Sep 2021
3155,74852218,215.0,0.816988639668268,5,9,/kavehshahhosseini/tps-sep-2021-blending-xgboost-catboost,Tabular Playground Series - Sep 2021
3156,74460827,141.0,0.8161264988326069,0,1,/umairalam/tabular-playground-with-catboost,Tabular Playground Series - Sep 2021
3157,73918396,219.0,0.7823474521274022,0,2,/shivamkc3/tabular-series-using-automl-pycaret,Tabular Playground Series - Sep 2021
3158,73894617,220.0,0.817821676931584,36,60,/junhyeok99/stacking-ensemble-for-beginner,Tabular Playground Series - Sep 2021
3159,75432862,196.0,0.8128801946499248,0,11,/khankamranali/simple-keras-hyperparameter-early-stop,Tabular Playground Series - Sep 2021
3160,74458285,145.0,0.8089414669637782,3,7,/aayush26/tps-sep-2021-autogluon-101,Tabular Playground Series - Sep 2021
3161,75340645,178.0,,5,17,/bserdogan/tps-09-21-eda-basics,Tabular Playground Series - Sep 2021
3162,76066862,131.0,0.8184436672567047,1,13,/vamsikrishnab/tps-sep-ann,Tabular Playground Series - Sep 2021
3163,73792678,132.0,,0,7,/oddasparagus11/baseline-catboost-model-0-79545-tps-sept,Tabular Playground Series - Sep 2021
3164,76349952,200.0,0.8179022396263421,0,4,/sergeyzemskov/tps-21-09-stacking-ensemble-lgbm-catboost-xgboost,Tabular Playground Series - Sep 2021
3165,75511408,161.0,0.7981244417336147,1,4,/ashokkumarpalivela/tps-sep21,Tabular Playground Series - Sep 2021
3166,73782954,322.0,0.7129086752534971,3,10,/mohammadkashifunique/hyperparameter-tuning-lgbm-optuna,Tabular Playground Series - Sep 2021
3167,75266586,173.0,,3,8,/pavan9065/tps-h2o-automl,Tabular Playground Series - Sep 2021
3168,75386912,98.0,0.8163384638982484,6,10,/jonigooner/histgradient-classifier-optuna,Tabular Playground Series - Sep 2021
3169,75905850,229.0,0.8180389198840132,0,2,/mdzisun/staking-xgb-lgbm-catboost,Tabular Playground Series - Sep 2021
3170,74009780,234.0,,4,8,/arnabbiswas1/reference-doc-for-individual-columns,Tabular Playground Series - Sep 2021
3171,75895323,330.0,,0,9,/akmeghdad/tps-0921-essential,Tabular Playground Series - Sep 2021
3172,73919430,246.0,0.8102337794817412,0,0,/astashiro/tps-sep2021-02lightautoml,Tabular Playground Series - Sep 2021
3173,73751196,235.0,,0,0,/guptadev26/sept-tsp-xgb-cat,Tabular Playground Series - Sep 2021
3174,76196504,251.0,,0,5,/adamwurdits/tps09-lgbm-2,Tabular Playground Series - Sep 2021
3175,74937541,299.0,,1,17,/azzamradman/single-catboost-baseline-with-simple-eda,Tabular Playground Series - Sep 2021
3176,76038311,271.0,0.8181432145443319,0,12,/eugenebee/tps-sep-2021-xgb-early-stopping-rounds,Tabular Playground Series - Sep 2021
3177,74060447,231.0,,2,9,/gauravbrills/10-folds-stratified-parquet-feather,Tabular Playground Series - Sep 2021
3178,74815659,180.0,0.8176371748364363,17,27,/rahullalu/tps-sept-2021-eda-multiple-models-blending,Tabular Playground Series - Sep 2021
3179,73823516,274.0,0.8097996719246008,21,46,/kennethquisado/xgboost-10fold-cv-blend,Tabular Playground Series - Sep 2021
3180,75175679,339.0,,0,8,/davidcoxon/exploring-engineering-blending-0-818-tpssept21,Tabular Playground Series - Sep 2021
3181,74839581,242.0,0.8182204829857678,0,3,/meherajhossain/tps-sep2021-xgb-and-hyper-parameter-tuning,Tabular Playground Series - Sep 2021
3182,75888025,255.0,,1,6,/merrickolivier/tabular-competition-stacking-with-optuna,Tabular Playground Series - Sep 2021
3183,74584564,394.0,0.798107849005157,6,44,/anandhuh/tps-september-21-simple-catboost,Tabular Playground Series - Sep 2021
3184,73816181,340.0,0.8148153153780864,10,16,/antonellomartiello/tps09-autogluon,Tabular Playground Series - Sep 2021
3185,75396359,279.0,,1,4,/priyank7/tps-efficient-data-visualization,Tabular Playground Series - Sep 2021
3186,73755401,284.0,,0,1,/nitinrajput47/eda-with-simple-approach,Tabular Playground Series - Sep 2021
3187,75021552,332.0,,22,70,/bextuychiev/write-powerful-code-w-custom-sklearn-transformers,Tabular Playground Series - Sep 2021
3188,73758025,244.0,,0,0,/sharmoul/tps-sep21-eda,Tabular Playground Series - Sep 2021
3189,74107249,469.0,0.8179645883370807,2,14,/bernhardklinger/tps-lightgbm-feature-eng,Tabular Playground Series - Sep 2021
3190,73986387,343.0,,0,5,/manthanbhagat/tps-sep-2k21-stratifiedkfold,Tabular Playground Series - Sep 2021
3191,75046504,354.0,,8,39,/shivansh002/gentle-introduction-to-gan,Tabular Playground Series - Sep 2021
3192,75346228,477.0,0.8181008884219121,3,18,/shreyaspj/tabular-playground-series-0-8181-auc,Tabular Playground Series - Sep 2021
3193,73986773,286.0,0.8091120793356319,12,77,/alexryzhkov/sep21-lightautoml-starter,Tabular Playground Series - Sep 2021
3194,74129993,290.0,,2,6,/elemento/tabplayseptember,Tabular Playground Series - Sep 2021
3195,73742938,293.0,0.6925394755269686,0,0,/lexplua/baseline-iterativeimputer-lgb,Tabular Playground Series - Sep 2021
3196,74000940,295.0,,0,8,/vaby667/filna-isolationforest-to-detect-outliers,Tabular Playground Series - Sep 2021
3197,73871597,305.0,0.8113457306493003,1,11,/takahiroyoshida012/eda-lightgbm-hyperparameter-tuning-using-optuna,Tabular Playground Series - Sep 2021
3198,75245121,349.0,0.818082565386874,0,2,/rafidameermahmud/tps-sep-stacking-xgb-lgbm,Tabular Playground Series - Sep 2021
3199,73846190,301.0,,0,0,/ratorato/tabnet-tabular-playground-series-sep-2021,Tabular Playground Series - Sep 2021
3200,75108734,459.0,0.8163335454691695,17,52,/lukaszborecki/tps-09-nn,Tabular Playground Series - Sep 2021
3201,76541858,328.0,,4,17,/raahulsaxena/tps-sept-21-introduction-to-stacking,Tabular Playground Series - Sep 2021
3202,73876818,412.0,0.8178012729840964,22,39,/maksymshkliarevskyi/tps-sep-all-for-start-eda-xgb-catboost-baseline,Tabular Playground Series - Sep 2021
3203,74440954,327.0,0.8138655436077966,11,19,/ekaterinadranitsyna/kerastuner-tf-decision-forest,Tabular Playground Series - Sep 2021
3204,75072546,352.0,,1,6,/heiswicked/smtm-s-tps-sep-2021-eda,Tabular Playground Series - Sep 2021
3205,74720926,300.0,,0,2,/hamidrezabakhtaki/xgb-uptuna-lightbm-cleancode,Tabular Playground Series - Sep 2021
3206,75947773,391.0,0.8179871206501806,0,4,/dstomcray/setembro-2021-tabular-playground-simple-approach,Tabular Playground Series - Sep 2021
3207,74012034,456.0,0.8138052543643279,12,18,/maximkazantsev/tps-09-21-eda-simple-xgboost,Tabular Playground Series - Sep 2021
3208,74383032,653.0,0.7427368842253822,1,1,/gabtex/lightgbm,Tabular Playground Series - Sep 2021
3209,74121967,381.0,0.7871435946792091,0,1,/truongdang1311/tabular-sep-2021-automl,Tabular Playground Series - Sep 2021
3210,73870631,437.0,0.8173120947538216,0,15,/hsuchialun/tps-xgboost-kfold-with-gpu,Tabular Playground Series - Sep 2021
3211,73746300,421.0,,0,1,/nghigia/notebookbd51362812,Tabular Playground Series - Sep 2021
3212,74692840,329.0,,3,7,/mustafacicek/tps-09-21-eda,Tabular Playground Series - Sep 2021
3213,73711178,432.0,,0,1,/amiteshgangrade/baseline-xgbclassifier,Tabular Playground Series - Sep 2021
3214,74334672,490.0,0.8137894734499802,1,3,/prinzitzak/tabular-playground-series-sep-2021,Tabular Playground Series - Sep 2021
3215,75365924,365.0,0.8179257944638465,1,23,/lucamassaron/autogluon-for-tabular-playground-sep-2021,Tabular Playground Series - Sep 2021
3216,75862368,484.0,0.8173726083047409,3,14,/skiller/a-z-predictive-modelling-eda-ensemble,Tabular Playground Series - Sep 2021
3217,75862368,484.0,0.8173726083047409,3,14,/skiller/a-z-predictive-modelling-eda-ensemble,Tabular Playground Series - Sep 2021
3218,73830669,345.0,0.7945836892150206,20,19,/prikshitsingla/master-the-tabular-first-baseline,Tabular Playground Series - Sep 2021
3219,75224036,415.0,,1,7,/mrsumitjha/3-layer-stacking-using-stackclassifier-of-sklearn,Tabular Playground Series - Sep 2021
3220,73682374,453.0,0.8036602421197037,1,6,/tomoyaogawam/tps-sep-lightgbm-baseline-2,Tabular Playground Series - Sep 2021
3221,74649669,395.0,0.8177625973787451,1,1,/seoltommy/gmo-submission,Tabular Playground Series - Sep 2021
3222,74243175,530.0,0.8169411135004987,3,9,/zhangcheche/tabular-sep-xgboost-optuna,Tabular Playground Series - Sep 2021
3223,73694554,344.0,,2,3,/khule28/gradient-boosting-feature-engg-roc-auc-scores,Tabular Playground Series - Sep 2021
3224,84703099,398.0,0.8147527190895959,1,5,/rsizem2/tps-09-21-simple-xgboost-model,Tabular Playground Series - Sep 2021
3225,74522233,489.0,0.8178300108020627,0,9,/keenborder/boosting-models-with-feature-engineering-optuna,Tabular Playground Series - Sep 2021
3226,74098976,463.0,,4,8,/viveksalunkhe/tabular-playground-sep-2021-lgbm-with-5-folds,Tabular Playground Series - Sep 2021
3227,74078051,898.0,0.7812103361825312,27,77,/carlmcbrideellis/classification-using-tensorflow-decision-forests,Tabular Playground Series - Sep 2021
3228,75098693,468.0,0.8170133113889662,2,5,/rahulchauhan3j/tps-sep-pseudolabeling,Tabular Playground Series - Sep 2021
3229,75098693,468.0,0.8171489090757305,2,5,/rahulchauhan3j/tps-sep-pseudolabeling,Tabular Playground Series - Sep 2021
3230,75283516,488.0,0.8170342530172918,5,8,/nancydrew/tps-sept-eda-xgboost-lgbm-catboost,Tabular Playground Series - Sep 2021
3231,74220889,423.0,,2,4,/smita09/tps-sep-worst-solution,Tabular Playground Series - Sep 2021
3232,74439060,420.0,0.8063943881479263,0,5,/nikhilsharma24/gbm-r-h2o,Tabular Playground Series - Sep 2021
3233,74053979,465.0,,4,4,/rogeriodelfim/01-tps-set-ponto-de-partida-eda-e-linha-de-base,Tabular Playground Series - Sep 2021
3234,74902314,559.0,,0,14,/jaikr18/tps-sept-eda-baseline-models-for-beginners,Tabular Playground Series - Sep 2021
3235,74449274,595.0,,2,17,/khkuggle/eda-pre-processing-with-pca-xgbclassifier,Tabular Playground Series - Sep 2021
3236,73898749,547.0,,0,10,/sgiuri/sep21tp-eda-na-handle-xgbc,Tabular Playground Series - Sep 2021
3237,74679721,528.0,,5,32,/ninjaac/xgboost-vs-logisticregression-optuna-features,Tabular Playground Series - Sep 2021
3238,74328075,555.0,0.7948381758736106,0,3,/rahul1594/tps-catboost-using-simpleimputer,Tabular Playground Series - Sep 2021
3239,73882910,563.0,0.8138799480153959,2,8,/ranjeetshrivastav/tps-sep-21-eda-lightgbm,Tabular Playground Series - Sep 2021
3240,73882910,563.0,0.8138799480153959,2,8,/ranjeetshrivastav/tps-sep-21-eda-lightgbm,Tabular Playground Series - Sep 2021
3241,103550168,568.0,,9,37,/brendanartley/sep-21-tab-series-lgbm-optuna,Tabular Playground Series - Sep 2021
3242,74398713,585.0,0.8171552885146902,0,5,/nicholasvolpe/september-tabular-challenge-rf-xgboost-catboost,Tabular Playground Series - Sep 2021
3243,76072741,573.0,,0,0,/johncenadon/september-trial-competition,Tabular Playground Series - Sep 2021
3244,74461075,630.0,,0,1,/scr0ll0/sep-2021-autogluon-feature-engineering,Tabular Playground Series - Sep 2021
3245,75558826,602.0,,0,4,/radkin17/tpsep21-xgboost,Tabular Playground Series - Sep 2021
3246,73931956,606.0,0.704218262150002,0,3,/datascientistsohail/using-xgboostclassifier-without-cv,Tabular Playground Series - Sep 2021
3247,76352918,600.0,,0,8,/m1y7k8/tabular-sep-21-23,Tabular Playground Series - Sep 2021
3248,75684823,614.0,,11,13,/melanie7744/tps9-eda-comparison-train-test-set,Tabular Playground Series - Sep 2021
3249,115162491,620.0,0.8152069383009917,35,46,/lonnieqin/catboost-tabular-playground-prediction-sep-2021,Tabular Playground Series - Sep 2021
3250,74853191,650.0,0.8155710675913596,0,2,/rajarpatra/simple-feature-addition-with-catboost,Tabular Playground Series - Sep 2021
3251,76028278,631.0,0.814702633827505,0,0,/jay9171/tps-sep-pycaret,Tabular Playground Series - Sep 2021
3252,74570035,668.0,0.8166729409847031,3,9,/ted0071/tps-sep-2021,Tabular Playground Series - Sep 2021
3253,75218802,707.0,0.8165648711515072,2,7,/cascadinglight/tps-sep-pytorch-mlp-trainer,Tabular Playground Series - Sep 2021
3254,73829418,672.0,0.5845978307539988,2,7,/datajmcn/classification-using-tensorflow-randomforest,Tabular Playground Series - Sep 2021
3255,75808291,621.0,0.8164818656226764,5,15,/akihironomura/tps-xgboost-kfold,Tabular Playground Series - Sep 2021
3256,76024696,635.0,0.8164444346590345,4,4,/squarex/tps-092021-modelling,Tabular Playground Series - Sep 2021
3257,76024696,635.0,0.8162428811823583,4,4,/squarex/tps-092021-modelling,Tabular Playground Series - Sep 2021
3258,76024696,635.0,0.8161824835266637,4,4,/squarex/tps-092021-modelling,Tabular Playground Series - Sep 2021
3259,75232939,657.0,0.8162903754104986,3,7,/satoshiss/tabular-playground-september,Tabular Playground Series - Sep 2021
3260,75811060,662.0,0.8162485478200576,0,6,/seungtaekim/tabular-playground-series-september,Tabular Playground Series - Sep 2021
3261,75151380,622.0,0.8119351668270841,1,1,/pradeepchandrasuyal/outlier-handling-lgbm-without-hyprparameter-tuning,Tabular Playground Series - Sep 2021
3262,74305651,648.0,0.8160686114492299,0,4,/christoforum/lightgbm-optuna-tps-sep-2021,Tabular Playground Series - Sep 2021
3263,75453463,696.0,,11,19,/suharkov/09-2021-pg-comparison-of-different-averagings,Tabular Playground Series - Sep 2021
3264,76064424,718.0,0.7983933127234659,1,11,/rahiegadekar/a-beginners-approach-intel-extension-and-lightgbm,Tabular Playground Series - Sep 2021
3265,74671156,709.0,0.8135018477838206,0,5,/docxian/tabular-playground-9-gradient-boosting-starter,Tabular Playground Series - Sep 2021
3266,74957864,764.0,,0,2,/nakamurasyuta/diff-scaller,Tabular Playground Series - Sep 2021
3267,74916759,749.0,,10,7,/shenurisumanasekara/xgbclasssifier-step-by-step,Tabular Playground Series - Sep 2021
3268,75468287,739.0,,4,8,/ninamaamary/tabnet-approach-semi-supervised-tps-09,Tabular Playground Series - Sep 2021
3269,73989486,734.0,,5,8,/edwardjiwookkim/eda-tps-sep-2021,Tabular Playground Series - Sep 2021
3270,75948654,728.0,0.8153465621148601,1,1,/emelda2021/0929-catboost-max-min,Tabular Playground Series - Sep 2021
3271,74479228,725.0,0.8153140854439374,1,9,/mithun162001/september-playground-series,Tabular Playground Series - Sep 2021
3272,75332577,731.0,,0,2,/moraeslucas/tps-set-6,Tabular Playground Series - Sep 2021
3273,78390713,742.0,,0,2,/oraware/denoising-autoencoder-sep-2021,Tabular Playground Series - Sep 2021
3274,74091239,759.0,,1,4,/bosnomer/tps-sept-eda,Tabular Playground Series - Sep 2021
3275,74399011,758.0,0.8017763009965745,3,9,/pratikkgandhi/histgradientboostingclf-baseline,Tabular Playground Series - Sep 2021
3276,76958267,768.0,,0,6,/nesterenkomarina/tps-sep-deep-net-tensorflow-train-tpu,Tabular Playground Series - Sep 2021
3277,76194194,773.0,,0,2,/fadibadine/classification-using-tensorflow-decision-forests,Tabular Playground Series - Sep 2021
3278,75691163,783.0,0.8143126852712014,0,6,/mhdi1380/tsp-xgboost,Tabular Playground Series - Sep 2021
3279,75689752,784.0,0.7822444289380811,0,2,/dhruvbajaj01/getting-started-september-2021-tabular-playground,Tabular Playground Series - Sep 2021
3280,74530403,790.0,,0,2,/ransakaravihara/starter-notebook-xgboostbaseline,Tabular Playground Series - Sep 2021
3281,74021193,806.0,,1,4,/danieleongari/tps-sep21-7-cool-python-packages-i-m-telling-you,Tabular Playground Series - Sep 2021
3282,75755018,799.0,0.7941448445546373,4,8,/abrambeyer/tps-sep21-eda-preprocess-baseline-model,Tabular Playground Series - Sep 2021
3283,75083370,810.0,0.7946737077737921,0,7,/deependraparichha/tps-sep-2021,Tabular Playground Series - Sep 2021
3284,75037495,838.0,,0,1,/dontguess/ae-included-yet-not-so-fine,Tabular Playground Series - Sep 2021
3285,113258610,845.0,,2,5,/aniruddhapa/insurance-claim,Tabular Playground Series - Sep 2021
3286,73698037,836.0,0.7952810567905232,1,6,/aleksandraposka/mljar-automl-starter-tps-sep21,Tabular Playground Series - Sep 2021
3287,75533472,842.0,0.8121350317924657,13,58,/firefliesqn/simple-keras-cpu-100-data,Tabular Playground Series - Sep 2021
3288,74347693,852.0,0.799012947637841,13,29,/virasydoriak/simple-logistic-regression-very-fast-with-sklearn,Tabular Playground Series - Sep 2021
3289,75831182,829.0,0.8093626888883005,1,0,/robinbaldeo/notebookb8e6e27ba3,Tabular Playground Series - Sep 2021
3290,74164312,868.0,0.7380054532780582,0,3,/mafrojaakter/september-2021-tabular,Tabular Playground Series - Sep 2021
3291,73963837,859.0,,1,8,/cmarquay/eda-skewness,Tabular Playground Series - Sep 2021
3292,73920318,887.0,0.8108613651735608,4,8,/chamecall/tps-pytorch-lightning,Tabular Playground Series - Sep 2021
3293,74958018,855.0,,0,4,/bibhabasumohapatra/lightgbm-hyperparameters,Tabular Playground Series - Sep 2021
3294,74594674,893.0,0.8104339585505587,0,4,/danofer/tabnet-cv-0-81,Tabular Playground Series - Sep 2021
3295,74210896,860.0,,11,30,/mrigendraagrawal/tps-sep-eda-and-starter,Tabular Playground Series - Sep 2021
3296,73789756,870.0,0.8100386692320265,0,9,/tensorchoko/tabular-sep-2021-lightgbm,Tabular Playground Series - Sep 2021
3297,74070881,904.0,,0,3,/shivarama/tps-submission-1,Tabular Playground Series - Sep 2021
3298,74272856,888.0,0.8086435785473239,0,4,,Tabular Playground Series - Sep 2021
3299,75323201,916.0,,0,3,/ottpocket/embeddings-from-daes-with-tensorflow,Tabular Playground Series - Sep 2021
3300,73720073,909.0,,0,5,/madhuri15/tps-sept2021,Tabular Playground Series - Sep 2021
3301,76080116,947.0,,0,0,/maryiakurdina/mlpclassifier-september-2021-playground,Tabular Playground Series - Sep 2021
3302,73956182,954.0,0.8034830333931821,21,37,/desalegngeb/sept-2021-tps-eda-models,Tabular Playground Series - Sep 2021
3303,73956182,954.0,0.8039688769436899,21,37,/desalegngeb/sept-2021-tps-eda-models,Tabular Playground Series - Sep 2021
3304,73956182,954.0,0.8033263813768301,21,37,/desalegngeb/sept-2021-tps-eda-models,Tabular Playground Series - Sep 2021
3305,73682974,956.0,0.8048532798831906,0,4,/kieranmcgee/tps-september-lightautoml-baseline,Tabular Playground Series - Sep 2021
3306,74921555,1033.0,,0,18,/alexeykolobyanin/tps-sep-ridge-with-sklearn-intelex-2x-speedup,Tabular Playground Series - Sep 2021
3307,74211274,970.0,,12,17,/venkatkumar001/tps-sep-2021-automl,Tabular Playground Series - Sep 2021
3308,75400341,985.0,0.7745383360626397,2,9,/berkcanucan/tps-sep-2021-tensorflow-cnn,Tabular Playground Series - Sep 2021
3309,73891628,995.0,0.8036413029235964,2,4,/shreyashgupta88/kfold-tuning-xgb-using-optuna,Tabular Playground Series - Sep 2021
3310,73778503,1005.0,0.786034706065779,2,9,/sankalpsrivastava26/tps-sept21-tensorflow-model-with-gpu,Tabular Playground Series - Sep 2021
3311,74086870,1002.0,,0,1,/guanboon/20210902-tps-base-line,Tabular Playground Series - Sep 2021
3312,74529895,1009.0,0.8028364041995529,2,7,/mehedimuaz/handle-skewed-data-and-go-with-xgbclassifier,Tabular Playground Series - Sep 2021
3313,74770255,1018.0,0.800416192601052,0,2,/mahditavakol/sep1-xgboost,Tabular Playground Series - Sep 2021
3314,73755539,1041.0,0.5090998744003844,1,6,/tunguz/tps-sep-2021-simple-linear-baseline,Tabular Playground Series - Sep 2021
3315,76010708,1098.0,,0,3,/hisaylama/tabular-playground-series,Tabular Playground Series - Sep 2021
3316,75591532,1129.0,0.5252005837347897,0,3,/yasassandeepa/regression-techniques-pca,Tabular Playground Series - Sep 2021
3317,74365082,1124.0,0.799012947637841,0,3,/sureshmecad/tps-sep-2021-eda,Tabular Playground Series - Sep 2021
3318,74154745,1203.0,,0,1,/theodormihaiiliant/tabular-september-eda,Tabular Playground Series - Sep 2021
3319,73979422,1215.0,,0,3,/liveyourdreams/tabularplaygroundseriesdataanalysis,Tabular Playground Series - Sep 2021
3320,76090764,1223.0,,0,7,/priyaduttbhatt/tps-sep2021,Tabular Playground Series - Sep 2021
3321,75964535,1227.0,0.7912856087037826,0,5,/swetash/september-21-tps-lgbm,Tabular Playground Series - Sep 2021
3322,73694505,1222.0,0.7912668353199773,18,32,/jeongbinpark/tps-sep-2021-lightgbm,Tabular Playground Series - Sep 2021
3323,141922434,1229.0,,1,5,/haozhang607/tabular-playground-series-sep-2021,Tabular Playground Series - Sep 2021
3324,73773218,1242.0,,10,17,/jeongkyulim/cheer-up-r-simple-baseline-catboost,Tabular Playground Series - Sep 2021
3325,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3326,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3327,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3328,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3329,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3330,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3331,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3332,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3333,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3334,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3335,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3336,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3337,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3338,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3339,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3340,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3341,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3342,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3343,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3344,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3345,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3346,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3347,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3348,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3349,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3350,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3351,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3352,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3353,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3354,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3355,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3356,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3357,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3358,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3359,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3360,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3361,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3362,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3363,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3364,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3365,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3366,73994279,1259.0,0.7809833437952713,1,1,/gopalkk1/how-to-handle-the-na-value-in-dataset,Tabular Playground Series - Sep 2021
3367,77634240,1257.0,,2,7,/moizkhan11/tabularplayground-models,Tabular Playground Series - Sep 2021
3368,73800344,1262.0,,0,1,/ravindrasonawane/tabular-playground-series-september-2021,Tabular Playground Series - Sep 2021
3369,74119389,1268.0,0.761516211174366,3,3,/hasangam/fastai-starter,Tabular Playground Series - Sep 2021
3370,74067198,1274.0,,0,1,/fernandocanteruccio/notebook124833d3c4,Tabular Playground Series - Sep 2021
3371,76049771,1275.0,0.5041027772855708,0,0,/rishabhkumar11081994/rishabhs-swag,Tabular Playground Series - Sep 2021
3372,73685165,1279.0,0.7743351500146476,1,2,/willemtraupel/early-exploration-and-xgboost-benchmark,Tabular Playground Series - Sep 2021
3373,74019800,1293.0,,0,0,/yvamshivardhan/sept-2021-nan-filling,Tabular Playground Series - Sep 2021
3374,74578478,1289.0,0.7741273263325424,1,2,/simodake/lightbgm,Tabular Playground Series - Sep 2021
3375,73985370,1311.0,,0,5,/peressim/tabular-playground-series-sep-2021,Tabular Playground Series - Sep 2021
3376,75570531,1308.0,,0,6,/juanpasutti/tps-09-21-chi2-test-for-missing-values,Tabular Playground Series - Sep 2021
3377,75913960,1338.0,,0,2,/mlevytskyi/sgdclassifier-randomizedsearchcv,Tabular Playground Series - Sep 2021
3378,76067112,1351.0,,0,1,/zsxoff/tps-sep-2021-lightautoml-baseline,Tabular Playground Series - Sep 2021
3379,73720245,1343.0,0.7710967994383484,1,4,/tarunbisht11/tps-september-xgb-in-gpu-baseline,Tabular Playground Series - Sep 2021
3380,78403807,1359.0,0.8158785076907137,1,5,/aaronds/tps-step2021,Tabular Playground Series - Sep 2021
3381,73738654,1377.0,0.7594241707757626,0,1,/flafuji/tps-sep2021-xgboost,Tabular Playground Series - Sep 2021
3382,74372954,1406.0,,2,3,/whitishlion/tabularplaygroundseries-sep2021,Tabular Playground Series - Sep 2021
3383,73806186,1410.0,,0,3,/stpeteishii/tps0921-data-histplot,Tabular Playground Series - Sep 2021
3384,75851952,1430.0,0.5544719748292538,0,3,/torokalbert/xgboost-september,Tabular Playground Series - Sep 2021
3385,73693830,1503.0,0.7311710600391521,2,13,/jarupula/tps-sep-getting-started,Tabular Playground Series - Sep 2021
3386,74519191,1526.0,0.7229971032516026,0,1,/mrshivanshuagnihotri/model-1-3,Tabular Playground Series - Sep 2021
3387,75818165,1539.0,0.7186002620007392,0,2,/jagdmir/tabular-playground-series-sep-2021-xgboost,Tabular Playground Series - Sep 2021
3388,75655239,1548.0,0.7170768353320377,0,0,/pranjalchatterjee/stacking-2-levels-base-5-models-tps-sep-21,Tabular Playground Series - Sep 2021
3389,73733477,1565.0,0.7107330096060066,0,2,/phamtheds/getting-started-september-2021-tabular-playground,Tabular Playground Series - Sep 2021
3390,73941941,1613.0,0.70603207844909,1,3,/revathiprakash/tps-sep-2021-rapids,Tabular Playground Series - Sep 2021
3391,73787863,1631.0,,0,4,/gauravduttakiit/claim-classification-using-pycaret,Tabular Playground Series - Sep 2021
3392,76115845,1636.0,,0,3,/tariqchhussain/simple-eda-xgb-implementation-tps-sept-2021,Tabular Playground Series - Sep 2021
3393,73816172,1638.0,0.6850752851875956,0,0,/tracyporter/sep-21-tabular,Tabular Playground Series - Sep 2021
3394,74291739,1668.0,,0,1,/nizado/tabular-playground-series-sep-2021-2nd-edition,Tabular Playground Series - Sep 2021
3395,75343744,1689.0,0.6190906933960414,4,8,/kalyanackrovvidy/chi2-feature-selection,Tabular Playground Series - Sep 2021
3396,75175829,1718.0,0.5678414789539513,0,1,/kelizatoh/sep-2021-tabular-playground-logistic-regression,Tabular Playground Series - Sep 2021
3397,74887996,1730.0,,0,0,/mpetrushanskyi/xgb-variations,Tabular Playground Series - Sep 2021
3398,73985768,1732.0,,0,2,/sorty24/kagglecomp,Tabular Playground Series - Sep 2021
3399,74218262,1738.0,0.5521137026579614,0,0,/sonjabutler/iterative-imputer-with-random-forest-regressor,Tabular Playground Series - Sep 2021
3400,74840525,1756.0,0.5442424624636794,0,3,/ranjeer/pg-sep2021,Tabular Playground Series - Sep 2021
3401,74606555,1762.0,0.5220391420509614,0,2,/deepak915/win-tps-like-a-pro,Tabular Playground Series - Sep 2021
3402,76097621,1770.0,,1,2,/stmohd/tensorflow-101-tabular-playground-series-sep-20,Tabular Playground Series - Sep 2021
3403,73864673,1776.0,0.5383080462923389,1,2,/heerendra/beginner-friendly-end-to-end,Tabular Playground Series - Sep 2021
3404,74212816,1799.0,0.4994260587400013,2,4,/reddy9819/tabular-playground-sep-2021,Tabular Playground Series - Sep 2021
3405,73958785,1816.0,,0,10,/saileshnair/tps202109-normal-and-quick-eda,Tabular Playground Series - Sep 2021
3406,73781538,1862.0,,0,4,/aravind2608/feature-selection-techniques,Tabular Playground Series - Sep 2021
3407,74950274,1893.0,0.5000134829036781,0,1,/hyunee98/210917-claim,Tabular Playground Series - Sep 2021
3408,75528343,1937.0,0.4469400199496601,1,3,/kishorthakre/tabular-playground-s21-kaggle,Tabular Playground Series - Sep 2021
3409,73940897,1940.0,,0,2,/aristotle609/eda-and-model,Tabular Playground Series - Sep 2021
3410,73752976,2.0,417.517933531464,0,0,/mohamedhelmy96/notebook49fc3630d6,Crime_Learn
3411,74874884,12.0,,0,4,/phantivia/can-we-read-faster,Wikipedia - Image/Caption Matching
3412,78727968,16.0,,11,48,/debarshichanda/pytorch-wikipedia-image-caption-starter,Wikipedia - Image/Caption Matching
3413,79221185,17.0,,0,2,/nathandiamond/wikipedia-image-caption,Wikipedia - Image/Caption Matching
3414,74796641,35.0,,5,18,/kalilurrahman/wikimedia-image-text-matching-eda,Wikipedia - Image/Caption Matching
3415,76637903,71.0,,0,3,/seikimaiihuang/practice,Wikipedia - Image/Caption Matching
3416,74993134,72.0,0.1806491104932289,6,36,/thedrcat/wiki-image-caption-eda-and-baseline-new-data,Wikipedia - Image/Caption Matching
3417,116033501,90.0,,0,3,/martenro/multilingualclipstart5epochs,Wikipedia - Image/Caption Matching
3418,78971618,1.0,0.1393661291545408,10,78,/shujun717/1-solution-lstm-cnn-transformer-1-fold,Google Brain - Ventilator Pressure Prediction
3419,76883289,4.0,0.1923763848615959,14,123,/junkoda/pytorch-lstm-with-tensorflow-like-initialization,Google Brain - Ventilator Pressure Prediction
3420,78774803,10.0,,7,74,/l0glikelihood/0-1093-single-public-lb,Google Brain - Ventilator Pressure Prediction
3421,76380193,13.0,0.6013575734647628,19,138,/cdeotte/rapids-knn-and-kmeans-0-600,Google Brain - Ventilator Pressure Prediction
3422,78747971,16.0,,0,14,/authman/magic-post-processing-attempt-no-3of6,Google Brain - Ventilator Pressure Prediction
3423,75881875,17.0,,9,93,/currypurin/ventilator-pressure-simple-eda,Google Brain - Ventilator Pressure Prediction
3424,76288837,19.0,,6,40,/columbia2131/speed-up-featur-extraction-diff-rolling,Google Brain - Ventilator Pressure Prediction
3425,76880867,35.0,,3,14,/cepheidq/gaussian-dropout-for-pytorch,Google Brain - Ventilator Pressure Prediction
3426,76042492,50.0,0.1768169530635958,8,65,/steubk/tensorflow-bidirectional-lstm-custom-mae-loss,Google Brain - Ventilator Pressure Prediction
3427,76861201,70.0,,12,92,/marutama/eda-about-time-step-and-u-out,Google Brain - Ventilator Pressure Prediction
3428,76020595,86.0,,0,2,/kokinishimaki/ventilator-pressure-eda-and-simple-submission,Google Brain - Ventilator Pressure Prediction
3429,76938056,98.0,,0,3,/blankaf/google-brain-vpp-train-infer-tpu,Google Brain - Ventilator Pressure Prediction
3430,77744464,108.0,,8,30,/bibhash123/ventilator-pressure-prediction-insights,Google Brain - Ventilator Pressure Prediction
3431,75701822,124.0,0.2710342976272745,13,48,/junhyeok99/tensorflow,Google Brain - Ventilator Pressure Prediction
3432,76537092,100.0,,3,30,/alexxanderlarko/lgbm-sel-feat-1,Google Brain - Ventilator Pressure Prediction
3433,76240083,129.0,0.1518015367351961,12,75,/dlaststark/gb-vpp-why-so-serious,Google Brain - Ventilator Pressure Prediction
3434,79176684,167.0,,0,5,/tunguz/gb-vpp-pulp-fiction-2,Google Brain - Ventilator Pressure Prediction
3435,77866101,158.0,0.1368231905608881,1,13,/katsuomi/median-wins-round,Google Brain - Ventilator Pressure Prediction
3436,77845723,161.0,,0,2,/lilkoke/1024-ensemble-lilkoke,Google Brain - Ventilator Pressure Prediction
3437,77294575,146.0,,2,5,/nishimoto/gb-vpp-keras-classifier-lb-0-186,Google Brain - Ventilator Pressure Prediction
3438,75704545,170.0,0.2761256742357517,12,24,/lukaszborecki/ventilator-ts,Google Brain - Ventilator Pressure Prediction
3439,78504142,179.0,,0,2,/dailysergey/ventillator-pressure-fastai-folds-train,Google Brain - Ventilator Pressure Prediction
3440,77418948,183.0,,2,20,/aikhmelnytskyy/google-brain-with-tpu-on-both-colab-and-kaggle,Google Brain - Ventilator Pressure Prediction
3441,78591828,206.0,,0,3,/leolu1998/dnn-lstm-kmeans-tpu,Google Brain - Ventilator Pressure Prediction
3442,75406095,197.0,,0,11,/yus002/9-22-eda,Google Brain - Ventilator Pressure Prediction
3443,78324930,226.0,,2,6,/toroi0610/feature-engineering-non-ml-approach,Google Brain - Ventilator Pressure Prediction
3444,75835345,230.0,0.1897565420667016,26,151,/dmitryuarov/ventilator-pressure-eda-lstm-0-189,Google Brain - Ventilator Pressure Prediction
3445,78054386,214.0,0.152923082455035,0,0,/chenghanpu/vpp-dual-head-regression-median-postprocessing,Google Brain - Ventilator Pressure Prediction
3446,76004409,224.0,0.6940992294497226,0,4,/gauravbrills/ventilator-pressure-prediction-autogluon-fiddle,Google Brain - Ventilator Pressure Prediction
3447,75473855,210.0,,24,32,/hamzaghanmi/data-visualization-using-autoviz,Google Brain - Ventilator Pressure Prediction
3448,77262837,325.0,,0,7,/albertferre/timeserieskmeans-clustering,Google Brain - Ventilator Pressure Prediction
3449,79996054,235.0,,1,5,/nilavanakilan/vpp-ensemble-3,Google Brain - Ventilator Pressure Prediction
3450,77113105,259.0,0.1599716049909824,1,12,,Google Brain - Ventilator Pressure Prediction
3451,76215088,267.0,0.1546498109447988,23,160,/snnclsr/a-dummy-approach-to-improve-your-score-postprocess,Google Brain - Ventilator Pressure Prediction
3452,77799147,231.0,0.6002365418653802,3,17,/frankmollard/decrease-in-impurity-importances,Google Brain - Ventilator Pressure Prediction
3453,77416895,284.0,,12,23,/barangizagiza/lightgbm-with-optuna-tunercv-gpu-0-468,Google Brain - Ventilator Pressure Prediction
3454,78521857,288.0,,4,76,/hrshuvo/dnn-lstm-tpu,Google Brain - Ventilator Pressure Prediction
3455,78710498,289.0,0.1359243221893614,0,4,/vineethakkinapalli/random-weights-blending-tool-ventilator-pressure,Google Brain - Ventilator Pressure Prediction
3456,79088134,293.0,0.1108698367694474,2,20,/titericz/pid-p-and-pi-reverse-engineer-1,Google Brain - Ventilator Pressure Prediction
3457,75432065,320.0,,0,5,/siero5335/basic-eda-ventilator,Google Brain - Ventilator Pressure Prediction
3458,77896191,349.0,0.1575579957034577,0,9,/vslaykovsky/better-than-median-classification-ensemble,Google Brain - Ventilator Pressure Prediction
3459,76218932,317.0,,0,6,/oriori4244/tensorflow-bidirectional-lstm,Google Brain - Ventilator Pressure Prediction
3460,76608306,352.0,0.2446021670891398,4,20,/jonaspalucibarbosa/ventilator-pressure-starter-lstm-on-tpu,Google Brain - Ventilator Pressure Prediction
3461,77631275,353.0,0.1616442282696086,6,20,/jmcslk/hybrid-cnn-enc-dec-sample-weights,Google Brain - Ventilator Pressure Prediction
3462,76235349,363.0,,0,13,/qquick/ventilator-eda-visual-correlation-w-pressure,Google Brain - Ventilator Pressure Prediction
3463,76026903,377.0,4.239316933939745,0,3,/theidleman/google-vpp,Google Brain - Ventilator Pressure Prediction
3464,76087612,390.0,9.826835354468708,0,5,/whitecat0022/google-brain-ventilator-pressure-prediction-knn,Google Brain - Ventilator Pressure Prediction
3465,75860982,392.0,0.3310605683784058,11,36,/kavehshahhosseini/google-brain-tensorflow-simple-lstm-start,Google Brain - Ventilator Pressure Prediction
3466,78643520,840.0,0.1407901295210029,0,2,/adityasharma01/dnn-lstm-tpu,Google Brain - Ventilator Pressure Prediction
3467,78060656,393.0,,3,7,/krivenkozz/simple-pytorch-fastai-deotte-dhoa-refactoring,Google Brain - Ventilator Pressure Prediction
3468,76441640,397.0,0.1522624305390277,20,84,/manabendrarout/single-bi-lstm-model-pressure-predict-gpu-infer,Google Brain - Ventilator Pressure Prediction
3469,77032477,398.0,0.2247316400158266,1,7,/pavan9065/explore-ventilator-pressure-prediction,Google Brain - Ventilator Pressure Prediction
3470,76969498,406.0,,0,5,/felipebihaiek/ventilator-lightgbm-with-gpu,Google Brain - Ventilator Pressure Prediction
3471,75416633,379.0,7.546997309183634,0,9,/junichiromorita/ventilator-pressure-preliminary-eda-en-jpn,Google Brain - Ventilator Pressure Prediction
3472,77896199,369.0,,0,2,/heliksmersenburg/exploratory-data-analysis-eda-basics,Google Brain - Ventilator Pressure Prediction
3473,76347622,411.0,,1,11,/coder247/simple-xgboost-solution-for-beginner-s,Google Brain - Ventilator Pressure Prediction
3474,75908447,457.0,,2,29,/konradb/tabnet-end-to-end-starter,Google Brain - Ventilator Pressure Prediction
3475,78538031,417.0,0.1364028721507512,0,2,/muki2003/ventilator-pressure-prediction-tpu,Google Brain - Ventilator Pressure Prediction
3476,77817748,476.0,0.4614147656903485,1,6,/omarvivas/lgbm-v1,Google Brain - Ventilator Pressure Prediction
3477,77627517,1520.0,,3,4,/andreylovyagin/examples-of-auto-eda,Google Brain - Ventilator Pressure Prediction
3478,80743643,549.0,,5,31,/bryanb/ventilator-pressure-prediction-eda,Google Brain - Ventilator Pressure Prediction
3479,78424264,495.0,,0,13,/tensorchoko/google-brain-eda,Google Brain - Ventilator Pressure Prediction
3480,75935155,496.0,,2,21,/kalilurrahman/google-ventilator-lazy-prediction-eda,Google Brain - Ventilator Pressure Prediction
3481,75564843,504.0,,0,4,/kalaikumarr/automl-pycaret,Google Brain - Ventilator Pressure Prediction
3482,80514082,505.0,,3,3,/vladiluzjr/linear-regression-u-in-and-pressure,Google Brain - Ventilator Pressure Prediction
3483,87067799,555.0,,0,3,/ghostcxs/ventilator-kerastuner-model,Google Brain - Ventilator Pressure Prediction
3484,77419823,511.0,,5,8,/zenstat/beginner-linear-regression-example,Google Brain - Ventilator Pressure Prediction
3485,78300278,567.0,,0,5,/ounamg008/lgbm-featureeng-added-3-new-feature-kfold-0-50,Google Brain - Ventilator Pressure Prediction
3486,78253566,546.0,0.1830208975716681,1,2,/msc2021/didactic-tests-eda-gpu-tpu-lstm-tensor-flow,Google Brain - Ventilator Pressure Prediction
3487,76680140,423.0,,7,4,/masato114/vp-wavenet-training-gpu,Google Brain - Ventilator Pressure Prediction
3488,75776786,357.0,0.1734060589444909,30,177,/kensit/improvement-base-on-tensor-bidirect-lstm-0-173,Google Brain - Ventilator Pressure Prediction
3489,76161348,658.0,,2,6,/takumindesu/begginer-eda,Google Brain - Ventilator Pressure Prediction
3490,77434141,614.0,,7,31,/motloch/ventilator-pressure-train-data-exploration,Google Brain - Ventilator Pressure Prediction
3491,76350972,1078.0,0.7001866526232561,1,13,/shinyatakaramoto/simple-lightgbm,Google Brain - Ventilator Pressure Prediction
3492,75684321,630.0,,0,6,/tahsinulislam/google-brain-v2-simple-xgboost-lb-1-01-cv-0-61,Google Brain - Ventilator Pressure Prediction
3493,75780119,704.0,,4,23,/danofer/ts-windows-feature-engineering-ventilators,Google Brain - Ventilator Pressure Prediction
3494,76483554,729.0,0.1522624305390277,0,13,/soumenksarker/bi-lstm-model-pressure-predict-gpu-infer,Google Brain - Ventilator Pressure Prediction
3495,75714074,730.0,0.4987806127532808,6,29,/ilialar/ventilator-pressure-eda-and-baseline,Google Brain - Ventilator Pressure Prediction
3496,77878714,755.0,0.1590823078604201,0,10,/aimanlim0/transformer-lstm,Google Brain - Ventilator Pressure Prediction
3497,77336770,769.0,,0,13,/pavfedotov/lofo-feature-importance,Google Brain - Ventilator Pressure Prediction
3498,76749900,671.0,,0,3,/hiroueno/implement-groupkfold-for-bidirectional-lstm,Google Brain - Ventilator Pressure Prediction
3499,76507150,806.0,1.3431514323729885,1,9,/bobber/nn-baseline-with-eda-and-predict-80-pressures,Google Brain - Ventilator Pressure Prediction
3500,78166491,800.0,,2,10,/luizflpe/vpp-pressure-hysteresis-impact-of-r-feat-eng,Google Brain - Ventilator Pressure Prediction
3501,78469331,791.0,,0,30,/atamazian/ventilator-custom-loss-in-tensorflow,Google Brain - Ventilator Pressure Prediction
3502,75671530,820.0,,0,13,/zhaodianwen/simple-eda-beginner,Google Brain - Ventilator Pressure Prediction
3503,77706337,823.0,,0,5,/sagnik1511/pytorch-ann-baseline-google-ventilator-challenge,Google Brain - Ventilator Pressure Prediction
3504,76144211,826.0,,0,7,/jaredsavage/ventilator-pressure-prediction-with-r,Google Brain - Ventilator Pressure Prediction
3505,88616714,891.0,,0,3,/jarupula/google-ventilator-pressure-prediction-lstm,Google Brain - Ventilator Pressure Prediction
3506,76502935,897.0,,0,1,/seraquevence/r-first-nn-ventilator-nn-v01,Google Brain - Ventilator Pressure Prediction
3507,76671996,881.0,,31,182,/carlmcbrideellis/ventilator-pressure-eda-and-simple-submission,Google Brain - Ventilator Pressure Prediction
3508,78375165,892.0,,1,2,/kiitosu/ventilator-feature-engineering,Google Brain - Ventilator Pressure Prediction
3509,75814357,895.0,,0,9,/docxian/google-brain-ventilator-pressure-starter,Google Brain - Ventilator Pressure Prediction
3510,76582247,868.0,,0,3,/takasu331/google-brain-eda-japanese-and-start,Google Brain - Ventilator Pressure Prediction
3511,76584104,946.0,,12,34,/get2jawa/simple-eda-with-xgboost-for-beginners,Google Brain - Ventilator Pressure Prediction
3512,75470932,947.0,4.132889814508622,0,4,/rhythmcam/pycaret-ventilator-pressure,Google Brain - Ventilator Pressure Prediction
3513,75521271,919.0,0.7152352757714673,0,11,/susnato/lgbm-starter,Google Brain - Ventilator Pressure Prediction
3514,75945183,918.0,0.4019853984138347,12,49,/optimo/the-beauty-of-tabnet-a-simple-baseline,Google Brain - Ventilator Pressure Prediction
3515,77059293,962.0,0.6013642917396794,0,1,/alfredomaranca/rapids-knn-and-kmeans-lung-inspiration-fft,Google Brain - Ventilator Pressure Prediction
3516,75457498,1014.0,,0,4,/ryotaichikawa/ventilator-pressure-simple-eda-lightgbm-model,Google Brain - Ventilator Pressure Prediction
3517,76003140,1018.0,0.1577631474755263,34,295,/tenffe/finetune-of-tensorflow-bidirectional-lstm,Google Brain - Ventilator Pressure Prediction
3518,75749932,1041.0,,2,9,/towhidultonmoy/lgbm-on-cpu-optuna-tuning,Google Brain - Ventilator Pressure Prediction
3519,76332136,1047.0,,6,35,/mistag/keras-model-tuning-with-optuna,Google Brain - Ventilator Pressure Prediction
3520,78673661,1048.0,0.1501406910620067,0,2,/rizkykiky/ensemble-of-lstm-notebook,Google Brain - Ventilator Pressure Prediction
3521,76016912,1073.0,,2,7,/werooring/ventilator-pressure-prediction-eda-starter,Google Brain - Ventilator Pressure Prediction
3522,75453039,1092.0,6.244215308983569,2,8,/edwintyh/ventilator-pressure-quick-eda-dummy-baseline,Google Brain - Ventilator Pressure Prediction
3523,75453039,1092.0,6.358612408636467,2,8,/edwintyh/ventilator-pressure-quick-eda-dummy-baseline,Google Brain - Ventilator Pressure Prediction
3524,75711881,1110.0,1.566884833013364,1,12,/akihironomura/google-brain-lightgbm-optuna,Google Brain - Ventilator Pressure Prediction
3525,77615577,1143.0,0.5357442307990955,7,23,/dignil/ventilator-google-brain-challenge,Google Brain - Ventilator Pressure Prediction
3526,76991843,1101.0,,23,79,/aerdem4/google-ventilator-lofo-feature-importance,Google Brain - Ventilator Pressure Prediction
3527,76157595,1120.0,1.1564610451310202,0,9,/yasuosuzuki/various-feature-and-lightgbm,Google Brain - Ventilator Pressure Prediction
3528,78679903,1195.0,,0,2,/aichiaida/removeoutliers,Google Brain - Ventilator Pressure Prediction
3529,76109939,1252.0,,0,5,/luongduongminh/ventilator-pressure,Google Brain - Ventilator Pressure Prediction
3530,75612908,1304.0,,6,8,/msafi04/google-brain-ventilator-pressure-prediction-gpu,Google Brain - Ventilator Pressure Prediction
3531,75648019,1294.0,0.3508356014952372,14,74,/ryanbarretto/tensorflow-lstm-baseline,Google Brain - Ventilator Pressure Prediction
3532,76352232,1324.0,,6,66,/t88take/searching-similar-u-in-using-cosine-similarity,Google Brain - Ventilator Pressure Prediction
3533,78271666,1338.0,0.1647696874480518,0,0,/sumitai/ventillator-fastai-lb-0-169-no-kfolds-no-blend,Google Brain - Ventilator Pressure Prediction
3534,75832126,1366.0,0.550795362282484,1,9,/drastamat/lgbm-starter,Google Brain - Ventilator Pressure Prediction
3535,75555903,1377.0,,0,4,/haroldmei/data-visualisation,Google Brain - Ventilator Pressure Prediction
3536,78176083,1365.0,0.168188286146522,10,45,/dienhoa/ventillator-fastai-lb-0-168-no-kfolds-no-blend,Google Brain - Ventilator Pressure Prediction
3537,75594561,1363.0,,7,33,/kooose/anomaly-detection-by-clustering,Google Brain - Ventilator Pressure Prediction
3538,76388784,1404.0,1.3830107046062494,1,10,/ahmedaffan789/google-brain-eda-lstm-bi-directional,Google Brain - Ventilator Pressure Prediction
3539,75823909,1449.0,6.25741113978766,0,6,/samkupferschmid/lstm-baseline-tensorflow-keras,Google Brain - Ventilator Pressure Prediction
3540,77221238,1454.0,,0,4,/ahmedmoabbas/pytorch-models-getting-data,Google Brain - Ventilator Pressure Prediction
3541,75830721,1492.0,0.640556579131622,4,19,/craigmthomas/gb-vpp-stacked-starter,Google Brain - Ventilator Pressure Prediction
3542,78149898,1502.0,,0,0,/rishishounak/vent-5,Google Brain - Ventilator Pressure Prediction
3543,78709395,1494.0,0.1882597340132464,43,83,/kartik2khandelwal/feature-engineering-lstm-score-0-1878,Google Brain - Ventilator Pressure Prediction
3544,76787928,1496.0,,0,3,/michaelcerda/lgbm-for-beginners-ventilator-pressure,Google Brain - Ventilator Pressure Prediction
3545,76256671,1512.0,,0,1,/navid1993/ventilator-pressure-prediction-bidirectional-lstm,Google Brain - Ventilator Pressure Prediction
3546,76829995,1532.0,4.203244485201774,0,7,/shubham9455999082/prediction-using-lstm,Google Brain - Ventilator Pressure Prediction
3547,78418072,1551.0,,5,10,/valentinateslenko/ventilator-pressure-tensorflow-feature-engineering,Google Brain - Ventilator Pressure Prediction
3548,77142997,1552.0,,0,10,/yoshikuwano/vpp-eda,Google Brain - Ventilator Pressure Prediction
3549,75633839,1556.0,,1,6,/shashimo/foolishly-implemented-what-i-learned-in-introml,Google Brain - Ventilator Pressure Prediction
3550,77202266,1569.0,,0,0,/ajiiscbanglore/neural-network-google-brain,Google Brain - Ventilator Pressure Prediction
3551,75586321,1570.0,7.384161485486842,0,5,/nikhilsharma24/quick-start-in-r,Google Brain - Ventilator Pressure Prediction
3552,76447998,1580.0,,0,3,/natthasit/ventilator-pressure-prediction,Google Brain - Ventilator Pressure Prediction
3553,78998360,1577.0,,10,27,/tfukuda675/update-add-3d-data-visu-plotly-seaborn-matplot,Google Brain - Ventilator Pressure Prediction
3554,75821962,1578.0,0.2055241695855895,0,10,/munumbutt/tensorflow-bidirectional-lstm-with-tpu,Google Brain - Ventilator Pressure Prediction
3555,75754461,1598.0,,0,5,/wabinab/ventpressure1,Google Brain - Ventilator Pressure Prediction
3556,76176354,1612.0,,1,7,/bakar31/vpp-basic-eda-and-baseline-model,Google Brain - Ventilator Pressure Prediction
3557,78116954,1613.0,0.2265061955615884,5,13,/sagarikajadon/gb-vpp-pytorch-lstm-baseline,Google Brain - Ventilator Pressure Prediction
3558,76799979,1639.0,0.2526466679219571,0,1,/anaxmenobrito/lung-pressure-competition-pytorch-version,Google Brain - Ventilator Pressure Prediction
3559,75784568,1641.0,0.2438890870619688,4,38,/alexryzhkov/lightautoml-continuer,Google Brain - Ventilator Pressure Prediction
3560,76038677,1647.0,,3,11,/tetsuya777/japanease-google-brain-eda,Google Brain - Ventilator Pressure Prediction
3561,75529216,1673.0,3.802084722658943,0,4,/drsachingupta/xgboost-simple-run-with-autoviz-and-gridsearchcv,Google Brain - Ventilator Pressure Prediction
3562,75976800,1689.0,,1,8,/suharkov/vent-pressure-eda,Google Brain - Ventilator Pressure Prediction
3563,75633159,1686.0,0.9593729216991886,4,12,/ranjeetshrivastav/ventilator-pressure-prediction-xgboost,Google Brain - Ventilator Pressure Prediction
3564,77628105,1696.0,0.2824335767753082,9,19,/esratmaria/ventilator-pressure-prediction-eda-kfold,Google Brain - Ventilator Pressure Prediction
3565,77910565,1700.0,,2,6,/sakuraandblackcat/r-eda-and-tidymodels,Google Brain - Ventilator Pressure Prediction
3566,76020002,1711.0,,0,3,/squarex/ventilator-pressure-prediction-lgb-eda,Google Brain - Ventilator Pressure Prediction
3567,78134820,1709.0,,1,3,/jordiarellano/lstm-model,Google Brain - Ventilator Pressure Prediction
3568,79074092,1715.0,,0,0,/sebastienmonfort/notebookcea05140f2,Google Brain - Ventilator Pressure Prediction
3569,78241014,1731.0,,0,0,/v18nguye/lstm-feature-filtering-tpu-huberloss,Google Brain - Ventilator Pressure Prediction
3570,78760441,1739.0,,2,5,/trinayanbharadwaj/google-brain-ventilator-pressure-prediction-0-353,Google Brain - Ventilator Pressure Prediction
3571,78115176,1746.0,,1,6,/tom99763/fitting-with-rnn,Google Brain - Ventilator Pressure Prediction
3572,75697559,1775.0,,0,6,/shinichikanehira/ventilator-pressure-eda,Google Brain - Ventilator Pressure Prediction
3573,153910066,1794.0,,2,3,/manuelmasiello/ventilator-pressure-prediction-using-cnn,Google Brain - Ventilator Pressure Prediction
3574,92170583,1856.0,,2,7,/jackwilliams3rd/how-to-confirm-data,Google Brain - Ventilator Pressure Prediction
3575,76176117,1858.0,,0,4,/giobbu/ventilator-tf-data-dataset-tensorflow,Google Brain - Ventilator Pressure Prediction
3576,76642170,1873.0,,0,8,/dellingson/ventilator-pressure-dnn,Google Brain - Ventilator Pressure Prediction
3577,75549059,1904.0,,1,12,/lys620/eda-google-brain-graph,Google Brain - Ventilator Pressure Prediction
3578,75982793,1917.0,,50,242,/usharengaraju/eda-fe-tabnet-weights-and-biases,Google Brain - Ventilator Pressure Prediction
3579,75426542,1926.0,3.860130743437783,6,26,/patrick0302/add-last-u-in-as-new-feat,Google Brain - Ventilator Pressure Prediction
3580,78511370,1949.0,0.624085277005859,3,17,/mykeysid10/ventilator-pressure-prediction-lstm,Google Brain - Ventilator Pressure Prediction
3581,78299610,1959.0,0.6382016028444708,0,5,/corrrado/ventilator-xgboost,Google Brain - Ventilator Pressure Prediction
3582,76353568,1961.0,0.702682034806997,0,8,/hamditarek/google-vp-prediction-xgbregressor-gpu,Google Brain - Ventilator Pressure Prediction
3583,75535687,1987.0,0.6849830728895778,2,12,/official6pack/basic-idea-with-xgboost-hyperparameters-684,Google Brain - Ventilator Pressure Prediction
3584,75535687,1987.0,0.6849830728895778,2,12,/official6pack/basic-idea-with-xgboost-hyperparameters-684,Google Brain - Ventilator Pressure Prediction
3585,78711578,2008.0,0.7277779132238903,0,1,/dmitriykolach/some-eda-and-process-visualisation-catboost-preds,Google Brain - Ventilator Pressure Prediction
3586,77524147,2025.0,,0,0,/pradeepmiriyala/google-brain-lung,Google Brain - Ventilator Pressure Prediction
3587,77484643,2033.0,0.8142259689489968,0,6,/msvrao/tscomp,Google Brain - Ventilator Pressure Prediction
3588,75964674,2072.0,1.532398521566224,0,11,/kaitohonda/beginner-lgbm,Google Brain - Ventilator Pressure Prediction
3589,75647357,2076.0,0.9954934794729589,2,9,/mohammadkashifunique/google-brain-xgboost-and-optuna,Google Brain - Ventilator Pressure Prediction
3590,75639084,2095.0,,0,11,/sandeep2812/clustering-google-brain-ventilationpressure,Google Brain - Ventilator Pressure Prediction
3591,76333747,2099.0,4.24519310543536,0,2,/ramkiran55devireddy/ventilator-press-prediction-using-simpleregression,Google Brain - Ventilator Pressure Prediction
3592,76333747,2099.0,1.1564610451310342,0,2,/ramkiran55devireddy/ventilator-press-prediction-using-simpleregression,Google Brain - Ventilator Pressure Prediction
3593,76333747,2099.0,1.1564610451310342,0,2,/ramkiran55devireddy/ventilator-press-prediction-using-simpleregression,Google Brain - Ventilator Pressure Prediction
3594,76601339,2107.0,1.2170945329267138,1,7,/devkhant24/ventilator-pressure-prediction-lgbmregressor,Google Brain - Ventilator Pressure Prediction
3595,77978019,2116.0,,1,4,/shakshyathedetector/brain-ventilator-pressure-prediction,Google Brain - Ventilator Pressure Prediction
3596,78324850,2132.0,,0,0,/luminiel/notebook8c9d56e0a3,Google Brain - Ventilator Pressure Prediction
3597,77475234,2143.0,,4,12,/sudipg411/eda-with-feature-engineering,Google Brain - Ventilator Pressure Prediction
3598,75736282,2186.0,2.0227849060102363,0,6,/abhilashhemaraj/mark-6,Google Brain - Ventilator Pressure Prediction
3599,75913925,2196.0,,0,4,/mlevytskyi/simple-xgboost-randomizedsearchcv,Google Brain - Ventilator Pressure Prediction
3600,76906163,2202.0,2.3040700262441494,1,4,/jueun1617gmailcom/googlebrain-lgbm,Google Brain - Ventilator Pressure Prediction
3601,78468490,2211.0,,2,8,/nehapawar/eda-and-ml-models,Google Brain - Ventilator Pressure Prediction
3602,75632834,2228.0,3.4551314882058626,3,11,/rdboyes/r-eda-and-simple-model,Google Brain - Ventilator Pressure Prediction
3603,80626157,2241.0,,1,5,/deepak915/ventilator-pressure-predictor-hope-it-works-well,Google Brain - Ventilator Pressure Prediction
3604,142884281,2242.0,,0,0,/haozhang607/google-brain-ventilator-pressure-prediction,Google Brain - Ventilator Pressure Prediction
3605,76943591,2245.0,3.697943729342121,0,4,/ashishtop/baseline,Google Brain - Ventilator Pressure Prediction
3606,78440878,2296.0,,0,4,/stpeteishii/ventilator-pressure-prediction-eda,Google Brain - Ventilator Pressure Prediction
3607,76340710,2318.0,,0,4,/mrud17/basic-xgboost-with-gpu-google-brain,Google Brain - Ventilator Pressure Prediction
3608,77261799,2371.0,,2,10,/drcapa/google-brain-starter,Google Brain - Ventilator Pressure Prediction
3609,75641827,2421.0,5.212222243140233,0,5,/pratikskarnik/time-series-lstm-keras,Google Brain - Ventilator Pressure Prediction
3610,77786776,2443.0,5.249531491673241,0,0,/sachin1153/pressure-prediction,Google Brain - Ventilator Pressure Prediction
3611,76675157,2451.0,5.930434200349152,0,2,/kishorthakre/ventilator-pressure-prediction-inference,Google Brain - Ventilator Pressure Prediction
3612,76502297,2483.0,,1,6,/pritiyadavml/neural-network,Google Brain - Ventilator Pressure Prediction
3613,76033474,2497.0,7.547217194072814,7,13,/nicapotato/ventilator-pressure-eda-simple-heuristics,Google Brain - Ventilator Pressure Prediction
3614,76033474,2497.0,7.547217194072814,7,13,/nicapotato/ventilator-pressure-eda-simple-heuristics,Google Brain - Ventilator Pressure Prediction
3615,77854104,2504.0,,0,0,/nevruz/train-lstm-gru-model,Google Brain - Ventilator Pressure Prediction
3616,75672871,2533.0,7.685131676888638,0,8,/tracyporter/ventilator-pytorch-av-linear-regression,Google Brain - Ventilator Pressure Prediction
3617,75736608,2534.0,7.794185698126503,0,5,/theamitnikhade/pressure-predition-gru-tpu-xgboot-cat-lgbm,Google Brain - Ventilator Pressure Prediction
3618,79005628,2550.0,,0,1,/henriqueseschinneto/google-ventilator-models-knn-linear-r-cnn-tcn,Google Brain - Ventilator Pressure Prediction
3619,76073539,2578.0,18.173358571155788,3,20,/yasserhessein/ventilator-pressure-prediction-using-eda-dl,Google Brain - Ventilator Pressure Prediction
3620,78321273,2591.0,,13,37,/mohamedbakrey/ml-for-vpp-pred-by-ml-and-dl,Google Brain - Ventilator Pressure Prediction
3621,77486713,2599.0,,0,6,/grzegorzlippe/ventilator-pressure-prediction-exploration,Google Brain - Ventilator Pressure Prediction
3622,76428219,6.0,18.033894328577272,60,328,/cdeotte/rapids-svr-boost-17-8,PetFinder.my - Pawpularity Contest
3623,80778021,1.0,,0,1,/titericz/openai-clip,PetFinder.my - Pawpularity Contest
3624,85383017,2.0,17.956894147976502,0,3,/ktakita/exp108-inference,PetFinder.my - Pawpularity Contest
3625,81579810,545.0,18.01685129049328,8,13,/drtausamaru/petfinder2-yolov5x-swint1-inference,PetFinder.my - Pawpularity Contest
3626,75481315,983.0,,1,4,/kunihikofurugori/simple-eda-using-pandas-profiling,PetFinder.my - Pawpularity Contest
3627,82827342,906.0,,3,31,/ytakayama/pytorch-baseline-try-to-reproduce-fastai-notebook,PetFinder.my - Pawpularity Contest
3628,80372864,249.0,,0,7,/masaishi/keras-vision-transformer-vit-keras,PetFinder.my - Pawpularity Contest
3629,78929073,149.0,18.99931181003084,0,9,/nischaydnk/swin-inference-384x384-only-images-w-comments,PetFinder.my - Pawpularity Contest
3630,81506232,303.0,,5,46,/reighns/visualizing-convolution-filters,PetFinder.my - Pawpularity Contest
3631,78120225,45.0,29.71547709873296,0,0,/czs1311/infer,PetFinder.my - Pawpularity Contest
3632,83722423,107.0,,0,3,/xinshiwang026/lovely-doggo-with-bonky-fastai-timm-906940,PetFinder.my - Pawpularity Contest
3633,78712547,264.0,,0,1,/tiandaye/find-duplicate-images,PetFinder.my - Pawpularity Contest
3634,85053041,746.0,,1,2,/zoubairkachri/petcount-metada-yolo5x-random-forest-regression,PetFinder.my - Pawpularity Contest
3635,76414673,92.0,,6,101,/chumajin/petfinder-eda-lgbm-for-starter-version,PetFinder.my - Pawpularity Contest
3636,112661830,133.0,,0,0,/bachan/pawpularity-fastai-17-02741-private-lb,PetFinder.my - Pawpularity Contest
3637,85791071,12.0,17.77491078388538,0,1,/kurokurob/infer-of-12th-place-solution,PetFinder.my - Pawpularity Contest
3638,82028591,161.0,20.799617323852008,0,0,/kurmoy/baseline-cnn,PetFinder.my - Pawpularity Contest
3639,82475282,310.0,18.333606999700525,0,1,/pablolarrosa/pf-pytorch-svr,PetFinder.my - Pawpularity Contest
3640,77464435,62.0,18.107366383683825,48,136,/rsmits/effnet-b2-feature-models-catboost,PetFinder.my - Pawpularity Contest
3641,84859687,241.0,17.780505848776517,0,0,/hideyukizushi/petfinder-inf-pre-bscheck64-blend-406-z111-06-04,PetFinder.my - Pawpularity Contest
3642,85231856,49.0,17.793995141868965,0,1,/blankaf/petfinder-fastai-3-inference-best,PetFinder.my - Pawpularity Contest
3643,81324999,1055.0,20.47748115094849,1,4,/taichikakino/resizeman,PetFinder.my - Pawpularity Contest
3644,122584653,113.0,,0,0,/a2015003713/petfinder-swinl224-384ensemble-jointregbin,PetFinder.my - Pawpularity Contest
3645,77664256,93.0,,6,9,/crained/fastai-timm,PetFinder.my - Pawpularity Contest
3646,81921396,1099.0,,0,1,/deeeeeeeplearning/fork-of-petfindder-updated-rules-12ad6c,PetFinder.my - Pawpularity Contest
3647,85841036,207.0,,0,4,/toshihikok/207th-solution,PetFinder.my - Pawpularity Contest
3648,83002328,313.0,,2,8,/ferlockx/cross-validation-17-44-in-fastai-pipeline,PetFinder.my - Pawpularity Contest
3649,84032107,903.0,20.920445550501626,3,14,/abh1jeetpandey/eda-and-efficientnet-for-beginner,PetFinder.my - Pawpularity Contest
3650,78776399,763.0,,3,7,/dailysergey/petfinder-eda-w-b-visualization,PetFinder.my - Pawpularity Contest
3651,87825707,536.0,,0,8,/dwchen/tez-starfish-training,PetFinder.my - Pawpularity Contest
3652,84240118,114.0,,0,2,/ttkagglett/petfinder-cnn-training-for-pseudolabel-2-fastai,PetFinder.my - Pawpularity Contest
3653,83809143,921.0,,0,0,/pengyf0709/pawpularity,PetFinder.my - Pawpularity Contest
3654,76680667,84.0,,3,39,/valleyzw/petfinder-duplicate-images,PetFinder.my - Pawpularity Contest
3655,83493606,68.0,,0,2,/riadalmadani/fast-ai-model-psudolabel,PetFinder.my - Pawpularity Contest
3656,85228430,156.0,,0,3,/lucamassaron/fastai-multiple-seeds,PetFinder.my - Pawpularity Contest
3657,78406525,58.0,,15,27,/dschettler8845/load-efficientnetv2-pretrained-weights-finetune,PetFinder.my - Pawpularity Contest
3658,82661032,332.0,,1,1,/warotjanpinitrat/lovely-doggo-using-rapids-svr-boost,PetFinder.my - Pawpularity Contest
3659,84750171,335.0,17.8237107253045,0,0,/rizkykiky/lovely-doggo-with-bonky-fastai-timm-671671,PetFinder.my - Pawpularity Contest
3660,82155457,336.0,,3,30,/vinayaktiwari28/pawpularity-resnet-predictions-rmse-19-8,PetFinder.my - Pawpularity Contest
3661,84989993,103.0,,0,0,/kotashimomura/fork-of-ens-oofcv,PetFinder.my - Pawpularity Contest
3662,78441338,342.0,18.008143642647703,10,47,/adityasharma01/rapids-svr-boost-17-97,PetFinder.my - Pawpularity Contest
3663,78441338,342.0,18.01417559963663,10,47,/adityasharma01/rapids-svr-boost-17-97,PetFinder.my - Pawpularity Contest
3664,78530956,351.0,,0,6,/sparkyjunior/using-ext-data-stanford,PetFinder.my - Pawpularity Contest
3665,81488993,365.0,17.941933275455025,1,9,/gjhlove/swin-t-effb4,PetFinder.my - Pawpularity Contest
3666,84476216,394.0,20.49859418167554,0,0,/bhuwanchandra11/cnn-work,PetFinder.my - Pawpularity Contest
3667,85590884,175.0,,0,0,/yamash73/petfinder-ensemble,PetFinder.my - Pawpularity Contest
3668,85473073,121.0,,0,3,/malachymoran/the-general,PetFinder.my - Pawpularity Contest
3669,85211041,74.0,18.132881442327328,0,1,/anitho2910/fastai-inference,PetFinder.my - Pawpularity Contest
3670,90036748,202.0,20.52676944237861,1,0,/kun4qi/pawpularity-inference,PetFinder.my - Pawpularity Contest
3671,80056861,200.0,,0,10,/forcewithme/train-multitask-swint-nnhead,PetFinder.my - Pawpularity Contest
3672,77054991,1425.0,22.735818130850387,0,0,/neverlim/petsubmit,PetFinder.my - Pawpularity Contest
3673,80649743,142.0,,0,10,/kozodoi/mean-and-std-of-pet-photos,PetFinder.my - Pawpularity Contest
3674,98960017,250.0,,0,0,/datakite/petfinder-pawpularity-score-using-fast-ai,PetFinder.my - Pawpularity Contest
3675,83534156,13.0,,0,0,/olegsidorshin/petfinder-224,PetFinder.my - Pawpularity Contest
3676,76292982,244.0,,3,36,/danielkorth/quick-pawpularity-eda,PetFinder.my - Pawpularity Contest
3677,78944591,274.0,,2,6,/lazybuttryingfinal/paw-effib4-10fold,PetFinder.my - Pawpularity Contest
3678,83262279,1343.0,,0,1,/markbquant/petfinder-keras-h2o-svr,PetFinder.my - Pawpularity Contest
3679,85200361,177.0,17.843988569757133,0,1,/wuyhbb/pawpularity-ensemble-0112,PetFinder.my - Pawpularity Contest
3680,82262728,320.0,,0,0,/millerrfu/fastai-swin,PetFinder.my - Pawpularity Contest
3681,79372504,327.0,,0,11,/tensorchoko/pet-finder-eda,PetFinder.my - Pawpularity Contest
3682,82156185,129.0,19.30384992681288,0,0,/szlky1234/vit-together,PetFinder.my - Pawpularity Contest
3683,78428515,146.0,,0,2,/guillaumes/petfinder-xgboost-baseline,PetFinder.my - Pawpularity Contest
3684,83794622,287.0,,1,0,/crazycth/clean-petfinder-fastai-kf-10-mixup-the-b-023d09,PetFinder.my - Pawpularity Contest
3685,100678840,65.0,17.898682357547404,2,9,/linuxdex/use-autogluon-to-predict-pet-adoption,PetFinder.my - Pawpularity Contest
3686,82700370,586.0,18.024453322470755,33,268,/tanlikesmath/petfinder-pawpularity-eda-fastai-starter,PetFinder.my - Pawpularity Contest
3687,77343268,296.0,,3,21,/kishalmandal/xgb-pawpularity-lb-20-7119,PetFinder.my - Pawpularity Contest
3688,82630527,281.0,18.84601351987384,0,4,/shuntakinami/inception-resnet-v2-using-keras-tensorflow-b16d0-3,PetFinder.my - Pawpularity Contest
3689,83129685,719.0,17.86405098986074,0,0,/blaneart/inference,PetFinder.my - Pawpularity Contest
3690,82806332,877.0,,0,0,/mmaymay/linearswin,PetFinder.my - Pawpularity Contest
3691,79956140,1286.0,17.955159607325815,0,2,/aishikai/petfinder-fastai-with-dataaugmentation-kfold-10,PetFinder.my - Pawpularity Contest
3692,76378153,428.0,,0,11,/lonnieqin/petfinder-pawpularity-prediction,PetFinder.my - Pawpularity Contest
3693,82574814,437.0,17.90488378179957,0,0,/utshabkumarghosh/pawpularity-top-13,PetFinder.my - Pawpularity Contest
3694,80844455,447.0,,0,0,/vkehfdl1/pawpularity-baseline-efficientnetb0-tf,PetFinder.my - Pawpularity Contest
3695,83121577,463.0,,9,17,/smsajideen/torchlightning-basic-skip-nn-meta-data,PetFinder.my - Pawpularity Contest
3696,75476373,466.0,,0,15,/heyytanay/petfinder-eda-resized-images-224-512,PetFinder.my - Pawpularity Contest
3697,77205818,473.0,18.64927869561453,12,32,/manabendrarout/pawpularity-score-starter-cnn-xgboost-infer,PetFinder.my - Pawpularity Contest
3698,76971409,484.0,,48,176,/usharengaraju/tensorflow-probability-ngboost-w-b,PetFinder.my - Pawpularity Contest
3699,85101110,397.0,18.23770855954091,0,0,/tegetegeracing/1-clean-petfinder-fastai-kf-10-mixup-the-best,PetFinder.my - Pawpularity Contest
3700,75956610,503.0,,1,5,/yazanmajzob/from-tensorflow-multi-input-pet-pawpularity-model,PetFinder.my - Pawpularity Contest
3701,81757556,769.0,,1,1,/tom99763/label-embedding-method-for-label-representation,PetFinder.my - Pawpularity Contest
3702,135652510,826.0,,14,23,/anirudhg15/pawpular-competition-w-fastai-lb-18-0,PetFinder.my - Pawpularity Contest
3703,78747336,811.0,21.889957687544136,0,1,/coldfir3/petfinder-regression-baseline,PetFinder.my - Pawpularity Contest
3704,75930426,835.0,,0,6,/nameytg/train-petfinder-based-on-pytorch,PetFinder.my - Pawpularity Contest
3705,78967400,894.0,,23,114,/subinium/petfinder-i-am-featurefinder-eda-notebook,PetFinder.my - Pawpularity Contest
3706,89637429,253.0,18.04416718574813,0,2,/handudu/tez-swin-ference,PetFinder.my - Pawpularity Contest
3707,79799137,164.0,,0,6,/genichiroshimizu/keras-multi-imput-image-resnet50-meta-nn,PetFinder.my - Pawpularity Contest
3708,101355734,780.0,,4,17,/kimalpha/petfinder-simple-t-sne-fireworks,PetFinder.my - Pawpularity Contest
3709,78960791,854.0,,0,4,/adastraz1/first-glance-pawpularity,PetFinder.my - Pawpularity Contest
3710,80231145,698.0,,0,0,/motono0223/petfinder-tfrecords-regress-classification,PetFinder.my - Pawpularity Contest
3711,76297290,659.0,20.489127457480024,0,1,/yuyuco777/notebook95a9cafa86,PetFinder.my - Pawpularity Contest
3712,82660021,1164.0,,0,0,/llibinn/reswin,PetFinder.my - Pawpularity Contest
3713,80001007,540.0,19.071715165147577,1,3,/hamzaboulahia/pawpularity-participation,PetFinder.my - Pawpularity Contest
3714,82955992,567.0,20.52213481651308,0,1,/harshbansal27/petfinder-using-lgbmregressor-on-meta-data,PetFinder.my - Pawpularity Contest
3715,82519758,571.0,23.6821477280304,0,1,/juliengre/pawpularity-score-efficientnet-feature-engineering,PetFinder.my - Pawpularity Contest
3716,84568186,876.0,,1,2,/hikarumoriya/petfinder-eda-lgbm-predict,PetFinder.my - Pawpularity Contest
3717,85177757,551.0,,0,0,/yassinealouini/segmented-model,PetFinder.my - Pawpularity Contest
3718,79241640,1104.0,,0,0,/ludovicchangeon/pet-finder-eda-catvsdog-regression,PetFinder.my - Pawpularity Contest
3719,85216737,1119.0,19.612984174176464,0,4,/tetsuroasano/xgboost-resnet-googlenet-densenet,PetFinder.my - Pawpularity Contest
3720,84694324,685.0,19.1234275583938,0,6,/ashikshafi/fastai-quick-baseline,PetFinder.my - Pawpularity Contest
3721,76726898,1003.0,18.58935808664716,1,5,/wittmannf/deepfeatx-lightgbm-benchmark,PetFinder.my - Pawpularity Contest
3722,75919686,1751.0,,0,3,/josemauricioneuro/eda-baseline-lgb,PetFinder.my - Pawpularity Contest
3723,84243966,1352.0,,0,0,/mkagglemm/cleardraw,PetFinder.my - Pawpularity Contest
3724,83336343,753.0,,0,1,/tenffe/petfindd-1-trainer-reg,PetFinder.my - Pawpularity Contest
3725,76238777,762.0,,0,3,/jeluisme/basic-stratkfld-lgb-for-meta-features-only,PetFinder.my - Pawpularity Contest
3726,79666394,770.0,,0,3,/rhythmcam/tez-timm-pytorch-simple-image-trainer,PetFinder.my - Pawpularity Contest
3727,76369259,225.0,,0,6,/leventelippenszky/petfinder-eda,PetFinder.my - Pawpularity Contest
3728,76014386,1350.0,,48,434,/phalanx/train-swin-t-pytorch-lightning,PetFinder.my - Pawpularity Contest
3729,83064713,939.0,,0,9,/liqizheng/petfinderabaaba,PetFinder.my - Pawpularity Contest
3730,77550806,411.0,,0,2,/nilavanakilan/petfinder-feature-engineering,PetFinder.my - Pawpularity Contest
3731,80674793,1050.0,,0,4,/jungi21cc/tf-efficientnet-quick-starter-k-fold,PetFinder.my - Pawpularity Contest
3732,78987361,727.0,,0,2,/legolas140/tez-pawpular-swin-ference-revised,PetFinder.my - Pawpularity Contest
3733,80744995,132.0,,2,11,/anjum48/lb-noise-estimation,PetFinder.my - Pawpularity Contest
3734,77281116,791.0,19.97137008289878,2,23,/cascadinglight/clip-prompt-feature-engineering-xgb,PetFinder.my - Pawpularity Contest
3735,82967309,1028.0,18.58861199041607,0,1,/ing37050/effnet-with-yolo,PetFinder.my - Pawpularity Contest
3736,80953595,1033.0,17.963752090128047,0,14,/markerkor/petfindder-updated-rules-cheol-5fold,PetFinder.my - Pawpularity Contest
3737,78868825,1035.0,,0,9,/tsuno0821/petfinder-eda-for-japanese-starter,PetFinder.my - Pawpularity Contest
3738,80513326,1043.0,20.488388586362923,0,0,/mizoru/pawp-subm,PetFinder.my - Pawpularity Contest
3739,77614184,944.0,21.00773553052601,0,6,/seeingtimes/just-regression,PetFinder.my - Pawpularity Contest
3740,78696866,1462.0,,3,4,/yingpengchen/find-duplicate-images,PetFinder.my - Pawpularity Contest
3741,78693994,1385.0,,0,5,/abebe9849/duplicate-images,PetFinder.my - Pawpularity Contest
3742,85149638,18.0,17.963502836081375,5,35,/cpmpml/pet-064,PetFinder.my - Pawpularity Contest
3743,76302516,792.0,,2,6,/rajatranjan/pawpularity-score-infer-simple,PetFinder.my - Pawpularity Contest
3744,81595013,794.0,18.290989618041024,1,8,/nur988/pet-paw,PetFinder.my - Pawpularity Contest
3745,77060920,749.0,,0,7,/showeed/image-check,PetFinder.my - Pawpularity Contest
3746,77149970,905.0,,11,64,/schulta/petfinder-identify-duplicates-and-share-findings,PetFinder.my - Pawpularity Contest
3747,81075512,1381.0,,0,2,/yashuwang/petfinder-pawpularity-contest-part-1,PetFinder.my - Pawpularity Contest
3748,76583281,783.0,,0,1,/nullyousee/predict-the-csv-train,PetFinder.my - Pawpularity Contest
3749,79524790,1261.0,,0,1,/srikanthpotukuchi/understanding-pawpular-model,PetFinder.my - Pawpularity Contest
3750,76976441,1359.0,,6,19,/hongseokho/tf-swin,PetFinder.my - Pawpularity Contest
3751,84495288,1126.0,,1,7,/tanulsingh077/petfinder-compute-oof-cv-with-tta,PetFinder.my - Pawpularity Contest
3752,80379383,751.0,18.85665397940721,24,61,/devkhant24/pretrained-model-efficientnet,PetFinder.my - Pawpularity Contest
3753,79088881,1114.0,,0,2,/mikhailsavin/beginners-pytorch-create-dataloader,PetFinder.my - Pawpularity Contest
3754,82097364,1131.0,20.44262486817116,0,0,/enkrish259/notebook78b8402024,PetFinder.my - Pawpularity Contest
3755,77560694,1346.0,20.5650754465414,0,0,/greatpark94/feature-engineering-with-skorch,PetFinder.my - Pawpularity Contest
3756,79241659,1289.0,,1,8,/sarthakjohnsonprasad/pawpular-pawpularity-eda,PetFinder.my - Pawpularity Contest
3757,78332851,1292.0,18.015139562766315,8,32,/jillanisofttech/pawpularity-contest-with-svr-new-accuracy,PetFinder.my - Pawpularity Contest
3758,78030949,1305.0,20.514858407725683,0,5,/aistraugalait/elasticnet-regression,PetFinder.my - Pawpularity Contest
3759,76597957,1186.0,,2,8,/pranavuikey/pawpularity-efficientnetb0-training,PetFinder.my - Pawpularity Contest
3760,82214813,1223.0,18.027514692623907,0,0,/lewiszhang/swin-t-svr-boost,PetFinder.my - Pawpularity Contest
3761,85485521,1225.0,18.22499883214884,0,0,/ni7san/tez-pawpular-inference-swin-transformer,PetFinder.my - Pawpularity Contest
3762,75996397,1233.0,20.489493857477022,0,0,/alxbkr/pawpularity-lightgbm-metadata-only,PetFinder.my - Pawpularity Contest
3763,79603250,1234.0,,1,3,/sifatshikdar/predict-with-svm,PetFinder.my - Pawpularity Contest
3764,82308226,927.0,,0,1,/hliu6019/swin-t-hliu6019,PetFinder.my - Pawpularity Contest
3765,76462554,1516.0,,0,5,/duongchivinh10998/petfinder-train,PetFinder.my - Pawpularity Contest
3766,78036014,678.0,20.49181939145406,0,2,/hoangpham51/petfinder-votingregressor,PetFinder.my - Pawpularity Contest
3767,81254694,2272.0,19.01710235245642,0,8,/bierone/deep-model-training,PetFinder.my - Pawpularity Contest
3768,80975485,1483.0,,0,2,/kimbyoungwook/tez-pawpular-swin-ference-910,PetFinder.my - Pawpularity Contest
3769,78439886,1487.0,,0,0,/bibhabasumohapatra/regression-of-pawpularity-of-deep-learning,PetFinder.my - Pawpularity Contest
3770,81446569,1489.0,,0,2,/htfosterchen/tez-pawpular-swin-ference,PetFinder.my - Pawpularity Contest
3771,84281907,1450.0,,0,0,/gohweizheng/petfinder-first-cnn-model,PetFinder.my - Pawpularity Contest
3772,77154475,1530.0,18.045885592482527,0,9,/karthikeya14/tez-pawpular-tuning,PetFinder.my - Pawpularity Contest
3773,75466508,1428.0,,8,81,/abhishek/same-old-creating-folds,PetFinder.my - Pawpularity Contest
3774,76217043,1430.0,,4,16,/vincenttu/paw-eda,PetFinder.my - Pawpularity Contest
3775,75684881,1437.0,,0,4,/sawradipsaha/petfinder2021-ultimate-pawerful-eda,PetFinder.my - Pawpularity Contest
3776,78723628,1392.0,,1,3,/quillio/cleanfid-resizer,PetFinder.my - Pawpularity Contest
3777,75642914,1622.0,20.497735119767565,4,36,/currypurin/petfinder-eda-lgb-meta-features-and-img-size,PetFinder.my - Pawpularity Contest
3778,76979267,1680.0,20.751517271183108,2,7,/shikameow/conv2d-net-rmse-0-21-ru-en,PetFinder.my - Pawpularity Contest
3779,83102223,1566.0,18.148444700394247,0,4,/jaipawar/efficientnetb2-stratified-k-fold-image-based-model,PetFinder.my - Pawpularity Contest
3780,76777849,1460.0,,0,7,/alibaba19/fastai-training-pipeline-w-mixup,PetFinder.my - Pawpularity Contest
3781,84516971,1646.0,20.43517021277843,1,2,/max237/pytorch-cnn-from-scratch-no-transfer-learning,PetFinder.my - Pawpularity Contest
3782,82236422,1601.0,20.52592710884956,10,17,/santhoshkumarv/xgboost-model-on-metadata,PetFinder.my - Pawpularity Contest
3783,77316903,1735.0,,0,8,/nayakroshan/pytorch-swin-transformer-folds,PetFinder.my - Pawpularity Contest
3784,82987868,898.0,,0,0,/illustriousdust/tez-pawpular-training,PetFinder.my - Pawpularity Contest
3785,82616456,1801.0,18.257868306250803,10,12,/joatom/petfinder2021-simple-fastai-inference,PetFinder.my - Pawpularity Contest
3786,79023127,1672.0,,0,4,/jtan2231/pet-pawpularity-tf-cnn-5-fold-training,PetFinder.my - Pawpularity Contest
3787,81345361,1687.0,,2,2,/narendra/basic-eda,PetFinder.my - Pawpularity Contest
3788,75880169,1809.0,20.49780132734168,2,19,/ekaterinadranitsyna/xgboost-for-tabular-data,PetFinder.my - Pawpularity Contest
3789,78441773,1627.0,,0,0,/hogehogewhale/simpleeda,PetFinder.my - Pawpularity Contest
3790,75710311,1727.0,,0,8,/reppy4620/fast-ai-efficientnetb0-5fold-training,PetFinder.my - Pawpularity Contest
3791,81410514,1790.0,18.26135439392847,3,8,/niutianyi/swin-t-fold10-224-infer,PetFinder.my - Pawpularity Contest
3792,76939001,1871.0,,3,6,/jackstapleton/d169-baseline-nc-train,PetFinder.my - Pawpularity Contest
3793,75492834,1679.0,,6,21,/ayuraj/interactive-eda-using-w-b-tables,PetFinder.my - Pawpularity Contest
3794,84574763,1700.0,18.32943864821216,0,0,/dsmeena/vision-with-petfinder-using-fastai,PetFinder.my - Pawpularity Contest
3795,81672120,1725.0,20.554284245711475,1,13,/ghadiyaayush/fastai-with-efficientnet-timm-training-inference,PetFinder.my - Pawpularity Contest
3796,84359046,2191.0,19.275516474184297,0,12,/vishalkarangale/inceptionv3-10folds-tensorflow,PetFinder.my - Pawpularity Contest
3797,83449045,1962.0,20.59543999283043,0,0,/milenasokol/pawpularity-contest-simple-cnn-mlp,PetFinder.my - Pawpularity Contest
3798,81314338,1934.0,18.69491090169913,0,4,/tianjunwei/pawpularitydetectorsubmission,PetFinder.my - Pawpularity Contest
3799,77703237,1860.0,23.61670915131408,1,9,/shanmukh05/petfinder-my-flaml-automl,PetFinder.my - Pawpularity Contest
3800,77794666,2023.0,,0,15,/burakbekci/petfinder-finding-duplicates-with-cnn,PetFinder.my - Pawpularity Contest
3801,76272391,1888.0,18.56170868426753,0,5,/leangab/tf-pawpularity-efficientnet-metadata-ensamble,PetFinder.my - Pawpularity Contest
3802,77180761,1897.0,,1,7,/aniketmaurya/pawpular-gradsflow,PetFinder.my - Pawpularity Contest
3803,81326284,2029.0,18.52591660004149,0,0,/spencerbb/notebook1b4993b418,PetFinder.my - Pawpularity Contest
3804,79820301,1922.0,23.578565609413555,0,3,/quantumdamage/petfinder-pawpularity-score-tensorflow,PetFinder.my - Pawpularity Contest
3805,76119812,1925.0,18.56644938894985,0,10,/luongduongminh/tez-petfinder,PetFinder.my - Pawpularity Contest
3806,76301013,1927.0,18.56644938894985,0,1,/lystriving/tez-pawpular-inference-adapted,PetFinder.my - Pawpularity Contest
3807,80782804,1945.0,,0,0,/rilts5/notebookf095c410bb,PetFinder.my - Pawpularity Contest
3808,80782804,1945.0,,0,0,/rilts5/notebookf095c410bb,PetFinder.my - Pawpularity Contest
3809,80782804,1945.0,,0,0,/rilts5/notebookf095c410bb,PetFinder.my - Pawpularity Contest
3810,80247323,2001.0,18.94412392234444,0,5,/dardodel/petfinder-keras-inceptionv3-use-images-only,PetFinder.my - Pawpularity Contest
3811,77032037,1957.0,,0,4,/gbalachandhiran/eda-notebook,PetFinder.my - Pawpularity Contest
3812,79360227,1963.0,,0,1,/anshumansharma002/pawpred,PetFinder.my - Pawpularity Contest
3813,80562953,2091.0,,1,3,/kuposatina/petfinder-starter-pack-basic-idea,PetFinder.my - Pawpularity Contest
3814,80877273,1938.0,,0,0,/zheyiwangriceu/notebook94d224bf3b,PetFinder.my - Pawpularity Contest
3815,83055453,2020.0,18.78294618509661,0,0,/lishaoleung/just-a-joke,PetFinder.my - Pawpularity Contest
3816,75580906,1901.0,20.477372808112754,3,32,/carlolepelaars/petfinder2021-eda-baseline,PetFinder.my - Pawpularity Contest
3817,82974375,2017.0,18.914825987786408,0,0,/zzt0814/just-a-joke,PetFinder.my - Pawpularity Contest
3818,79865892,2062.0,,1,8,/christodoulos/petfinder-transfer-learning-w-meta-features,PetFinder.my - Pawpularity Contest
3819,77667783,2175.0,,0,4,/bfitzpa5/pawpularity-baseline-cnn-with-keras,PetFinder.my - Pawpularity Contest
3820,84051987,2104.0,,0,3,/colander/pawpularity-mvi,PetFinder.my - Pawpularity Contest
3821,84671926,2010.0,19.38346448158488,0,0,/romanresner/pawpularity-contest-keras-efficientnetb6,PetFinder.my - Pawpularity Contest
3822,77579744,2212.0,,2,4,/vijayshankar756/petsinception,PetFinder.my - Pawpularity Contest
3823,77122353,2126.0,20.505725873366124,5,12,/shakshyathedetector/petfinder-my-pawpularity-contest,PetFinder.my - Pawpularity Contest
3824,76119959,2045.0,,3,11,/tarunbisht11/find-a-pet-with-lightning-speed-wandb,PetFinder.my - Pawpularity Contest
3825,82337953,1893.0,,2,3,/harveenchadha/why-this-scores-17-33-on-cv,PetFinder.my - Pawpularity Contest
3826,84801779,2252.0,,0,0,/sagarikajadon/pawpreds-efficientnetb3-rmse-training,PetFinder.my - Pawpularity Contest
3827,77401480,2052.0,20.028889750868995,12,36,/abdallahmahmoud/images-effnet-val-19-78,PetFinder.my - Pawpularity Contest
3828,80686361,2081.0,,0,0,/kk99807/pawpularity-eda,PetFinder.my - Pawpularity Contest
3829,79387124,1873.0,18.89746783025161,0,6,/jordan75/efficient-net-transfer-learning-18-8,PetFinder.my - Pawpularity Contest
3830,80775723,2142.0,18.83379612331101,0,1,/sakkarinpoolsuk/final-model-popularity-prediction-yakdaia-group,PetFinder.my - Pawpularity Contest
3831,76483899,2187.0,,2,10,/larsmadsen/breed-is-correlated-with-pawpularity-it-seems,PetFinder.my - Pawpularity Contest
3832,75787657,2048.0,,1,10,/kooose/search-for-similar-annotation-data,PetFinder.my - Pawpularity Contest
3833,84591450,2197.0,18.86661430967608,0,1,/krooz0/resnet-features-and-stacked-regressions,PetFinder.my - Pawpularity Contest
3834,83984980,2154.0,,2,11,/sender1999/resnet50-pretrained-3stratifiedkfold,PetFinder.my - Pawpularity Contest
3835,77719325,2115.0,20.63818252441582,0,0,/phannguyenthe/tf-pawpularity-cnn,PetFinder.my - Pawpularity Contest
3836,79436105,2157.0,,0,0,/johnjdavisiv/demo-of-cute-dog-model,PetFinder.my - Pawpularity Contest
3837,84744025,2082.0,,0,0,/claudiobonetta/claudio-train,PetFinder.my - Pawpularity Contest
3838,76222359,2123.0,,0,7,/chiragtagadiya/randomforest-regression-baseline-no-image-feature,PetFinder.my - Pawpularity Contest
3839,81205729,1951.0,18.94630404560823,1,0,/parshv2521/parshv,PetFinder.my - Pawpularity Contest
3840,81280570,2102.0,18.95890558002093,0,4,/lokeshsaipureddi/eda-transfer-learning-using-pretrained-weights,PetFinder.my - Pawpularity Contest
3841,80483206,2106.0,18.96039676369585,0,0,/flukec/pet-paw,PetFinder.my - Pawpularity Contest
3842,76655980,2215.0,,0,7,/bhavesjain/pawpularity-train,PetFinder.my - Pawpularity Contest
3843,77585302,2251.0,20.563363700441744,3,13,/tqrahman/basic-cnn-with-tensorflow-v2,PetFinder.my - Pawpularity Contest
3844,81569846,2302.0,,0,0,/dmitryalexanderov/notebook03149460c2,PetFinder.my - Pawpularity Contest
3845,85791401,2314.0,,4,17,/ryuodan/cnn-tensorflow-approach,PetFinder.my - Pawpularity Contest
3846,77339633,2237.0,,0,0,/arunamenon/pawpularity-prediction,PetFinder.my - Pawpularity Contest
3847,77919349,2159.0,,0,3,/stmohd/petfnder-cnn-efficientnet-basic-model-average,PetFinder.my - Pawpularity Contest
3848,83909998,2292.0,,0,2,/hoomanmisaghi/keras-resnet-101,PetFinder.my - Pawpularity Contest
3849,75728233,2158.0,,2,10,/josepc/pawpularity-efficient-net-b0-metadata,PetFinder.my - Pawpularity Contest
3850,84335944,2295.0,,0,0,/gokhankesler/simple-silly-efficientnetb0,PetFinder.my - Pawpularity Contest
3851,77645577,2211.0,,0,0,/kiranpradeep1811/preprocessing-pawfinder,PetFinder.my - Pawpularity Contest
3852,84442583,2296.0,19.18806403825696,0,0,/shankard/resnet-machine-learning,PetFinder.my - Pawpularity Contest
3853,77243595,2241.0,33.41800786923764,0,0,/ajiiscbanglore/cutepet-facenet-nn,PetFinder.my - Pawpularity Contest
3854,100857219,2222.0,,0,0,/temirlankaliyev/working-efficient-net-with-gpu,PetFinder.my - Pawpularity Contest
3855,76050259,2366.0,19.81539717483236,2,9,/miklgr500/petfinder-my-effb0-catalyst-timms-only-image,PetFinder.my - Pawpularity Contest
3856,76342478,2276.0,20.530719171723177,1,7,/adityachakma/starter-keras-meta-data-mobilenetv2,PetFinder.my - Pawpularity Contest
3857,77430264,2359.0,,1,1,/davidhammond/pawpularity-metadata-eda,PetFinder.my - Pawpularity Contest
3858,80518088,2227.0,20.48467922546852,0,2,/saaries/method1,PetFinder.my - Pawpularity Contest
3859,81008000,2231.0,20.496368102916943,1,1,/msueconalinaivanova/msuecon21-alina-ivanova,PetFinder.my - Pawpularity Contest
3860,84652267,2305.0,19.38771174715384,8,14,/djagatiya/pawpularity-pytorch-training,PetFinder.my - Pawpularity Contest
3861,80240603,2220.0,20.495013605279016,0,3,/agileteam/petfinder-simple-baseline-kr,PetFinder.my - Pawpularity Contest
3862,76374148,2380.0,,1,12,/sandy4perception/pet-finder-eda,PetFinder.my - Pawpularity Contest
3863,96056060,2376.0,,0,0,/florianpierre/petfinder,PetFinder.my - Pawpularity Contest
3864,81415883,2420.0,20.72380957922899,0,1,/achan31/modified-tutorial-part-3-cnn-image-modeling-1,PetFinder.my - Pawpularity Contest
3865,77229535,2361.0,19.63705382177818,0,2,/uestchzx/notebookd97ba6b497,PetFinder.my - Pawpularity Contest
3866,81494312,2406.0,,0,1,/tianyuq1/notebook476905e203,PetFinder.my - Pawpularity Contest
3867,83342162,2334.0,42.97356881546391,0,3,/avirdee/supplementary-model-photo-metadata,PetFinder.my - Pawpularity Contest
3868,81068544,2360.0,19.859638352467137,0,0,/wcmlgb/notebooke6ea7cbd34,PetFinder.my - Pawpularity Contest
3869,82913622,2427.0,,0,2,/goodgoodstud1/resnet50-predictions,PetFinder.my - Pawpularity Contest
3870,82736909,2428.0,,0,0,/wanweih/resnet-predictions,PetFinder.my - Pawpularity Contest
3871,81566492,2442.0,,0,3,/vladlee/pawpularity-lgbm-tabonly-optuna,PetFinder.my - Pawpularity Contest
3872,77154781,2465.0,,0,6,/priyaduttbhatt/feature-engineering-create-dog-cat-label,PetFinder.my - Pawpularity Contest
3873,95268918,2460.0,,0,1,/michaelcarrasco4/pawpularity-prediction-using-yolov5,PetFinder.my - Pawpularity Contest
3874,83412844,2461.0,20.52371481110921,0,8,/suryadeepti/find-my-pet-using-csv,PetFinder.my - Pawpularity Contest
3875,76110546,2394.0,20.29652582171168,0,0,/kudasovdmitriy/petfinder-v4,PetFinder.my - Pawpularity Contest
3876,76277574,2510.0,,0,13,/yaniv256/tensorflow-multi-input-pet-pawpularity-model,PetFinder.my - Pawpularity Contest
3877,79638224,2480.0,20.44492815207224,1,7,/adernild/pawpularity-ensemble-cnn,PetFinder.my - Pawpularity Contest
3878,84837538,2516.0,20.485661008124893,0,9,/egorphysics/catboost-hyperopt-on-meta-features,PetFinder.my - Pawpularity Contest
3879,80550052,2463.0,21.53881440397232,0,1,/hemantbhartiya/notebook9e7b70465c,PetFinder.my - Pawpularity Contest
3880,79131199,2750.0,20.85416062958804,0,3,/ryanlambert/pawpularity,PetFinder.my - Pawpularity Contest
3881,76643212,2743.0,,0,3,/sidharkal/petfinder-ml-regressor,PetFinder.my - Pawpularity Contest
3882,81268360,2536.0,,2,6,/fairyandherhat/example-with-pictures,PetFinder.my - Pawpularity Contest
3883,78785141,2838.0,20.607533578344626,0,3,/pratikskarnik/resnet-regressor,PetFinder.my - Pawpularity Contest
3884,76258459,2600.0,20.491883637441497,0,6,/purvansharora/petfinder-pawpularity-competition,PetFinder.my - Pawpularity Contest
3885,81220009,2832.0,20.47304637923304,1,7,/artyomgrishanov/artyomgrishanovmsu2021,PetFinder.my - Pawpularity Contest
3886,76160615,2544.0,,4,9,/vivmankar/understanding-the-problem-eda,PetFinder.my - Pawpularity Contest
3887,75988294,2699.0,20.483493779850992,4,6,/stpeteishii/petfinder-pawpularity-metadata-lgbm,PetFinder.my - Pawpularity Contest
3888,76035348,2614.0,,1,12,/k589k589/lightgbm-eda,PetFinder.my - Pawpularity Contest
3889,81570752,3092.0,,4,7,/pandalovedeep/pet-pawpularity-using-inceptionv3-and-xgboost,PetFinder.my - Pawpularity Contest
3890,81202235,2502.0,20.47681345502956,6,17,/samuelcortinhas/pawpularity-eda-rf-model,PetFinder.my - Pawpularity Contest
3891,83592201,2509.0,,0,9,/pythonash/how-to-handle-dataset-for-beginners,PetFinder.my - Pawpularity Contest
3892,76148524,2592.0,20.493143834407665,0,5,/morenovanton/pawpularity-flaml-lightgbm,PetFinder.my - Pawpularity Contest
3893,75921638,2630.0,,1,2,/crpatel123/petfinder-eda-let-s-find-home-for-animals,PetFinder.my - Pawpularity Contest
3894,79115477,2713.0,,4,32,/hotsonhonet/petfinder-predictions-using-metadata,PetFinder.my - Pawpularity Contest
3895,78458789,2530.0,20.516708630446946,0,1,/blazer007/f-net-petfinder,PetFinder.my - Pawpularity Contest
3896,83678125,2677.0,,0,0,/wuhsinwei/notebook68cdcfe411,PetFinder.my - Pawpularity Contest
3897,84772315,2494.0,20.50215479708873,0,5,/nikhilsatani/petfinder,PetFinder.my - Pawpularity Contest
3898,82230291,2695.0,20.763165049949126,0,0,/conswang/new-picture-data-notebook,PetFinder.my - Pawpularity Contest
3899,75738480,2805.0,20.482963325043304,0,5,/drscarlat/pawpularity-keras-image-and-tabular-features,PetFinder.my - Pawpularity Contest
3900,85062963,2574.0,20.56507142674005,1,1,/nohrud/pawpularity-challenge-svr-lightgbm-deeplearning,PetFinder.my - Pawpularity Contest
3901,76778150,2616.0,,0,4,/elemento/petfinder-vgg16-mlp,PetFinder.my - Pawpularity Contest
3902,75853862,2613.0,20.505747372640226,0,13,/kaushal2896/petfinder-my-initial-eda-mean-baseline,PetFinder.my - Pawpularity Contest
3903,109061130,2981.0,,17,145,/tanmay111999/image-classification-vgg16-ml-algorithms,PetFinder.my - Pawpularity Contest
3904,79267142,2532.0,20.48648363598379,0,3,/ajaysingh04/petfind,PetFinder.my - Pawpularity Contest
3905,78867972,2982.0,20.487555129078576,0,0,/felipeesc/petfinder,PetFinder.my - Pawpularity Contest
3906,81310323,2684.0,27.90165089198996,0,0,/yushimaeno/submissionflow,PetFinder.my - Pawpularity Contest
3907,76082131,2566.0,,5,6,/chublax/beginner-s-attempt-pet-popularity-v0-03,PetFinder.my - Pawpularity Contest
3908,84317590,2590.0,,1,11,/ccaitlum/pet-pawpularity-regression-with-cnn,PetFinder.my - Pawpularity Contest
3909,75852015,2889.0,,1,4,/osvaldomx/first-intent-pawpularity,PetFinder.my - Pawpularity Contest
3910,76295530,2531.0,,9,12,/oguzhansahin/meta-features-xgboost-lightgbm-catboost-optuna,PetFinder.my - Pawpularity Contest
3911,82636174,2674.0,20.49004821828081,0,1,/spike8086/petfinder,PetFinder.my - Pawpularity Contest
3912,80366875,2788.0,20.491001441728024,1,4,/wltjd54/petfinder-dpark,PetFinder.my - Pawpularity Contest
3913,81873023,2576.0,,0,7,/alijan21/eda-machine-learning-for-pawpularity,PetFinder.my - Pawpularity Contest
3914,81572627,2704.0,20.545551645634912,4,19,/junjitakeshima/beginner-s-try-lgbm-cnn-eng,PetFinder.my - Pawpularity Contest
3915,82657153,2723.0,20.49189414356974,0,6,/matthieubritoantunes/petfinder-pawpularity-score-baseline-tabular-data,PetFinder.my - Pawpularity Contest
3916,81450242,2579.0,20.507739294346194,5,5,/shringi7/pawpularity-lazy-version,PetFinder.my - Pawpularity Contest
3917,77451749,2720.0,20.491977491456865,0,1,/sarang210/pet-finder-metadata-regression-score-20-49,PetFinder.my - Pawpularity Contest
3918,79447642,2666.0,,0,7,/esratmaria/petfinder-pawpularity-prediction-eda,PetFinder.my - Pawpularity Contest
3919,78232034,2539.0,20.49332340850165,0,4,/apurvsj/first-attempt-linreg-xgb-gbr,PetFinder.my - Pawpularity Contest
3920,80323760,2602.0,,0,1,/manojkumars00/petfinder-pawpularity,PetFinder.my - Pawpularity Contest
3921,77968105,2655.0,20.49368464193253,0,0,/nonnontra/mr-faruk-non-petffinder,PetFinder.my - Pawpularity Contest
3922,81050480,2709.0,,1,19,,PetFinder.my - Pawpularity Contest
3923,76142288,2626.0,20.494527676622376,1,4,/mayur7garg/pawpularity-eda-and-naive-linear-model,PetFinder.my - Pawpularity Contest
3924,75975637,2538.0,20.495531390576204,2,6,/joeywonpark/lightgbm-puppy,PetFinder.my - Pawpularity Contest
3925,75975637,2538.0,20.50497064360936,2,6,/joeywonpark/lightgbm-puppy,PetFinder.my - Pawpularity Contest
3926,79152077,2819.0,21.096152439940848,0,1,/egorsheremetov3/meta-features-models,PetFinder.my - Pawpularity Contest
3927,83264540,2777.0,20.50081820370057,2,4,/ahmadabdbutt/simple-pawpularity-rf-adaboost-gb-xgb-voting,PetFinder.my - Pawpularity Contest
3928,83264540,2777.0,20.50081820370057,2,4,/ahmadabdbutt/simple-pawpularity-rf-adaboost-gb-xgb-voting,PetFinder.my - Pawpularity Contest
3929,82976518,3054.0,20.53482712983429,0,6,/yitianru/pet-finder-noob-me-learning-cnn,PetFinder.my - Pawpularity Contest
3930,79042533,2760.0,20.50907692334432,1,0,/takara0515/notebook4d8db1b735,PetFinder.my - Pawpularity Contest
3931,88448317,2862.0,,1,2,/marcuscheong/pawpularity-contest,PetFinder.my - Pawpularity Contest
3932,78711909,2915.0,20.53340436196548,0,7,/theamitnikhade/petfinder-my-pawpularity-contest,PetFinder.my - Pawpularity Contest
3933,85741390,2912.0,,0,0,/pranjalchatterjee/cnn-rf-evaluating-pet-pawpularity-petfinder-my,PetFinder.my - Pawpularity Contest
3934,81009194,2929.0,20.514398622704142,0,0,/mraihanfaa/notebooka20722f5d1,PetFinder.my - Pawpularity Contest
3935,81009194,2929.0,20.514398622704142,0,0,/mraihanfaa/notebooka20722f5d1,PetFinder.my - Pawpularity Contest
3936,81014282,2933.0,,0,0,/maulanafadilah/assesment2-6701191022,PetFinder.my - Pawpularity Contest
3937,81042175,2936.0,20.514398622704142,0,1,/rezarizkyrachmansyah/notebook549bb671df,PetFinder.my - Pawpularity Contest
3938,81045205,2938.0,20.514398622704142,0,0,/meizirpnababan/notebook328d5a6cb8,PetFinder.my - Pawpularity Contest
3939,81155523,2939.0,20.514398622704142,0,0,/dindaputriwidyadhari/dinda-putri-widyadhari-6701194059,PetFinder.my - Pawpularity Contest
3940,81161960,2940.0,20.514398622704142,0,1,/fahriel/fahriel,PetFinder.my - Pawpularity Contest
3941,81170042,2941.0,20.514398622704142,0,0,/yusufmuhamad/notebook595b180c8f,PetFinder.my - Pawpularity Contest
3942,84064112,3065.0,,0,2,/lsimulik/pawpets,PetFinder.my - Pawpularity Contest
3943,83289643,2967.0,,0,5,/ahmetdadak/petfinder-pytorch,PetFinder.my - Pawpularity Contest
3944,81182369,3020.0,30.37886728357713,3,16,/patonoide/basic-keras-cnn-with-datagenerator,PetFinder.my - Pawpularity Contest
3945,84523061,2990.0,20.519767997073664,0,0,/dheerendrachouhan/concatenation-of-mlp-and-cnn,PetFinder.my - Pawpularity Contest
3946,85475169,3126.0,22.429627043831864,0,3,/arturszczesniak/pawpularitycontest,PetFinder.my - Pawpularity Contest
3947,89712779,3035.0,,45,229,/alexteboul/tutorial-part-1-eda-for-beginners,PetFinder.my - Pawpularity Contest
3948,83831225,2910.0,20.682688060096112,0,0,/saraswatitiwari/petfinder-my-pawpularity-contest,PetFinder.my - Pawpularity Contest
3949,75689593,3043.0,,0,6,/soumochatterjee/startingwith-efficientnet-easy,PetFinder.my - Pawpularity Contest
3950,78854646,3016.0,,0,5,/pteridin/exploratory-analysis-and-glm-fit-r,PetFinder.my - Pawpularity Contest
3951,83972044,3114.0,,0,5,/demko1/pet-finder-my-nn-v2,PetFinder.my - Pawpularity Contest
3952,76270203,3090.0,20.585511949260844,11,18,/faridtaghiyev/pawpularity-regression-on-several-models,PetFinder.my - Pawpularity Contest
3953,76446216,3137.0,,1,5,/skoushik/simple-random-forest-approach,PetFinder.my - Pawpularity Contest
3954,83957320,3177.0,20.56377826650637,0,4,/arcsinx/myfirstmodel,PetFinder.my - Pawpularity Contest
3955,82264571,3029.0,20.56887882609538,0,0,/p1a2v3e4l5/final-version-dm-leo,PetFinder.my - Pawpularity Contest
3956,82219931,3172.0,24.250860073344324,0,0,/xiaoxiwang17/msuecon21-wangxiaoxi,PetFinder.my - Pawpularity Contest
3957,80097784,3026.0,,0,2,/taryll/petfinder-pawpularity-prediction,PetFinder.my - Pawpularity Contest
3958,77049073,3164.0,20.583067493660405,1,11,/beezus666/tweedie-and-lgbm-tuning,PetFinder.my - Pawpularity Contest
3959,82278203,3044.0,20.59404173845545,0,0,/haoyuguan/notebookd4357d4e13,PetFinder.my - Pawpularity Contest
3960,82504113,3099.0,20.60877137518188,0,0,/diazmath/pet-finder,PetFinder.my - Pawpularity Contest
3961,81840374,3203.0,20.6114243416654,0,0,/nikhilkagitaumass/resnet50,PetFinder.my - Pawpularity Contest
3962,75897454,3198.0,20.61781323674301,0,4,/niklausparcell/xgb-shap-explainer-train-and-test,PetFinder.my - Pawpularity Contest
3963,78458321,3236.0,,0,6,/ransakaravihara/petfinder-my-pytorch-lightning-vgg,PetFinder.my - Pawpularity Contest
3964,78044102,2834.0,,1,3,/sanjeevsahu/eda-and-modelling-beginner-intermediate,PetFinder.my - Pawpularity Contest
3965,95293279,2835.0,,0,3,/jasonnonstop10/petfinder,PetFinder.my - Pawpularity Contest
3966,83787677,3263.0,20.682688060096112,2,4,/vanchachanell/pawpularity-eda-some-models,PetFinder.my - Pawpularity Contest
3967,76170947,3270.0,,2,9,/drcapa/petfinder-my-starter,PetFinder.my - Pawpularity Contest
3968,83191715,3283.0,,7,1,/kaicho0504/data-arrange,PetFinder.my - Pawpularity Contest
3969,87823979,3217.0,,0,0,/danielpleus/pet-finder-cnn-tabular-data-in-single-nn,PetFinder.my - Pawpularity Contest
3970,81166527,3249.0,20.725921820779664,0,2,/mihsandf/6701190098-ichsan,PetFinder.my - Pawpularity Contest
3971,80462461,3287.0,20.781883781791624,8,24,/ankitkalauni/pet-finder-noob-me-learning-cnn,PetFinder.my - Pawpularity Contest
3972,81173811,3254.0,20.7843567589594,0,2,/faisalbahri/petfinder-6701193069,PetFinder.my - Pawpularity Contest
3973,84918224,3247.0,20.78516964710523,0,2,/dipikajiandani/pawpularity-eda-and-tensorflow-keras,PetFinder.my - Pawpularity Contest
3974,77876666,3215.0,,1,4,/batprem/01-keras-images-model-poc,PetFinder.my - Pawpularity Contest
3975,80482068,3265.0,20.85652034128812,0,0,/kxndxkxvw/pawpularity-version-secret,PetFinder.my - Pawpularity Contest
3976,84189557,3259.0,,0,3,/abhisheksrathore/pawfinder-custom-keras-class-and-model-training,PetFinder.my - Pawpularity Contest
3977,76776905,3327.0,,2,5,/sabzero/explore-sample-images-target-and-meta-data,PetFinder.my - Pawpularity Contest
3978,84202552,3295.0,,1,2,/kathleenlee/petfinder-pawpularity,PetFinder.my - Pawpularity Contest
3979,75481193,3294.0,22.324511321562788,2,8,/ranjeetshrivastav/pawpularity-contest-xception,PetFinder.my - Pawpularity Contest
3980,77062981,3292.0,,3,2,/peace1019/petfinder-dot-my-v1,PetFinder.my - Pawpularity Contest
3981,81154064,3330.0,21.1315103993212,0,0,/beningramadanmk/petfinder-6701194006,PetFinder.my - Pawpularity Contest
3982,81157982,3331.0,21.1315103993212,0,0,/ichsan759/petfinder-6701190098,PetFinder.my - Pawpularity Contest
3983,77417035,3315.0,,0,1,/ashkash247/pawpular-eda,PetFinder.my - Pawpularity Contest
3984,78868295,3311.0,21.700131493467243,2,16,/ted0071/petfinder-image-cnn-meta-nn,PetFinder.my - Pawpularity Contest
3985,80265156,3298.0,21.147391518784605,0,3,/samu2505/petfinder-zero,PetFinder.my - Pawpularity Contest
3986,84596056,3317.0,21.242145576569715,0,0,/sourabhwarrier/pawpularity,PetFinder.my - Pawpularity Contest
3987,76063389,3333.0,,2,11,/ritesh2000/pytorch-petfinder-fastai-baseline-w-b,PetFinder.my - Pawpularity Contest
3988,81544816,3310.0,21.399436606252205,0,0,/matkobarbic/pawpularity-effnet,PetFinder.my - Pawpularity Contest
3989,80565967,3343.0,22.19951721526173,0,3,/seungsikchoi/petfinder,PetFinder.my - Pawpularity Contest
3990,80565967,3343.0,21.393584190907195,0,3,/seungsikchoi/petfinder,PetFinder.my - Pawpularity Contest
3991,80565967,3343.0,21.62141168542752,0,3,/seungsikchoi/petfinder,PetFinder.my - Pawpularity Contest
3992,75579010,3347.0,,0,0,/anaselmasry/tez-pawpular-inference-f5a097,PetFinder.my - Pawpularity Contest
3993,80492462,3358.0,24.493894069666936,0,0,/tany1404/basic-cnn,PetFinder.my - Pawpularity Contest
3994,81028592,3361.0,,1,2,/minsingjinkinghee/kinghee-minsing-jin-tabluar-and-cnn,PetFinder.my - Pawpularity Contest
3995,76014987,3365.0,,0,11,/sheepb/keras-api,PetFinder.my - Pawpularity Contest
3996,76383212,3357.0,21.70186446018871,1,7,/abhishekkumarsaini/pet-finder-noobie,PetFinder.my - Pawpularity Contest
3997,76139889,3385.0,,0,14,/vaibhavrmankar/let-s-see-problem-statement-eda-approaches,PetFinder.my - Pawpularity Contest
3998,80667562,3387.0,,0,0,/noppanutboonrueng/notebookd10bc4c13c,PetFinder.my - Pawpularity Contest
3999,80106052,3389.0,,0,0,/ohbewise/pawpularity-contest,PetFinder.my - Pawpularity Contest
4000,79610068,3395.0,23.034432597748022,0,5,/akuppps/pawpularity-starter-book-overanalyzed,PetFinder.my - Pawpularity Contest
4001,80977435,3450.0,24.180358434494263,0,0,/hyunwookkwon2/korean-pawpularity-baseline-efficientne-6215bb,PetFinder.my - Pawpularity Contest
4002,81655526,3454.0,,2,4,/takoai/simplecnn,PetFinder.my - Pawpularity Contest
4003,78990533,3479.0,,0,2,/ferrariic/submission,PetFinder.my - Pawpularity Contest
4004,78549143,3480.0,29.332870780227807,0,6,/tharunreddy/pawpular-kickoff-keras,PetFinder.my - Pawpularity Contest
4005,82987040,3481.0,29.744734599348646,0,1,/bibhuti93/pawpularity-prediction,PetFinder.my - Pawpularity Contest
4006,75735339,3486.0,,0,4,/blackitten13/pawpularity-eda-small-and-fast,PetFinder.my - Pawpularity Contest
4007,78125122,3489.0,,0,0,/ravinderkotwal/petfinder2021-eda-baseline,PetFinder.my - Pawpularity Contest
4008,79224927,3498.0,,0,1,/mosugi/petfinder2,PetFinder.my - Pawpularity Contest
4009,80006716,3499.0,,2,18,/sagnik1511/petfinder-pytorch-dnn,PetFinder.my - Pawpularity Contest
4010,84096563,3505.0,,0,2,/hasegawayoshio/notebook7d436da372,PetFinder.my - Pawpularity Contest
4011,81945266,3514.0,43.41358832255607,0,0,/ljaem10/competition-pawpularity-jae,PetFinder.my - Pawpularity Contest
4012,77759386,2.0,0.8559210111984614,0,5,/vkonstantakos/tps-october-mljar,Tabular Playground Series - Oct 2021
4013,77828341,13.0,0.8565291378923094,0,21,/joecooper/tsp-single-xgboost-model,Tabular Playground Series - Oct 2021
4014,77309896,4.0,,0,6,/motchan/tps-oct-target-abs-correlation-coefficient,Tabular Playground Series - Oct 2021
4015,76105013,10.0,0.8560761098832098,8,13,/dlaststark/tps-1021-la-dee-da,Tabular Playground Series - Oct 2021
4016,76105013,10.0,0.8561654164355382,8,13,/dlaststark/tps-1021-la-dee-da,Tabular Playground Series - Oct 2021
4017,76105013,10.0,0.8562731482571835,8,13,/dlaststark/tps-1021-la-dee-da,Tabular Playground Series - Oct 2021
4018,76105013,10.0,0.8562839914041679,8,13,/dlaststark/tps-1021-la-dee-da,Tabular Playground Series - Oct 2021
4019,76407120,5.0,,14,23,/pourchot/neural-network-2-inputs-numerical-categorical,Tabular Playground Series - Oct 2021
4020,77674278,19.0,0.8563539098208476,3,24,/mehrankazeminia/1-tps-oct-21-lgbm-auc-evaluation,Tabular Playground Series - Oct 2021
4021,87171646,21.0,,31,59,/kavehshahhosseini/tps-oct-2021-pca-and-kmeans-feature-eng,Tabular Playground Series - Oct 2021
4022,77140781,25.0,,5,6,/joanyeo/tps-oct-2021-eda,Tabular Playground Series - Oct 2021
4023,76183479,16.0,,0,2,/data2science/tps-10-21-yet-another-simple-eda,Tabular Playground Series - Oct 2021
4024,78250532,180.0,0.8564267272372393,0,2,/adityasharma01/tps-single-xgboost-model,Tabular Playground Series - Oct 2021
4025,76903698,24.0,0.8458957721597441,4,14,/vamsikrishnab/tps-oct-cnn,Tabular Playground Series - Oct 2021
4026,78089541,9.0,,0,16,/adamwurdits/15-lgbms-trained-on-20-seeds-dataset-included,Tabular Playground Series - Oct 2021
4027,123236820,14.0,,12,37,/maxdiazbattan/tps-2021-kfold-oom-solution,Tabular Playground Series - Oct 2021
4028,78383504,131.0,,7,22,,Tabular Playground Series - Oct 2021
4029,76392221,79.0,,0,7,/kalaikumarr/tps-oct-21-22-models-comparision,Tabular Playground Series - Oct 2021
4030,77560937,37.0,0.8457157015546801,11,28,/mhslearner/tps-oct-eda-tabnet,Tabular Playground Series - Oct 2021
4031,77895189,41.0,,4,8,/harshjhunjhunwala/xgbm-histgbm-featureengineering-gridsearch,Tabular Playground Series - Oct 2021
4032,77821995,59.0,0.8561974910451581,16,46,/hamzaghanmi/tps-oct-lightgbm,Tabular Playground Series - Oct 2021
4033,76087261,76.0,,2,15,/towhidultonmoy/eda-tabular-playground-series-oct-21,Tabular Playground Series - Oct 2021
4034,89684207,63.0,,6,32,/kalilurrahman/tps-oct-2021-eda-and-analysis,Tabular Playground Series - Oct 2021
4035,76090229,126.0,0.8553847182532405,2,30,/shivansh002/october-madness,Tabular Playground Series - Oct 2021
4036,77841044,129.0,0.8563213295763945,0,2,/omarvivas/lgbm-tpsoct-v1,Tabular Playground Series - Oct 2021
4037,76244680,32.0,,10,30,/raahulsaxena/tps-oct-21-data-check-and-feature-engineering,Tabular Playground Series - Oct 2021
4038,76096898,130.0,0.8548323654016525,6,13,/mohammadkashifunique/tsp-oct-eda-autoviz-histgradientboost,Tabular Playground Series - Oct 2021
4039,76093147,49.0,0.8559233789615767,4,9,/azzamradman/tps-10-single-catboost-optimization,Tabular Playground Series - Oct 2021
4040,76093147,49.0,0.8559233789615767,4,9,/azzamradman/tps-10-single-catboost-optimization,Tabular Playground Series - Oct 2021
4041,76412484,55.0,,3,9,/rhythmcam/automl-pycaret-tps-oct-2021,Tabular Playground Series - Oct 2021
4042,77108796,64.0,,4,11,/zhangcheche/tabular-oct-xgboost-optuna,Tabular Playground Series - Oct 2021
4043,78441673,150.0,0.849407908710831,7,22,/fusioncenter/skip-connection-neural-network-architecture,Tabular Playground Series - Oct 2021
4044,91204766,57.0,,4,11,/edrickkesuma/explanatory-votingclassifier-power-averaging,Tabular Playground Series - Oct 2021
4045,76200691,143.0,,5,13,/hardyxu52/tps-oct-2021-reduce-memory-usage-but-faster,Tabular Playground Series - Oct 2021
4046,76778566,98.0,0.8565490240622676,6,44,/ankitkalauni/noob-stacking-0-85654,Tabular Playground Series - Oct 2021
4047,78448975,89.0,0.8565045541987387,5,13,/vishalmishra1400/tps-oct-xgboost,Tabular Playground Series - Oct 2021
4048,76698833,46.0,,0,4,/lilkaskitc/tps-oct-2021-lgb,Tabular Playground Series - Oct 2021
4049,76193243,182.0,0.8511816563043028,2,4,/pradeepchandrasuyal/feature-selection-with-lightgbm,Tabular Playground Series - Oct 2021
4050,76097025,231.0,,3,7,/mlanhenke/tps-10-basic-eda-spot-check-xgb-lgbm-catb,Tabular Playground Series - Oct 2021
4051,78028844,186.0,0.8563847575459473,2,13,/mmellinger66/tps-oct-2021-basic-cv-lgbm,Tabular Playground Series - Oct 2021
4052,84759151,216.0,,1,8,/rsizem2/tps-10-21-adversarial-validation,Tabular Playground Series - Oct 2021
4053,76468278,197.0,,0,6,/aditya01233/notebookc5dd760ec6,Tabular Playground Series - Oct 2021
4054,76734502,154.0,,0,11,/sudipg411/data-exploration,Tabular Playground Series - Oct 2021
4055,76762541,155.0,0.8552858918450892,0,5,/mikhailkuzmenkov/brief-catboost-with-randomized-parameters-search,Tabular Playground Series - Oct 2021
4056,76667754,296.0,,2,17,/raj401/simple-clean-eda-tps-oct,Tabular Playground Series - Oct 2021
4057,77365589,288.0,0.78868295296863,2,8,/adizafar/tps-oct-xgboost-conclusion-till-now,Tabular Playground Series - Oct 2021
4058,76318327,247.0,,0,5,/nishantsushmakar/here-we-go,Tabular Playground Series - Oct 2021
4059,77844651,295.0,0.8564522319942621,0,3,/jaysrivastav/single-xgb-without-anything-fancy-tps-oct-21,Tabular Playground Series - Oct 2021
4060,76584289,190.0,0.8555369027372296,0,1,/jonigooner/histogradient-with-optuna,Tabular Playground Series - Oct 2021
4061,76749991,280.0,,3,8,/eeeaaa/xgboost-hyperparams-optimisation-with-optuna,Tabular Playground Series - Oct 2021
4062,77477556,260.0,,17,47,/vivek468/everything-i-learnt-in-a-kaggle-competition,Tabular Playground Series - Oct 2021
4063,77420668,229.0,,0,2,/stevesimons/tps-21-10-single-stochastic-gradient-descent-model,Tabular Playground Series - Oct 2021
4064,77087963,209.0,0.8563623944053506,1,14,/houzhinan/tps-my-conclusion,Tabular Playground Series - Oct 2021
4065,77208872,221.0,0.8526250233378577,1,8,/docxian/tabular-playground-10-first-glance-baseline,Tabular Playground Series - Oct 2021
4066,76104165,271.0,0.8526467784365664,4,11,/junhyeok99/pycaret-baseline-for-beginner,Tabular Playground Series - Oct 2021
4067,76334888,272.0,,40,180,/usharengaraju/tensorflow-decision-forests-w-b,Tabular Playground Series - Oct 2021
4068,76104876,309.0,0.8488949747748122,8,19,/hrshuvo/tps-oct-21-xgbm-kfold,Tabular Playground Series - Oct 2021
4069,76463409,193.0,,0,2,/manthanbhagat/tps-oct-auto-eda-using-dataprep,Tabular Playground Series - Oct 2021
4070,76600307,306.0,,1,9,/pavan9065/tps-stacking-ensemble-october,Tabular Playground Series - Oct 2021
4071,78490841,298.0,0.8563461980895863,0,8,/aaronds/tps-oct2021,Tabular Playground Series - Oct 2021
4072,76364527,265.0,0.8553363233193134,0,5,/truongdang1311/tabular-automl,Tabular Playground Series - Oct 2021
4073,76467572,286.0,,6,32,/legendsoul/tps-october-21-comprehensive-insight-of-eda,Tabular Playground Series - Oct 2021
4074,76089519,350.0,,1,4,/rahulchauhan3j/tps-oct-2021-stratifiedkfolds,Tabular Playground Series - Oct 2021
4075,76436807,334.0,,15,51,/davidcoxon/first-look-at-october-data,Tabular Playground Series - Oct 2021
4076,77561164,313.0,0.8563052192665552,0,1,/abhijitd16/lgbm-optuna-stratkfold,Tabular Playground Series - Oct 2021
4077,76108900,363.0,0.8557337342969558,1,8,/luongduongminh/tps-oct-21-cat,Tabular Playground Series - Oct 2021
4078,76151934,361.0,0.8278227851116663,1,6,/joeywonpark/practice-eda-lgbmtps-oct,Tabular Playground Series - Oct 2021
4079,78272049,322.0,0.849008258978961,0,8,/m1y7k8/tps-oct-21-lgb-fixed,Tabular Playground Series - Oct 2021
4080,77251496,369.0,0.8562645516649642,1,1,/robinbaldeo/stacked-catboost-gbdt-and-goss,Tabular Playground Series - Oct 2021
4081,77045509,325.0,0.8561335550406067,14,20,/mrutyunjaybiswal/tps-oct21-xgb-starter,Tabular Playground Series - Oct 2021
4082,76109814,389.0,,2,12,/takahiroyoshida012/tps-oct-2021-single-lgbm-kfold,Tabular Playground Series - Oct 2021
4083,77885274,408.0,0.8561143385167804,0,7,/eugenebee/tsp-oct-21-single-catboost-skf-rs,Tabular Playground Series - Oct 2021
4084,76541558,393.0,0.847658782813548,0,3,/srhyeu/starter-simple-auto-ml-with-h2o,Tabular Playground Series - Oct 2021
4085,77592186,371.0,,4,6,/khule28/single-catboost-tps-oct,Tabular Playground Series - Oct 2021
4086,78175694,383.0,,0,2,/sergeilepitko/tps-oct-2021-eda,Tabular Playground Series - Oct 2021
4087,77973645,409.0,,0,8,/lonnieqin/catboost-tabular-prediction-oct-2021,Tabular Playground Series - Oct 2021
4088,76263040,406.0,0.8561373993054382,0,4,/bishlar/notebook320b4b4cc6,Tabular Playground Series - Oct 2021
4089,76242326,432.0,,7,17,/anirudhg15/tps-oct-21-baseline-w-nvidia-rapids,Tabular Playground Series - Oct 2021
4090,76176373,397.0,,0,11,/lucamassaron/autogluon-for-tabular-playground-oct-2021,Tabular Playground Series - Oct 2021
4091,76581137,405.0,,1,8,/brbarasulpis/tps-2021-oct-ligtgbm-classif-begginers,Tabular Playground Series - Oct 2021
4092,77554313,385.0,0.8560507277346336,3,11,/melanie7744/tps10-using-optuna-s-lightgbm-tuner,Tabular Playground Series - Oct 2021
4093,76637335,416.0,0.8560349014443605,1,10,/rahiegadekar/a-beginner-s-approach,Tabular Playground Series - Oct 2021
4094,77306247,400.0,0.8560595415418168,0,1,/crismolav/tps-oct-2021-pca-logistic-reg,Tabular Playground Series - Oct 2021
4095,78423552,372.0,0.8459250363757559,0,2,/rizkykiky/xgboost-hyper-params,Tabular Playground Series - Oct 2021
4096,78423552,372.0,0.8463468872370618,0,2,/rizkykiky/xgboost-hyper-params,Tabular Playground Series - Oct 2021
4097,78423552,372.0,0.8459341034003832,0,2,/rizkykiky/xgboost-hyper-params,Tabular Playground Series - Oct 2021
4098,78423552,372.0,0.8463485477514546,0,2,/rizkykiky/xgboost-hyper-params,Tabular Playground Series - Oct 2021
4099,76932215,475.0,0.8558327773200296,0,8,/venkatkumar001/tps-lightautoml,Tabular Playground Series - Oct 2021
4100,76645476,427.0,,0,13,/yukiyamamoto/lightgbm-baseline,Tabular Playground Series - Oct 2021
4101,77367832,423.0,,0,2,/pradipkumardas/tps-oct-21-compression-xgb-parameters-tuning-ipynb,Tabular Playground Series - Oct 2021
4102,77119238,418.0,,29,108,/lordozvlad/fast-automl-with-intel-extension-for-scikit-learn,Tabular Playground Series - Oct 2021
4103,76118211,449.0,0.8559813641561768,3,14,/maximkazantsev/tps-10-21-eda-lightgbm-optuna,Tabular Playground Series - Oct 2021
4104,76871881,439.0,0.8559765732261295,0,3,/vitalyleontev/tps10-21-lightautoml,Tabular Playground Series - Oct 2021
4105,76618317,446.0,0.8559042406431379,1,11,/hamidrezabakhtaki/tabular-oct-2021-xgboost-optuna,Tabular Playground Series - Oct 2021
4106,76649124,445.0,,0,7,/pawan2905/tabular-playground-series-xgb,Tabular Playground Series - Oct 2021
4107,77290748,461.0,0.8558048479959784,2,20,/rahullalu/tps-oct-2021-eda-and-baseline,Tabular Playground Series - Oct 2021
4108,77290748,461.0,0.8558594281560057,2,20,/rahullalu/tps-oct-2021-eda-and-baseline,Tabular Playground Series - Oct 2021
4109,76260829,482.0,0.8558556650967685,2,5,/kojimar/lightgbm-with-optuna,Tabular Playground Series - Oct 2021
4110,88718274,450.0,,1,12,/nikhilkhetan/utility-for-large-datasets,Tabular Playground Series - Oct 2021
4111,76136958,465.0,,2,8,/akmeghdad/tps-1021-essential,Tabular Playground Series - Oct 2021
4112,77744905,451.0,0.8552650968125194,0,6,/muhammadsabih56/tps-oct-feature-selection-comparative-analysis,Tabular Playground Series - Oct 2021
4113,78292615,448.0,0.8540270669246405,0,1,/sgiuri/oct21tp-lgbm-ctb-stacking,Tabular Playground Series - Oct 2021
4114,76406380,512.0,,0,5,/peressim/tabular-playground-series-oct-2021-eda,Tabular Playground Series - Oct 2021
4115,76997572,505.0,,0,5,/yogeshkaushik/tsp-oct2021-eda,Tabular Playground Series - Oct 2021
4116,76415098,463.0,0.8556058638879632,0,8,/bibhabasumohapatra/october-playground-with-lgbclassifier,Tabular Playground Series - Oct 2021
4117,76146603,456.0,,0,4,/christoforum/preparing-datasets,Tabular Playground Series - Oct 2021
4118,76444520,485.0,0.8556186683700641,0,5,/datascientistsohail/hyperparameterstuning-tps-oct2021-hyperopt,Tabular Playground Series - Oct 2021
4119,77361601,489.0,0.8555468234206655,4,18,/pallavisinha12/october-playground-series,Tabular Playground Series - Oct 2021
4120,166350327,490.0,,25,76,/bennyfung/feature-selection-lightgbm,Tabular Playground Series - Oct 2021
4121,76136570,491.0,,0,4,/stpeteishii/tps1021-data-histplot,Tabular Playground Series - Oct 2021
4122,77790537,514.0,0.8552423864480024,1,6,/alxbkr/flaml-quick-low-effort-automl-solution,Tabular Playground Series - Oct 2021
4123,76565900,531.0,,0,7,/ameerhamza319/oct-tps-eda-kfold-catboost-score-0-85540,Tabular Playground Series - Oct 2021
4124,77530110,549.0,,0,1,/tomods/tabular-playground-oct-2021,Tabular Playground Series - Oct 2021
4125,77421631,534.0,,2,4,/semihuslu/tps-oct2021-catboost,Tabular Playground Series - Oct 2021
4126,78448235,558.0,0.8552960705463,0,1,/harshalbhamare/tpc-0ct2021,Tabular Playground Series - Oct 2021
4127,77587418,555.0,0.8551391705374584,4,8,/shenurisumanasekara/tabular-october-catboost,Tabular Playground Series - Oct 2021
4128,77901415,562.0,0.8551409194579415,0,5,/djagatiya/tps-oct-2021,Tabular Playground Series - Oct 2021
4129,77167443,550.0,0.8549573464115943,8,19,/farizhaykal/tps-oct-2021-eda-lightgbm-randomizedsearchcv,Tabular Playground Series - Oct 2021
4130,76498858,575.0,0.8540175698703883,1,6,/juliorsleite/tps-10-21-simplexgboost-randomizedsearchcv,Tabular Playground Series - Oct 2021
4131,79222897,581.0,,0,1,/kingxl/octpgfinal,Tabular Playground Series - Oct 2021
4132,78388673,580.0,,0,3,/egorovalexeyd/tps-october-simple-lgbm-parameters-tuning-example,Tabular Playground Series - Oct 2021
4133,78418857,590.0,0.8463371405656136,0,5,/haozhang607/tabular-playground-series-oct-2021,Tabular Playground Series - Oct 2021
4134,76955399,624.0,,0,0,/johncenadon/xgboost-optuna-mpetition,Tabular Playground Series - Oct 2021
4135,77315924,622.0,0.854119547495627,1,1,/hakanerdogan/tps-oct-2021-simple-code,Tabular Playground Series - Oct 2021
4136,77175075,627.0,,1,3,/gabtex/optuna-tuning-and-feature-exclusion,Tabular Playground Series - Oct 2021
4137,119754418,616.0,,9,81,/bextuychiev/25-numpy-functions-you-never-knew-existed,Tabular Playground Series - Oct 2021
4138,76329810,632.0,0.8529957858796893,0,3,/kelizatoh/oct-2021-tabular-playground-tabularautoml,Tabular Playground Series - Oct 2021
4139,78106247,638.0,0.8454164143367836,0,0,/markct/tps-202110,Tabular Playground Series - Oct 2021
4140,76257509,640.0,0.7804399679093893,2,10,/nesterenkomarina/pseudo-label-tps1021-cnn-tensorflow,Tabular Playground Series - Oct 2021
4141,92900939,643.0,,1,2,/limyikeen/very-basic-ml-competition,Tabular Playground Series - Oct 2021
4142,77941998,651.0,,0,7,/mfedeli/tabular-playground-oct-2021,Tabular Playground Series - Oct 2021
4143,76114465,661.0,0.8505879884065213,0,5,/johnycoder/oct-xgb,Tabular Playground Series - Oct 2021
4144,76266424,662.0,,2,15,/nancysamuel/basic-xgboost-lightgbm-and-catboost-models,Tabular Playground Series - Oct 2021
4145,76222894,674.0,0.8520708763626726,0,6,/sankalpsrivastava26/tps-oct-21-tensorflow-approach-gpu-0-85207-score,Tabular Playground Series - Oct 2021
4146,76728892,691.0,,1,10,/revathiprakash/oct-2021-tps-baseline-cudf-tpot-gpu,Tabular Playground Series - Oct 2021
4147,76859348,699.0,,0,1,/datajmcn/xgb-baseline-oct21,Tabular Playground Series - Oct 2021
4148,76633678,702.0,,2,9,/stmohd/tps-oct-2021-model-with-memory-reduced,Tabular Playground Series - Oct 2021
4149,76177865,708.0,,1,4,/susree64/tabular-playground-series-oct21,Tabular Playground Series - Oct 2021
4150,76626245,710.0,0.8495530073066734,3,17,/carlmcbrideellis/h2o-ai-gradient-boosting-classifier,Tabular Playground Series - Oct 2021
4151,76188986,705.0,,1,4,/yamahisa/eda-in-progress,Tabular Playground Series - Oct 2021
4152,76882447,728.0,0.8486203962590982,0,1,/danielbissell/tps-oct-lightgbm,Tabular Playground Series - Oct 2021
4153,76882447,728.0,0.8486203962590982,0,1,/danielbissell/tps-oct-lightgbm,Tabular Playground Series - Oct 2021
4154,76838481,721.0,,4,5,/colt2brbr/tabularplaygrond-oct-2021-randomforest-base,Tabular Playground Series - Oct 2021
4155,76608012,729.0,0.848394735113302,1,8,/diwash1/tps-oct-2021-eda-model-with-lgbm,Tabular Playground Series - Oct 2021
4156,76354282,740.0,0.8474884560797393,0,13,/cascadinglight/tabtransformer-gauss-rank-baseline-kfold,Tabular Playground Series - Oct 2021
4157,76707006,744.0,,1,5,/gunjangrunge/tps-1021-xgboost-with-twist-revised,Tabular Playground Series - Oct 2021
4158,77880544,753.0,0.8442914732395915,0,1,/tanmaymane18/5-folds-ensemble-with-differential-evolution,Tabular Playground Series - Oct 2021
4159,76407749,793.0,0.8400145119997317,0,6,/muhammadwaqargul/84-test-acc-with-simple-ann,Tabular Playground Series - Oct 2021
4160,76407749,793.0,0.8400145119997317,0,6,/muhammadwaqargul/84-test-acc-with-simple-ann,Tabular Playground Series - Oct 2021
4161,76249592,798.0,,6,25,/jeongbinpark/tps-oct-for-command-tip-in-pandas,Tabular Playground Series - Oct 2021
4162,77454284,809.0,0.5,0,10,/mahnoorrana/tps-data,Tabular Playground Series - Oct 2021
4163,76416519,813.0,,0,4,/seikimaiihuang/practice-tps-10-2021-logisticregression,Tabular Playground Series - Oct 2021
4164,76140920,815.0,,0,7,/ottpocket/feather-creator-october,Tabular Playground Series - Oct 2021
4165,78139258,855.0,0.8216448951168246,7,10,/olehmezhenskyi/eda-blend-of-linear-lgbm-mars-tidymodels,Tabular Playground Series - Oct 2021
4166,77878839,865.0,0.8168060119661643,2,1,/radkin17/tpoct21-xgboost,Tabular Playground Series - Oct 2021
4167,111557477,893.0,0.7683439602154193,22,122,/hadeux/kor-eng-simple-light-gbm-model,Tabular Playground Series - Oct 2021
4168,78485445,905.0,0.7576620123360298,8,15,/salama4ai/salama4ai-tabular-playground-series-oct-2021,Tabular Playground Series - Oct 2021
4169,78319098,927.0,0.754875678385484,0,1,/tariqchhussain/xgboost-optuna-tps-oct-21,Tabular Playground Series - Oct 2021
4170,79357963,928.0,0.7671914798210449,0,6,/loycelorenzo/tabular-playground-series-oct-2021,Tabular Playground Series - Oct 2021
4171,78484307,959.0,,0,2,/nitishraj/tabular-playground-oct21,Tabular Playground Series - Oct 2021
4172,77705988,970.0,,1,6,/pruthvi1009/xgboost-basic-predicton,Tabular Playground Series - Oct 2021
4173,77918409,975.0,,2,11,/pinstripezebra/xgboost-ensemble-approach,Tabular Playground Series - Oct 2021
4174,78334785,990.0,0.75857776542226,0,0,/rihann/eda-rf,Tabular Playground Series - Oct 2021
4175,76985369,1007.0,0.7565574112400604,3,9,/sonicaprasad/tabular-playground-series,Tabular Playground Series - Oct 2021
4176,76146222,1013.0,0.7442031791570122,0,4,/tracyporter/oct-21-tabular-selectkbest,Tabular Playground Series - Oct 2021
4177,76518216,1036.0,0.7214264106654308,1,6,/timothydhong/october-2021-playground-log-regression,Tabular Playground Series - Oct 2021
4178,76598575,18.0,0.9823,0,0,/xeno97/17011770-mnistdnn,DNN을 이용한 MNIST 손글씨 분류
4179,78462755,3.0,,62,219,/slawekbiel/positive-score-with-detectron-3-3-inference,Sartorius - Cell Instance Segmentation
4180,80088271,11.0,,19,164,/theoviel/competition-metric-map-iou,Sartorius - Cell Instance Segmentation
4181,80578423,4.0,,4,63,/ren4yu/sartorius-automatically-finding-broken-masks,Sartorius - Cell Instance Segmentation
4182,83828183,7.0,0.3324319121223094,0,3,/damtrongtuyen/sartorius-cellpose-inference-customize-all-in,Sartorius - Cell Instance Segmentation
4183,81429762,8.0,,22,58,/markunys/sartorius-transfer-learning-train-with-livecell,Sartorius - Cell Instance Segmentation
4184,79894333,9.0,,0,4,/kevin1742064161/create-singleclass-coco-stratifiedgroupkfold,Sartorius - Cell Instance Segmentation
4185,81471774,18.0,,0,17,/trushk/mmdetection-custom-eval-script,Sartorius - Cell Instance Segmentation
4186,80684343,28.0,,0,13,/rednikotin/duplicates-sartorius,Sartorius - Cell Instance Segmentation
4187,81921022,22.0,,0,1,/deeeeeeeplearning/fork-of-mmdetection-neuron-inference-dddf41,Sartorius - Cell Instance Segmentation
4188,78579647,20.0,0.2881864552735334,0,0,/zekunn/positive-score-with-detectron-3-3-inferen-class,Sartorius - Cell Instance Segmentation
4189,86194791,17.0,,0,7,/aimanlim0/cow-seg-with-detectron-training,Sartorius - Cell Instance Segmentation
4190,81524154,23.0,,1,13,/jaideepvalani/cv-strategy-stratified-by-masks-sum,Sartorius - Cell Instance Segmentation
4191,83550882,49.0,0.3126475856847756,0,0,/omargamal064/sep-classes,Sartorius - Cell Instance Segmentation
4192,83091681,36.0,,0,0,/guofenwei/positive-score-with-detectron-3-3-inference,Sartorius - Cell Instance Segmentation
4193,83951341,26.0,0.3317379780748858,0,0,/handudu/how-to-use-mmdectetion,Sartorius - Cell Instance Segmentation
4194,81442272,34.0,,14,37,/ebinan92/unet-with-deep-watershed-transform-dwt-train,Sartorius - Cell Instance Segmentation
4195,82225069,61.0,,0,0,/dylanliuofficial/sartorius-segmentation-detectron2-diagnosis,Sartorius - Cell Instance Segmentation
4196,80229416,63.0,,13,183,/gunesevitan/sartorius-cell-instance-segmentation-eda,Sartorius - Cell Instance Segmentation
4197,80654497,54.0,,0,0,/apparition/train-of-torch-mask-rcnn-square-augs,Sartorius - Cell Instance Segmentation
4198,78870181,57.0,,0,4,/zaopolearning/maskrcnn-basemodel,Sartorius - Cell Instance Segmentation
4199,79808480,82.0,,4,9,/hsadeghian/sartorius-detectron-training-w-b,Sartorius - Cell Instance Segmentation
4200,79087895,83.0,0.2485334859401832,1,9,/ctawong/cell-instance-segmentation-detectron2-mask-rcnn,Sartorius - Cell Instance Segmentation
4201,80723203,97.0,,3,15,/drzhuzhe/sartorius-eda,Sartorius - Cell Instance Segmentation
4202,83236137,112.0,,1,11,/kisakitetta/sartorius-kfold-coco,Sartorius - Cell Instance Segmentation
4203,77275630,115.0,,21,133,/ihelon/cell-segmentation-run-length-decoding,Sartorius - Cell Instance Segmentation
4204,83133463,111.0,0.3131855375353998,0,5,/aishikai/sartorious-inference-detectron-2-single,Sartorius - Cell Instance Segmentation
4205,83631826,168.0,0.3094140297050434,0,1,/blankaf/sartorius-inference,Sartorius - Cell Instance Segmentation
4206,82031480,163.0,,0,5,/denispotapov/cutmix-augmentation,Sartorius - Cell Instance Segmentation
4207,150838341,142.0,0.3114250734362536,0,2,/junxhuang/inference-sartorius-transfer-learning,Sartorius - Cell Instance Segmentation
4208,78812695,143.0,,3,10,/slavkoprytula/efficientnet-classification-semi-supervised,Sartorius - Cell Instance Segmentation
4209,81101422,183.0,,0,1,/myeongwonkim/mask-rcnn-training-using-detectron2,Sartorius - Cell Instance Segmentation
4210,79183330,220.0,0.1522319236543333,1,12,/drtausamaru/efnetb0-unet-inference,Sartorius - Cell Instance Segmentation
4211,80326811,191.0,0.2989639894521348,30,82,/vgarshin/detectron2-inference-with-ensemble-and-nms,Sartorius - Cell Instance Segmentation
4212,78871800,214.0,,4,16,/soumya9977/sartorious-nb-1-data-preprocessing-visualization,Sartorius - Cell Instance Segmentation
4213,82862992,256.0,,26,53,/vexxingbanana/sartorius-mmdetection-training,Sartorius - Cell Instance Segmentation
4214,82724109,247.0,0.2847637739892681,0,47,/tianshuo42/inference-and-submission,Sartorius - Cell Instance Segmentation
4215,84199454,269.0,,0,2,/kugaichen/how-to-use-mmdectetion,Sartorius - Cell Instance Segmentation
4216,79060942,274.0,,2,12,/kavehshahhosseini/sartorius-convert-images-and-masks-to-tfrecord,Sartorius - Cell Instance Segmentation
4217,78653910,275.0,,12,180,/julian3833/sartorius-starter-baseline-torch-u-net-0-0,Sartorius - Cell Instance Segmentation
4218,82743083,229.0,0.0428775429858398,2,3,/testforflb/inference-unet,Sartorius - Cell Instance Segmentation
4219,79100851,288.0,,5,107,/coldfir3/efficient-coco-dataset-generator,Sartorius - Cell Instance Segmentation
4220,77326849,230.0,,4,36,/amritpal333/choosing-augmentations-for-cell-segmentation,Sartorius - Cell Instance Segmentation
4221,78962439,236.0,,0,3,/timmate/train-sartorius-segmentation-just-plotting,Sartorius - Cell Instance Segmentation
4222,82568600,343.0,,1,17,,Sartorius - Cell Instance Segmentation
4223,80232526,352.0,0.2578885987020625,0,1,/tangjq/detectron-3-3-inferen,Sartorius - Cell Instance Segmentation
4224,84352146,311.0,,0,0,/ryusuke20210920/my-ensemble-privatescore-0-311,Sartorius - Cell Instance Segmentation
4225,82948573,337.0,,0,54,/ks2019/cellpose-training-pipeline,Sartorius - Cell Instance Segmentation
4226,82280183,388.0,,0,0,/xanjay/evaluate-using-competition-map-metric,Sartorius - Cell Instance Segmentation
4227,79070520,393.0,,0,1,/kurokia/semantic-segmentation-by-pspnet-train,Sartorius - Cell Instance Segmentation
4228,84313684,420.0,,0,1,/shir0mani/xai-cell-classification-lime,Sartorius - Cell Instance Segmentation
4229,78474849,682.0,,12,41,/dragonzhang/positive-score-with-detectron-3-3-inference,Sartorius - Cell Instance Segmentation
4230,78400691,427.0,,0,7,/stpeteishii/cell-instance-classify-densenet201,Sartorius - Cell Instance Segmentation
4231,81751492,665.0,,0,11,/zzhnku/mmdetection-neuron-inference-nms-improvement,Sartorius - Cell Instance Segmentation
4232,97167866,698.0,,0,0,/ehan12/ensemble-nms-detectron2-inference-ab57ec,Sartorius - Cell Instance Segmentation
4233,77246545,523.0,,5,23,/bhargav6031/run-length-decoding-function-beginners,Sartorius - Cell Instance Segmentation
4234,79072228,620.0,0.0,2,4,/karan23258/cell-instance-segmentation-unetfromscratch,Sartorius - Cell Instance Segmentation
4235,77847760,516.0,0.2739599171388389,0,4,/cuimdi/fork-of-positive-score-with-detectron-3-3-infere,Sartorius - Cell Instance Segmentation
4236,78288798,520.0,0.2746030001437147,0,1,/qq1623620766/sartorius-starter-torch-mask-r-cnn-lb-0-273,Sartorius - Cell Instance Segmentation
4237,79512916,530.0,,0,9,/wsmonroe/load-and-vis-sartorious-livecell-data,Sartorius - Cell Instance Segmentation
4238,78754968,541.0,,0,8,/abhishandy/visualizing-annotations,Sartorius - Cell Instance Segmentation
4239,78526556,561.0,,4,20,/linrds/convert-rle-to-polygons,Sartorius - Cell Instance Segmentation
4240,82265739,584.0,,0,6,/iusami/celltype-classification,Sartorius - Cell Instance Segmentation
4241,114920553,562.0,,0,17,/validmodel/baseline-model,Sartorius - Cell Instance Segmentation
4242,79191514,724.0,0.2940599234755813,0,0,/georgeteo89/satorius-segmentation-submission,Sartorius - Cell Instance Segmentation
4243,78846397,697.0,0.2476336586731163,1,9,/konradb/validate-submit,Sartorius - Cell Instance Segmentation
4244,77418499,784.0,,1,5,/markwijkhuizen/sartorius-preprocessing-kfolds-public,Sartorius - Cell Instance Segmentation
4245,80134774,712.0,,0,16,/vsedelnik/order-of-instances-in-metric-submission,Sartorius - Cell Instance Segmentation
4246,78853310,746.0,,3,17,/evangelou/sartorius-unet-pytorch-from-scratch,Sartorius - Cell Instance Segmentation
4247,81476623,707.0,,4,25,/hengck23/split-adjoining-cell-into-subsets-of-non-touching,Sartorius - Cell Instance Segmentation
4248,79851116,773.0,,1,22,/monikabozhinova/livecell-shsy5y-coco-dataset,Sartorius - Cell Instance Segmentation
4249,78371721,769.0,,0,4,/arminajdehnia/annotate-cell-instance-segmentaion,Sartorius - Cell Instance Segmentation
4250,77288035,905.0,,2,9,/hiroshisakiyama/yet-another-data-exploration,Sartorius - Cell Instance Segmentation
4251,78212154,849.0,,2,27,/shivansh002/getting-started,Sartorius - Cell Instance Segmentation
4252,84119719,830.0,,29,164,/awsaf49/sartorius-mmdetection-train,Sartorius - Cell Instance Segmentation
4253,80593586,806.0,,0,3,/mariapodguzova/semantic-segmentation,Sartorius - Cell Instance Segmentation
4254,77276037,885.0,,2,13,/arunamenon/cell-instance-segmentation-unet-eda,Sartorius - Cell Instance Segmentation
4255,83138751,960.0,0.0953995173169148,0,10,/carlosgut/sartorius-complete-from-eda-to-submit-unet,Sartorius - Cell Instance Segmentation
4256,95216922,967.0,,0,2,/piyush1089/sartorius-detectron,Sartorius - Cell Instance Segmentation
4257,77665230,903.0,,4,10,/kfk42kfk/train-sartorius-fpn-effnetb3-ns-baseline,Sartorius - Cell Instance Segmentation
4258,80885181,998.0,,0,2,/ethon543/cell-types-classifier-swin,Sartorius - Cell Instance Segmentation
4259,82647761,1036.0,0.2750570824538166,0,0,/as200188/sartorius-starter-torch-mask-r-cnn-lb-0-273,Sartorius - Cell Instance Segmentation
4260,81268958,1051.0,0.2707453799015069,2,2,/jianghuayu/pytorch-mask-rcnn,Sartorius - Cell Instance Segmentation
4261,77542910,1181.0,,0,8,/robertlangdonvinci/sartorius-cell-segmentation-data-gen,Sartorius - Cell Instance Segmentation
4262,80770679,1141.0,,0,2,/aktaruzzaman/detectron2-inference-scis,Sartorius - Cell Instance Segmentation
4263,77340819,1157.0,,0,5,/barteksadlej123/sartors-tf-starter,Sartorius - Cell Instance Segmentation
4264,77212731,1183.0,,5,15,/alibaba19/sartorius-segmentation-fastai-starter,Sartorius - Cell Instance Segmentation
4265,82307203,1194.0,0.2358462060924878,0,0,/yoshimoto0921/sartorius-starter-torch-mask-r-cnn,Sartorius - Cell Instance Segmentation
4266,78441059,1226.0,,0,4,/remananr/image-rotation-using-opencv,Sartorius - Cell Instance Segmentation
4267,77307564,1243.0,,2,6,/nxhong93/sartorius-cell-eda,Sartorius - Cell Instance Segmentation
4268,77552323,1255.0,,1,23,/susnato/understanding-run-length-encoding-and-decoding,Sartorius - Cell Instance Segmentation
4269,79425057,1275.0,0.0060154756656545,0,2,/ivoflorinscheiber/unetfromscratch-mypostpro,Sartorius - Cell Instance Segmentation
4270,82203082,1338.0,0.1224861800126288,0,3,/b3d1rhan/sartorious,Sartorius - Cell Instance Segmentation
4271,79022506,1354.0,,3,10,/kriyeng/evaluate-26-pretrained-models-to-split-the-problem,Sartorius - Cell Instance Segmentation
4272,85557200,1385.0,,0,3,/juhha1/simple-model-development-using-monai,Sartorius - Cell Instance Segmentation
4273,83295333,1399.0,,0,5,/huchlatymon/tf-deep-residual-unet-with-attention-train,Sartorius - Cell Instance Segmentation
4274,83958138,1413.0,,0,2,/nathennguyen/u-net-with-90k-parameters,Sartorius - Cell Instance Segmentation
4275,78106108,1460.0,,2,16,/aramos/sartorius-competition-training-keras-unet,Sartorius - Cell Instance Segmentation
4276,79550909,1472.0,,0,10,/sifatshikdar/run-length-decoding-the-masks,Sartorius - Cell Instance Segmentation
4277,82027673,1501.0,,0,0,/qilongchen/unet-with-deep-watershed-transform-dwt-train,Sartorius - Cell Instance Segmentation
4279,83189164,305.0,,22,33,,Tabular Playground Series - Nov 2021
4280,81244235,1.0,0.7523724211525599,0,7,/jayjay75/tpsnov21-012c-leaderboard-probing,Tabular Playground Series - Nov 2021
4281,81244235,1.0,0.752298698418062,0,7,/jayjay75/tpsnov21-012c-leaderboard-probing,Tabular Playground Series - Nov 2021
4282,78508696,3.0,0.7454419117052803,3,17,/ambrosm/tpsnov21-001-support-vector-classification,Tabular Playground Series - Nov 2021
4283,81214526,4.0,,8,30,/pourchot/my-super-simple-overfitting-tool-explained,Tabular Playground Series - Nov 2021
4284,78536702,42.0,0.7394396900516833,0,21,/faisalalsrheed/autoxgb-tps-nov-21,Tabular Playground Series - Nov 2021
4285,166329650,111.0,,2,24,/vinayaktiwari28/tps-solution-customann-with-skip-connections,Tabular Playground Series - Nov 2021
4286,78533428,124.0,0.7467293103769598,1,15,/lukaszborecki/torch-embeddings,Tabular Playground Series - Nov 2021
4287,78523200,54.0,0.7377358898372087,0,6,/mathurinache/mljar-automl-nov-2021,Tabular Playground Series - Nov 2021
4288,80126724,55.0,0.6139370874670141,0,5,/colt2brbr/tps-nov-data-analsys-lightlgb,Tabular Playground Series - Nov 2021
4289,80669221,64.0,,1,9,/krivenkozz/gpu-based-variables-interaction-simple-solution,Tabular Playground Series - Nov 2021
4290,80998385,78.0,,10,28,/smsajideen/tps-nov-pytorch-baseline-nn,Tabular Playground Series - Nov 2021
4291,78556159,81.0,,0,13,/kalaikumarr/tps-nov-simple-eda-with-detailed-summary,Tabular Playground Series - Nov 2021
4292,81181262,17.0,,0,8,/joanyeo/nov-tps-vsn-variable-selection-networks,Tabular Playground Series - Nov 2021
4293,80676705,84.0,0.7396906985144164,0,9,/omarvivas/lgbm-tpsnov-v1,Tabular Playground Series - Nov 2021
4294,78519150,92.0,,0,3,/aayush26/tps-nov-2021-eda-101,Tabular Playground Series - Nov 2021
4295,78508814,94.0,,0,8,/rhythmcam/tps-11-21-mljar-automl-prediction,Tabular Playground Series - Nov 2021
4296,81101448,91.0,0.7464633687799619,13,23,/mhslearner/tps-nov-eda-deeptables,Tabular Playground Series - Nov 2021
4297,79620333,89.0,,1,7,/zenstat/beginner-logistic-knn-svm-xgb,Tabular Playground Series - Nov 2021
4298,124175491,32.0,,19,43,/maxdiazbattan/tps-2021-feat-selection-engineering-ideas,Tabular Playground Series - Nov 2021
4299,85029116,120.0,0.7447789188776123,1,7,/rsizem2/tps-11-21-gradient-boosting-baselines-w-gpu,Tabular Playground Series - Nov 2021
4300,78529675,112.0,,2,15,/legendsoul/tps-november-21-comprehensive-insight-of-eda,Tabular Playground Series - Nov 2021
4301,80323975,303.0,,2,11,/sfktrkl/tps-nov-2021,Tabular Playground Series - Nov 2021
4302,78526349,122.0,0.739675555105039,2,13,/kavehshahhosseini/tps-nov-2021-shap-values-with-xgboost,Tabular Playground Series - Nov 2021
4303,78521384,113.0,,0,4,/yogeshkalauni/tps-nov-21-auto-xgboost-error,Tabular Playground Series - Nov 2021
4304,78925671,110.0,0.740310066358804,0,19,/devsubhash/tps-nov-starter-eda-lightautoml,Tabular Playground Series - Nov 2021
4305,78956637,145.0,,0,5,/mikhailsavin/try-pytorch-with-weights-init,Tabular Playground Series - Nov 2021
4306,79053944,148.0,0.6846958460031508,12,26,/kalilurrahman/tps-nov2021-automated-eda-ml,Tabular Playground Series - Nov 2021
4307,79053944,148.0,0.6846958460031508,12,26,/kalilurrahman/tps-nov2021-automated-eda-ml,Tabular Playground Series - Nov 2021
4308,79047988,284.0,0.7480924350987416,0,2,/rizkykiky/tensorflow-k-folds-with-pca-and-kmeans,Tabular Playground Series - Nov 2021
4309,79047988,284.0,0.7480924350987416,0,2,/rizkykiky/tensorflow-k-folds-with-pca-and-kmeans,Tabular Playground Series - Nov 2021
4310,81043592,154.0,,14,26,/yuyougnchan/tps-nov-lightgbm-baseline,Tabular Playground Series - Nov 2021
4311,80203272,45.0,,9,15,/pavan9065/exploring-tps-nov-2021,Tabular Playground Series - Nov 2021
4312,78678272,157.0,,0,10,/tomods/tpsnov-eda-distributions,Tabular Playground Series - Nov 2021
4313,81136031,163.0,,7,16,/safavieh/probing-test-set-chunks-with-math,Tabular Playground Series - Nov 2021
4314,78793702,115.0,0.7494083869699095,38,101,/chaudharypriyanshu/understanding-neural-net,Tabular Playground Series - Nov 2021
4315,78876051,544.0,0.7379629373408475,3,9,/zhangcheche/tps-11-eda-model-train,Tabular Playground Series - Nov 2021
4316,78589135,551.0,,1,10,/craigmthomas/tps-nov-2021-detailed-eda-models,Tabular Playground Series - Nov 2021
4317,80873049,239.0,,2,8,/willclare/dnn-and-kerastuner,Tabular Playground Series - Nov 2021
4318,79978495,183.0,0.7452642038262488,0,7,/mohammadhossein77/tps-nov-eda-lr,Tabular Playground Series - Nov 2021
4319,80109946,187.0,,1,17,/datastrophy/basic-eda-autoxgb-lgbm-no-tune,Tabular Playground Series - Nov 2021
4320,78910748,251.0,0.7402618229257674,6,14,/vamsikrishnab/tps-nov-eda-and-catboost,Tabular Playground Series - Nov 2021
4321,80393765,201.0,,12,39,/landfallmotto/tps-nov-21-kmeans-keras-discretization-layer,Tabular Playground Series - Nov 2021
4322,109511964,250.0,0.7406430705112174,18,104,/hadeux/kor-eng-simple-xgboost-model,Tabular Playground Series - Nov 2021
4323,78757297,221.0,,0,6,/puremath86/adversarial-train-test-similarity-tps-nov21,Tabular Playground Series - Nov 2021
4324,78507426,257.0,0.6844251715155171,0,9,/adizafar/tps-nov-2021-eda-and-analysis,Tabular Playground Series - Nov 2021
4325,79051330,123.0,,0,6,/aditya01233/ensembling-public-nb-nov-tps,Tabular Playground Series - Nov 2021
4326,79315920,241.0,0.7495112555155827,25,66,/javiervallejos/simple-nn-with-good-results-tps-nov-21,Tabular Playground Series - Nov 2021
4327,79159235,21.0,,9,41,/kartushovdanil/tps-nov21-4-begginers-rus-links,Tabular Playground Series - Nov 2021
4328,78779431,24.0,0.7464664304736295,4,13,/kaaveland/tps-nov-2021-some-models-that-work-ok,Tabular Playground Series - Nov 2021
4329,78686761,172.0,0.7472420719405178,1,9,/suharkov/tps-2021-11-eda-h2o,Tabular Playground Series - Nov 2021
4330,81121182,178.0,,2,9,/takuiga/let-s-use-lightgbm-with-optuna,Tabular Playground Series - Nov 2021
4331,79581721,198.0,,0,2,/yutotom/logistic,Tabular Playground Series - Nov 2021
4332,78660341,271.0,0.7455205666015957,24,76,/hamzaghanmi/make-it-simple,Tabular Playground Series - Nov 2021
4333,79140054,277.0,0.7459858498054089,7,34,/rahullalu/tps-nov-2021-eda-and-baseline,Tabular Playground Series - Nov 2021
4334,78502445,180.0,0.7357465552269926,2,21,/stevenrferrer/tps-nov-2021-baseline-xgbm-lgbm-cb-hgb,Tabular Playground Series - Nov 2021
4335,78502445,180.0,0.7390067750101014,2,21,/stevenrferrer/tps-nov-2021-baseline-xgbm-lgbm-cb-hgb,Tabular Playground Series - Nov 2021
4336,78502445,180.0,0.7389329630437288,2,21,/stevenrferrer/tps-nov-2021-baseline-xgbm-lgbm-cb-hgb,Tabular Playground Series - Nov 2021
4337,78502445,180.0,0.741169165037443,2,21,/stevenrferrer/tps-nov-2021-baseline-xgbm-lgbm-cb-hgb,Tabular Playground Series - Nov 2021
4338,79177831,419.0,,4,12,/thariqnugrohotomo/example-of-leaking-high-val-score-but-low-lb,Tabular Playground Series - Nov 2021
4339,78766232,289.0,,0,2,/motchan/tps-nov-2021-kmeans-method,Tabular Playground Series - Nov 2021
4340,78793488,209.0,,4,14,/adamwurdits/tps-11-2021-quick-lightgbm-starter,Tabular Playground Series - Nov 2021
4341,78849514,309.0,0.7442053980102232,2,8,/docxian/tabular-playground-11-first-glance-baselines,Tabular Playground Series - Nov 2021
4342,78849514,309.0,0.7455239502102546,2,8,/docxian/tabular-playground-11-first-glance-baselines,Tabular Playground Series - Nov 2021
4343,78604804,174.0,0.7454151221357781,2,5,/muhammadsabih56/tps-nov-baseline-models-performance-linear-vs-tree,Tabular Playground Series - Nov 2021
4344,82230422,203.0,,0,9,/cv13j0/tps-nov21-grn-vsn,Tabular Playground Series - Nov 2021
4345,79009521,264.0,,1,8,/teamwilliam/a-simple-keras-optuna-starter,Tabular Playground Series - Nov 2021
4346,80603682,33.0,0.746452569522359,2,18,/siukeitin/tps112021-hard-margin-svm,Tabular Playground Series - Nov 2021
4347,78570475,278.0,0.7406034303513558,5,22,/mmellinger66/tps-nov-21-basic-xgboost-cv-oof,Tabular Playground Series - Nov 2021
4348,78520607,226.0,,0,10,/harshjhunjhunwala/nov-21-eda-lightgbm,Tabular Playground Series - Nov 2021
4349,79787079,416.0,,2,17,/sudhakarcs/tps-nov-2021-mislabelled-classes-99-valid-acc,Tabular Playground Series - Nov 2021
4350,78531389,308.0,,2,18,/mlanhenke/tps-11-simple-basic-eda,Tabular Playground Series - Nov 2021
4351,78499271,38.0,0.7259152928017417,0,2,/realtimshady/baseline-lbgm-optuna,Tabular Playground Series - Nov 2021
4352,117650122,427.0,0.7352141518471813,6,56,/bennyfung/lgbm-beginner,Tabular Playground Series - Nov 2021
4353,78977469,343.0,0.6362078882197509,4,16,/farizhaykal/tps-nov-2021-simple-ann,Tabular Playground Series - Nov 2021
4354,79894630,301.0,0.7466913120035608,0,13,/m1y7k8/tps-nov-21-nn-model-mlp,Tabular Playground Series - Nov 2021
4355,80944510,230.0,0.7476883769651357,1,13,/antonellomartiello/tps11-tf-df-hybrid-model-nn-gb-calibration,Tabular Playground Series - Nov 2021
4356,78495454,563.0,,0,9,/motloch/nov-21-xgb-classifier,Tabular Playground Series - Nov 2021
4357,81475416,228.0,,1,9,/durgancegaur/november-playground-using-autoxgb,Tabular Playground Series - Nov 2021
4358,78555350,186.0,,1,26,/lucamassaron/feature-selection-by-boruta-shap,Tabular Playground Series - Nov 2021
4359,78935096,371.0,,0,5,/ymatioun/tps-nov2021-adversarial-validation,Tabular Playground Series - Nov 2021
4360,78549397,363.0,0.7469557792739144,1,12,/maximkazantsev/tps-11-21-eda-lightgbm-optuna,Tabular Playground Series - Nov 2021
4361,78636602,223.0,0.7480604216632223,2,15,,Tabular Playground Series - Nov 2021
4362,79019073,360.0,0.7444912335135234,75,161,/lordozvlad/tps-nov-logistic-regression-with-pytorch,Tabular Playground Series - Nov 2021
4363,78653846,117.0,,0,6,/lonnieqin/tps-11-2021-catboost,Tabular Playground Series - Nov 2021
4364,78521184,337.0,,9,25,/vivek468/tps-nov-auto-eda-to-the-rescue,Tabular Playground Series - Nov 2021
4365,78707139,399.0,,1,6,/vijayshankar756/let-s-do-it,Tabular Playground Series - Nov 2021
4366,78652446,390.0,0.7484580226902852,5,36,/alexryzhkov/lightautoml-november-21,Tabular Playground Series - Nov 2021
4367,80207136,237.0,0.7479985835740385,14,27,/bibhash123/tps-denoising-autoencoder-tf-keras-starter,Tabular Playground Series - Nov 2021
4368,80903117,166.0,0.7453287200720969,0,7,/te5serer/0-745-linearregression-score,Tabular Playground Series - Nov 2021
4369,78650829,242.0,0.7455018026989421,6,15,/gulshanmishra/tps-nov-21-lda-feature-logistic-regression,Tabular Playground Series - Nov 2021
4370,78527393,412.0,0.7446851409792092,0,11,/nikhilkhetan/h20-automl-tps-nov,Tabular Playground Series - Nov 2021
4371,135652634,414.0,,0,11,/anirudhg15/tps-nov-21-simple-baseline-w-autoxgb,Tabular Playground Series - Nov 2021
4372,80857896,342.0,,0,1,/yasht02/notebooka7bee15c27,Tabular Playground Series - Nov 2021
4373,80868338,364.0,0.7381232057903404,3,10,/satoshiss/spam-detection-tabular-playground-nov-2021,Tabular Playground Series - Nov 2021
4374,78512965,336.0,,0,3,/rahulchauhan3j/quick-eda-tps-nov-2021,Tabular Playground Series - Nov 2021
4375,80438034,431.0,0.7482670380686685,0,1,/saraswatitiwari/tabular-playground-series,Tabular Playground Series - Nov 2021
4376,93488437,453.0,,37,78,/sisharaneranjana/model-fitting-with-quantile-transformation,Tabular Playground Series - Nov 2021
4377,78535512,397.0,0.7455163618996342,1,10,/smita09/simple-logistic-regression-0-745,Tabular Playground Series - Nov 2021
4378,80476006,403.0,0.7480239330291173,0,0,/markct/tps202111-simple-nn,Tabular Playground Series - Nov 2021
4379,78537479,244.0,0.7341328866084254,0,12,/nancydrew/basic-eda-and-logistic-regression,Tabular Playground Series - Nov 2021
4380,78631037,268.0,0.6924961339440061,2,9,/tigofat/kick-start-with-neural-nets,Tabular Playground Series - Nov 2021
4381,78631037,268.0,0.6924961339440061,2,9,/tigofat/kick-start-with-neural-nets,Tabular Playground Series - Nov 2021
4382,79272209,516.0,0.7404830701574909,3,9,/vladlee/tabular-nov-21-lgbm,Tabular Playground Series - Nov 2021
4383,79272209,516.0,0.7404830701574909,3,9,/vladlee/tabular-nov-21-lgbm,Tabular Playground Series - Nov 2021
4384,79266856,361.0,,11,17,/ransakaravihara/tps-nov-2021-apply-different-transformations,Tabular Playground Series - Nov 2021
4385,78721028,410.0,0.7012330734661728,0,5,/stpeteishii/tps1121-lightgbm,Tabular Playground Series - Nov 2021
4386,79914479,313.0,,2,9,/akmeghdad/tps-1121-essential-personal-notes,Tabular Playground Series - Nov 2021
4387,78504580,317.0,0.7383613460564248,1,13,/yekahaaagayeham/tps-nov-21-spam-detection,Tabular Playground Series - Nov 2021
4388,78823784,352.0,0.7447835525328003,0,6,/jaredsavage/tps-nov-21-keras-randomsearchcv-k-fold-pred,Tabular Playground Series - Nov 2021
4389,78547362,327.0,0.7056379469310232,1,11,/egorovalexeyd/tps-november-lgbm-parameters-tuning-example,Tabular Playground Series - Nov 2021
4390,80125666,512.0,0.729013263427829,6,14,/rahiegadekar/tps-november-2021-a-beginners-approach,Tabular Playground Series - Nov 2021
4391,79420999,490.0,0.7465331513069784,16,31,/criskiev/game-over-or-eda-of-the-leaked-train-csv,Tabular Playground Series - Nov 2021
4392,78969759,559.0,0.7479462418770609,1,4,/makonori/tabular-nov2021-based-on-outlier-replace-keras,Tabular Playground Series - Nov 2021
4393,78882810,353.0,0.7399563007902052,5,14,/mohammadkashifunique/tps-nov-complete-eda-model-prediction,Tabular Playground Series - Nov 2021
4394,79683438,507.0,,1,5,/kmkmks/simple-lofo-feature-importance,Tabular Playground Series - Nov 2021
4395,79107214,454.0,,0,15,/bcruise/tps-nov-2021-simple-keras-model,Tabular Playground Series - Nov 2021
4396,78529236,282.0,0.5388129547755753,3,14,/lucasmorin/data-exploration-with-umap-hdbscan,Tabular Playground Series - Nov 2021
4397,81063601,204.0,0.7471335375709557,1,14,/lavrovlavrov/tps-nov-2021-simple-neural-network-with-keras,Tabular Playground Series - Nov 2021
4398,81214768,476.0,0.7469866873145756,13,30,/daking97/simple-nn,Tabular Playground Series - Nov 2021
4399,80862254,524.0,0.745918454531143,0,1,/danielkondo/a-simple-neural-network-for-playground,Tabular Playground Series - Nov 2021
4400,79098701,474.0,,1,26,/shivansh002/lstm-lgbm-spammer,Tabular Playground Series - Nov 2021
4401,79112771,500.0,0.7347275936437255,2,10,/ayhampar/0-73-score-predicting-value-using-pytorch,Tabular Playground Series - Nov 2021
4402,81044480,455.0,,4,13,/jhyeonlee/tensorflow-resdnn-playground-nov,Tabular Playground Series - Nov 2021
4403,80808767,498.0,,5,9,/chizenkomamiya/kdeplt-ordered-by-kld,Tabular Playground Series - Nov 2021
4404,78976798,535.0,0.7435266419517715,1,7,/tqrahman/quick-dirty-baseline-with-tensorflow,Tabular Playground Series - Nov 2021
4405,80317811,513.0,,4,7,/rajatpaliwal02/tps-nov-keras-sequential-api-keras-tuner,Tabular Playground Series - Nov 2021
4406,80200560,693.0,0.7347227515140683,11,16,/rayhanlahdji/tps-1121-naive-bayes-for-naive-souls,Tabular Playground Series - Nov 2021
4407,83756673,372.0,,1,2,/vasenkovartem/november-kaggle-competition,Tabular Playground Series - Nov 2021
4408,78925507,294.0,0.7469491381016213,0,4,/anishghiya/tps-nov-dtale-autoviz-h2o,Tabular Playground Series - Nov 2021
4409,80974572,537.0,,2,14,/ellavs/tabular-playground-nov-21-very-simple-xgb,Tabular Playground Series - Nov 2021
4410,79407647,470.0,,0,7,/heliksmersenburg/reduce-outliers-in-line,Tabular Playground Series - Nov 2021
4411,78549570,504.0,0.7471137036860938,2,17,/abhishek/autoxgb-nov-2021-tps,Tabular Playground Series - Nov 2021
4412,79540813,441.0,,1,6,/peressim/tabular-playground-series-nov-2021-eda,Tabular Playground Series - Nov 2021
4413,81346636,595.0,,0,10,/jirkaborovec/playing-tabular-with-lightning-flash,Tabular Playground Series - Nov 2021
4414,80914018,586.0,,0,1,/jlg17373/keras-tps-nov-21,Tabular Playground Series - Nov 2021
4415,80081318,478.0,,0,7,/govindlipne/my-first-tps-using-nn-pca-and-lr,Tabular Playground Series - Nov 2021
4416,79142960,773.0,,2,15,/pinstripezebra/tps-xgboost-approach,Tabular Playground Series - Nov 2021
4417,78666916,534.0,0.74150681725019,4,6,/santhoshkumarv/logisticregression-from-scratch-0-74150,Tabular Playground Series - Nov 2021
4418,79808126,591.0,0.7402768991111315,0,3,/anushpoghosyan/tabular-data-modelling-xgboost-lightgbm-tabnet,Tabular Playground Series - Nov 2021
4419,79808126,591.0,0.7402768991111315,0,3,/anushpoghosyan/tabular-data-modelling-xgboost-lightgbm-tabnet,Tabular Playground Series - Nov 2021
4420,79440889,828.0,0.7438846222259053,4,15,/yusufmuhammedraji/pytorch-cv-earlystopping-lrscheduler,Tabular Playground Series - Nov 2021
4421,78803183,713.0,,0,7,/chitwanmanchanda/tabular-playground-series-baseline,Tabular Playground Series - Nov 2021
4422,78838795,707.0,,0,5,/rmcabato/a-brisk-29-model-comparison-using-lazy-predict,Tabular Playground Series - Nov 2021
4423,78766578,781.0,,0,1,/yjs007/basic-artificial-neural-network,Tabular Playground Series - Nov 2021
4424,78500222,774.0,0.7408051702148525,0,8,/justinvanzyl/sal-autogluon,Tabular Playground Series - Nov 2021
4425,81102389,821.0,0.7454592514992281,3,7,/sk4ddd/simple-approach-using-tensorflow,Tabular Playground Series - Nov 2021
4426,79290678,605.0,0.745521969902869,6,33,/alexeykolobyanin/tps-nov-log-regression-with-sklearnex-17x-speedup,Tabular Playground Series - Nov 2021
4427,80781773,616.0,,15,30,/merlinschaefer/tps-nov-21-different-non-nn-models,Tabular Playground Series - Nov 2021
4428,81136345,657.0,,0,0,/phelix125/notebook6fed77caec,Tabular Playground Series - Nov 2021
4429,79016058,613.0,,0,3,/j3rome/kaggle-nov21-r-tidymodels-logistic-regression,Tabular Playground Series - Nov 2021
4430,78943782,628.0,0.7455208134897867,0,4,/lazybuttryingfinal/xgb-bin-logistic-gblinear-lr0-61-kfold-scaler,Tabular Playground Series - Nov 2021
4431,80280444,630.0,,3,14,/jsmithperera/lr-model,Tabular Playground Series - Nov 2021
4432,79498204,642.0,,3,23,/mayurdalvi/tabular-playground-series-simple-and-easy,Tabular Playground Series - Nov 2021
4433,78531164,646.0,,2,20,/bhuppi2898/tps-november-eda-easy-way,Tabular Playground Series - Nov 2021
4434,80799619,632.0,0.7455204985772967,5,14,/ramonferreiracruz/tps-nov-2021-logistic-regression,Tabular Playground Series - Nov 2021
4435,78970690,637.0,,1,3,/kritchais/nov21-classification-logistic-regression,Tabular Playground Series - Nov 2021
4436,79774422,662.0,0.7455201512532291,0,4,/verfuhrer/notebooka5f788d399,Tabular Playground Series - Nov 2021
4437,81160801,684.0,,2,8,/ahmetekiz/tps-nov-2021-starter-with-xgboost,Tabular Playground Series - Nov 2021
4438,79965304,673.0,0.7455148161474761,2,14,/tunguz/tps-nov-2021-simple-linear-baseline,Tabular Playground Series - Nov 2021
4439,78700436,675.0,,0,8,/mfedeli/tabular-playground-series-nov-2021,Tabular Playground Series - Nov 2021
4440,90134220,695.0,,2,5,/maulberto3/tps-nov2021-inspecting-labels-w-pca-and-k-means,Tabular Playground Series - Nov 2021
4441,79374581,700.0,,12,43,/gaganmaahi224/tps-nov-21-autoviz-simple-ann-for-beginners,Tabular Playground Series - Nov 2021
4442,79321624,702.0,0.6842993489704458,0,7,/nicholasvolpe/november-tps-rf-baseline,Tabular Playground Series - Nov 2021
4443,80788610,716.0,0.7454357951203749,2,16,/kiranclement/tabular-playground-series-nov-2021-base-model,Tabular Playground Series - Nov 2021
4444,80807786,834.0,,0,6,/kreyttsfeldt/november-2021-competition,Tabular Playground Series - Nov 2021
4445,78501327,727.0,,2,13,/brbarasulpis/tps-2021-nov-exploratory-data-analysis-eda,Tabular Playground Series - Nov 2021
4446,79030281,731.0,0.7351603778385677,0,10,/bibhuprasad97/tabular-playground-series-nov-2021,Tabular Playground Series - Nov 2021
4447,78824404,756.0,0.7453105403781285,0,15,/eduardogutierrez/tps-nov-21-exploratory-data-analysis-submission,Tabular Playground Series - Nov 2021
4448,81100991,734.0,0.7452922534458534,0,3,/ashishtop/tabular-nov2021-starter-lr,Tabular Playground Series - Nov 2021
4449,81100991,734.0,0.7452922534458534,0,3,/ashishtop/tabular-nov2021-starter-lr,Tabular Playground Series - Nov 2021
4450,81100991,734.0,0.7452922534458534,0,3,/ashishtop/tabular-nov2021-starter-lr,Tabular Playground Series - Nov 2021
4451,81182795,837.0,0.7391182322237326,3,7,/nitishraj/tabular-playground-nov21-nn-with-keras,Tabular Playground Series - Nov 2021
4452,80027858,804.0,0.6612318828408695,6,23,/kishalmandal/pytorch-tps-dec-baseline,Tabular Playground Series - Nov 2021
4453,79076793,848.0,0.738592177511729,0,11,/dienhoa/tabular-playgroud-fastai,Tabular Playground Series - Nov 2021
4454,80898952,800.0,0.7447968240735273,0,9,/sinkevichgerman/november-2021,Tabular Playground Series - Nov 2021
4455,80240983,814.0,0.7446655721890416,1,11,/rsesha/nov-tps-dnn-in-5-mins-0-7446-score,Tabular Playground Series - Nov 2021
4456,81226172,799.0,,0,10,/scchuy/tab-pytorch-resnet-2021-11,Tabular Playground Series - Nov 2021
4457,78558607,861.0,0.7387930722733468,2,21,/ahmedhaytham/nov22-0,Tabular Playground Series - Nov 2021
4458,78795791,847.0,,0,4,/nesterenkomarina/tps1121-deep-net-tensorflow,Tabular Playground Series - Nov 2021
4459,79389944,854.0,0.6396443123448127,17,24,/venkatkumar001/tps-baseline-xgb-optuna-cat-lgbm,Tabular Playground Series - Nov 2021
4460,79389944,854.0,0.6695876556064592,17,24,/venkatkumar001/tps-baseline-xgb-optuna-cat-lgbm,Tabular Playground Series - Nov 2021
4461,79389944,854.0,0.7391024519868742,17,24,/venkatkumar001/tps-baseline-xgb-optuna-cat-lgbm,Tabular Playground Series - Nov 2021
4462,79389944,854.0,0.7086466196590084,17,24,/venkatkumar001/tps-baseline-xgb-optuna-cat-lgbm,Tabular Playground Series - Nov 2021
4463,80713833,843.0,0.7397430216047475,2,9,/christoforum/tps-nov-2021-lightgbm-optuna,Tabular Playground Series - Nov 2021
4464,83116983,866.0,,0,3,/flezzer/tabular-playground-series-nov-2021,Tabular Playground Series - Nov 2021
4465,78557233,862.0,0.7434517754086938,1,8,/alxbkr/flaml-quick-low-effort-automl-solution-nov,Tabular Playground Series - Nov 2021
4466,79463047,864.0,0.7413651940609706,7,12,/sudipg411/eda-feature-engineering-xgboost-model,Tabular Playground Series - Nov 2021
4467,80788889,917.0,0.742175810621312,1,17,/samuelcortinhas/tabular-regular-neural-network,Tabular Playground Series - Nov 2021
4468,80605558,885.0,0.701210589434652,0,0,/drag88/november-playground-series-eda-baseline,Tabular Playground Series - Nov 2021
4469,80136193,898.0,0.7410791044669066,3,13,/tariqchhussain/xgboost-optuna-w-k-fold-cv-tps-nov-21,Tabular Playground Series - Nov 2021
4470,79052736,937.0,,3,10,/shivampr21/feature-analysis-with-pca,Tabular Playground Series - Nov 2021
4471,78989059,907.0,0.740825875210884,0,5,/sankalpsrivastava26/noise-reduction-with-tf-models,Tabular Playground Series - Nov 2021
4472,78733168,912.0,,4,16,/tharunreddy/xgboost-optuna-vanilla,Tabular Playground Series - Nov 2021
4473,78634918,915.0,0.7406304978201264,11,24,/seungbumlim/tps-nov-2021-simple-eda-lgbmclassifier-optuna,Tabular Playground Series - Nov 2021
4474,81077561,946.0,,4,22,/slythe/voting-ensemble-xgb-lgb-linear-nn-tps-nov-21,Tabular Playground Series - Nov 2021
4475,78617387,933.0,0.7317568856771327,10,22,/ranjeetshrivastav/tps-nov-21-pycaret,Tabular Playground Series - Nov 2021
4476,78721142,932.0,0.7403101469876054,0,3,/lagsfinder/autoxgb-to-the-rescue-medium-perf-score-0-74031,Tabular Playground Series - Nov 2021
4477,78842775,926.0,0.737395236152306,3,5,/datascientistsohail/tps-nov2021-lgbm-hyperparametertuning,Tabular Playground Series - Nov 2021
4478,79054831,943.0,0.7402196046449753,0,14,/nancysamuel/comparison-of-basic-models,Tabular Playground Series - Nov 2021
4479,78761220,944.0,,4,6,/shivarama/tps-nov-2021-xgboost-optuna-starter-101,Tabular Playground Series - Nov 2021
4480,80126306,983.0,,0,7,/hyunw3/lightgbm-tabular-beginner-s-notebook,Tabular Playground Series - Nov 2021
4481,80500175,973.0,0.7280542828703841,0,9,/juliorsleite/pipeline-randomizedsearchcv-xgboost-tpc-nov21,Tabular Playground Series - Nov 2021
4482,79055457,967.0,,0,14,/ahmedaffan789/tabular-playground-series-beginners-eda-and-xgb,Tabular Playground Series - Nov 2021
4483,80967492,969.0,0.7390300625286359,0,0,/josephy93/tps-nov-xgboost-baseline,Tabular Playground Series - Nov 2021
4484,79994877,993.0,0.735432573469569,2,6,/biancayan/tps-11-1-stacking,Tabular Playground Series - Nov 2021
4485,78693905,1022.0,,2,7,/hakanerdogan/tps-nov-2021-simple-code-with-catboost,Tabular Playground Series - Nov 2021
4486,141913970,1025.0,,0,10,/haozhang607/tabular-playground-series-nov-2021,Tabular Playground Series - Nov 2021
4487,78903492,1037.0,0.7337079682233291,0,3,/ottpocket/november-muddling-label-regularization,Tabular Playground Series - Nov 2021
4488,78936588,1063.0,0.7241805933497505,0,2,/yukiyamamoto/lightgbm-baseline-without-preprocessing,Tabular Playground Series - Nov 2021
4489,80680625,1060.0,,3,8,/alihammad99/tabular-playground-series-nov-2021,Tabular Playground Series - Nov 2021
4490,79059876,1089.0,0.5053344605226433,1,9,/amanb096/tabular-playground-pca-technique,Tabular Playground Series - Nov 2021
4491,81403613,1044.0,,4,15,/nidhi1502/dealing-with-large-dataset,Tabular Playground Series - Nov 2021
4492,81146302,1084.0,0.7339766618033627,4,9,/jokkojja/pipelines-and-gridsearch-for-logreg,Tabular Playground Series - Nov 2021
4493,79879382,1097.0,0.7334154429303692,0,7,/jjung2019/tabular-playground-series-nov-2021-python,Tabular Playground Series - Nov 2021
4494,79452365,1119.0,,2,3,/hyoungseocho/first-submission-randomforest-vs-dnn,Tabular Playground Series - Nov 2021
4495,78579437,1048.0,0.7004165618000406,0,2,/danielbissell/tps-nov-xgboost-baseline,Tabular Playground Series - Nov 2021
4496,79058951,1123.0,,7,20,/gavisr/starter-notebook,Tabular Playground Series - Nov 2021
4497,81120454,1143.0,0.6525329673012497,0,1,/nikhilsatani/tabular-playground-nov-2021,Tabular Playground Series - Nov 2021
4498,80188393,1132.0,0.7306856250121105,1,8,/markosthabit/tbs-november-naive-bayes,Tabular Playground Series - Nov 2021
4499,78913353,1135.0,,5,12,/yaswanthgali/combining-3-models-for-prediction,Tabular Playground Series - Nov 2021
4500,88475838,1151.0,,2,15,/nafishamoin/tabular-playground-november-2021,Tabular Playground Series - Nov 2021
4501,79691552,1133.0,0.7286520513992804,0,4,/saiful873/tpsnov2021-eda-prediction,Tabular Playground Series - Nov 2021
4502,78544203,1147.0,0.724032953411288,0,13,/carlmcbrideellis/tps-nov-2021-h2o-ai-gbm-model,Tabular Playground Series - Nov 2021
4503,79406201,1181.0,0.5676930798450515,0,1,/arpitjjain/tabular-playground-series-nov-2021,Tabular Playground Series - Nov 2021
4504,81186666,1192.0,0.7097355966524802,1,11,/loycelorenzo/tabular-playground-series-nov-2021,Tabular Playground Series - Nov 2021
4505,80661543,1219.0,0.7033941570268315,0,13,/alexandermandrov/map-tab-nov,Tabular Playground Series - Nov 2021
4506,78977723,1249.0,,0,1,/whitishlion/tabular-nov2021,Tabular Playground Series - Nov 2021
4507,80569599,1258.0,0.6828869950635066,2,11,/ofirmazor/rainy-november-playground,Tabular Playground Series - Nov 2021
4508,81149945,1264.0,0.6790839285701246,2,7,/kshitijbarnwal/tps-nov-xgboost-kfold,Tabular Playground Series - Nov 2021
4509,79196982,1266.0,,0,2,/asimzahid/rapids-xgboost,Tabular Playground Series - Nov 2021
4510,78608351,1269.0,0.6747775412855226,0,3,/tracyporter/nov-21-tabular-com-lrcv,Tabular Playground Series - Nov 2021
4511,78709400,1355.0,,3,7,/mingookkim/simple-easy-eda,Tabular Playground Series - Nov 2021
4512,81090313,1339.0,,0,8,/njelicic/tps-nov-nick,Tabular Playground Series - Nov 2021
4513,78680995,419.0,0.0,1,1,/weihong1510/lgbm-scoring,G-Research Crypto Forecasting
4514,78721720,829.0,,2,17,/konradb/super-simple-baseline,G-Research Crypto Forecasting
4515,78768918,371.0,0.0,3,30,/danofer/g-research-starter-0-361-lb,G-Research Crypto Forecasting
4516,78750573,484.0,0.0,2,77,/code1110/gresearch-simple-lgb-starter,G-Research Crypto Forecasting
4517,78767941,628.0,0.0,1,43,/shivansh002/i-purchased-bitcoin,G-Research Crypto Forecasting
4518,78763505,1352.0,0.0,9,117,/metathesis/torch-lstm-baseline-training-updated,G-Research Crypto Forecasting
4519,81206527,694.0,,0,1,/ankithanwate/g-research-starter-lgbm-pipeline-lb-0-174,G-Research Crypto Forecasting
4520,78787987,862.0,,1,25,/adityasharma01/g-research-starter-lgbm-pipeline-lb-0-5799,G-Research Crypto Forecasting
4521,80480812,222.0,,0,2,/avivlevi815/classic-pipeline,G-Research Crypto Forecasting
4522,80406289,1332.0,,1,2,/johnrizcallah/lightgbm-with-techindicators-scaledtarget,G-Research Crypto Forecasting
4523,78860535,872.0,,14,56,/gaganmaahi224/auto-eda-and-lgbmregressor-for-beginners,G-Research Crypto Forecasting
4524,79238299,1713.0,,0,12,/soumya9977/check-out-abhishek-thaku-s-autoxgb-in-action,G-Research Crypto Forecasting
4525,78673478,775.0,,0,17,/junichiromorita/tutorial-to-the-g-research-crypto-competition-jpn,G-Research Crypto Forecasting
4526,78787350,485.0,,11,29,/hamzaghanmi/g-research-crypto-forecasting-eda,G-Research Crypto Forecasting
4527,78916593,1601.0,,35,278,/julian3833/g-research-starter-lgbm-pipeline,G-Research Crypto Forecasting
4528,78970821,885.0,,0,1,/zhongguo/fork-of-g-research-starter,G-Research Crypto Forecasting
4529,78701231,890.0,,0,2,/haiyunhu/detailed-api-introduction,G-Research Crypto Forecasting
4530,80376302,896.0,,0,3,/colt2brbr/check-data-lightbgm-template,G-Research Crypto Forecasting
4531,78706224,520.0,,0,2,/neoistheone/myfirstmodification,G-Research Crypto Forecasting
4532,78777605,916.0,,1,5,/tom99763/end-to-end-training,G-Research Crypto Forecasting
4533,78851535,1782.0,,1,4,/seraphwedd18/g-research-crypto-exploring-the-data,G-Research Crypto Forecasting
4534,80308488,634.0,,0,7,/sergears/simplified-two-asset-model-feature-engineering,G-Research Crypto Forecasting
4535,80077283,952.0,,2,9,/kumudsingh9/g-research-crypto-prediction,G-Research Crypto Forecasting
4536,78806477,1462.0,,0,9,/tarlannazarov/g-research-crypto-starter-xgb-pipeline,G-Research Crypto Forecasting
4537,78711993,1798.0,,0,13,/tfukuda675/g-research-data-over-view-and-visualization,G-Research Crypto Forecasting
4538,81720995,231.0,,14,34,/whitecat0022/g-research-crypto-forecasting-lightgbm,G-Research Crypto Forecasting
4539,80196132,972.0,,0,6,/suneetsaini/beginner-s-lgbm-xgb-catboost,G-Research Crypto Forecasting
4540,79049844,1852.0,,0,2,/eranuragsingh/anurag-research-crypto-forecasting,G-Research Crypto Forecasting
4541,80476951,1465.0,,1,7,/kuboko/crypto-datacomplement-plot,G-Research Crypto Forecasting
4542,84355667,979.0,,0,0,/hiroki8383/base-analysis,G-Research Crypto Forecasting
4543,80933363,1574.0,0.0,0,8,/dragonzhang/i-purchased-bitcoin,G-Research Crypto Forecasting
4544,81036668,1444.0,0.0,1,13,/yliu27/g-research-starter-lgbm-pipeline-copied,G-Research Crypto Forecasting
4545,81163781,1001.0,,0,7,/aquiver123/g-research-guada,G-Research Crypto Forecasting
4546,81320460,1004.0,,6,19,/get2jawa/crypto-forecast-simple-basic-eda,G-Research Crypto Forecasting
4547,87587802,486.0,,0,2,/theodorospsarras/cryptocurrency-forecasting,G-Research Crypto Forecasting
4548,82570089,805.0,,0,0,/nik0lis/final-version,G-Research Crypto Forecasting
4549,81537827,680.0,,5,10,/knightbearr/22-simple-python-program-knightbearr,G-Research Crypto Forecasting
4550,82244471,1875.0,,0,2,/aralai/speed-up-data-loading,G-Research Crypto Forecasting
4551,80407545,1519.0,,2,13,/alexisalvarez/eda-resampling-the-power-of-technical-analysis,G-Research Crypto Forecasting
4552,86685771,1026.0,,0,3,/xuantianfengwu/digital-currency-competition,G-Research Crypto Forecasting
4553,82091659,149.0,,40,109,/junjitakeshima/crypto-beginner-s-try-for-simple-lgbm-en-jp,G-Research Crypto Forecasting
4554,80780145,1504.0,,1,3,/rkellner/descriptive-analysis,G-Research Crypto Forecasting
4555,84055276,1397.0,,0,5,/mdominguez2010/crypto-competish,G-Research Crypto Forecasting
4556,82178200,1037.0,,0,12,/kazutaka65k/the-g-research-crypto-competition-simple-lgbm,G-Research Crypto Forecasting
4557,85382470,1043.0,,0,0,/martinshengyenlin/lightgbm-original-with-sup-data-test,G-Research Crypto Forecasting
4558,82454818,234.0,0.0,0,0,/negstek/g-research-crypto-forecasting-modelization,G-Research Crypto Forecasting
4559,82523423,1628.0,,0,2,/neosoonhua/5-9-mem-reduced-remove-test-data-from-train-data,G-Research Crypto Forecasting
4560,84530418,1780.0,,3,4,/sddarkblue/crypto,G-Research Crypto Forecasting
4561,83879078,1113.0,,0,0,/ycliffd/g-research-crypto-competition-baseline-0001,G-Research Crypto Forecasting
4562,83343876,1073.0,,0,0,/tangjiantin/strict-light-gbm,G-Research Crypto Forecasting
4563,85282094,1316.0,,0,4,/linjoseph/g-research-parallel-lstm-training,G-Research Crypto Forecasting
4564,83760294,1317.0,,17,86,/h1yung/crypto-forecasting-using-lgbm,G-Research Crypto Forecasting
4565,81295062,1542.0,,2,1,/wolfgangb33r/crypto-randomforestregressor,G-Research Crypto Forecasting
4566,83445524,1365.0,0.0,0,0,/sajidurrehman1/version-1-0,G-Research Crypto Forecasting
4567,85136971,107.0,,0,5,/gmw2088/calculate-the-realized-market-series-and-beta,G-Research Crypto Forecasting
4568,103682233,1092.0,,0,0,/ungugu/runningaverage-randomizedsearchcv-lgbm-modelsaving,G-Research Crypto Forecasting
4569,83976761,1671.0,,4,10,/azzamradman/g-research-more-eda,G-Research Crypto Forecasting
4570,84372916,1491.0,0.0,0,0,/xuchenrui/torch-lstm-baseline-training,G-Research Crypto Forecasting
4571,79857202,614.0,,8,28,/vi2018/g-research-crypto-repro-target-computation,G-Research Crypto Forecasting
4572,84514844,731.0,,0,6,/sinrinosekai/prophet-gresearch,G-Research Crypto Forecasting
4573,84373339,390.0,,1,0,/mikhailg0/notebook788638a243,G-Research Crypto Forecasting
4574,84542623,1482.0,0.0,0,4,/ghaiyur/baseline-model-using-lgbmregressor,G-Research Crypto Forecasting
4575,86045528,1557.0,0.0,2,12,/loicge/baseline-model-with-lgbm,G-Research Crypto Forecasting
4576,84046035,119.0,,0,0,/maratkhisamutdinov/g-research-xgboost-starter-notebook,G-Research Crypto Forecasting
4577,84764773,275.0,,0,2,/platonfedorov/g-research-crypto-forecasting-test-lgbm,G-Research Crypto Forecasting
4578,85674581,1354.0,,2,1,/fanyuanlai/g-research-crypto-forecasting,G-Research Crypto Forecasting
4579,84893187,1350.0,0.0,0,3,/limweixuan1994/cryptocurrency-forecasting,G-Research Crypto Forecasting
4580,85456108,1804.0,,0,8,/qtphan110522604/g-research-gru-training-modified,G-Research Crypto Forecasting
4581,85083100,1524.0,,0,3,/michelleting/220113,G-Research Crypto Forecasting
4582,85317480,1176.0,0.0,0,28,/parikshitsharma2001/crypto,G-Research Crypto Forecasting
4583,94712678,55.0,,0,2,/nishimoto/g-research-simple-lightgbm-lb-0-0123-55th,G-Research Crypto Forecasting
4584,85654611,1575.0,,0,3,/andreybabushkin/xgboost,G-Research Crypto Forecasting
4585,85326472,1552.0,,0,0,/wangyashuu/g-research-crypto-forecasting-1-intro-explore,G-Research Crypto Forecasting
4586,78776180,1797.0,,0,7,/faisalalsrheed/g-research-csv-to-pickle-feather-parquet-jay,G-Research Crypto Forecasting
4587,82849716,1514.0,,0,8,/mattgrowden/gresearch-1st-test-submission,G-Research Crypto Forecasting
4588,85690557,123.0,,1,3,/freedom870601/gresearch-submitting-lagged-features-via-api,G-Research Crypto Forecasting
4589,85084637,602.0,,0,1,/rizkynindra/crypto-v2,G-Research Crypto Forecasting
4590,85570413,89.0,0.0,1,5,/yrtchn/simple-baseline-based-on-one-prop-score-around-02,G-Research Crypto Forecasting
4591,85216645,109.0,,0,2,/craniket/g-research-data-creation,G-Research Crypto Forecasting
4592,85686208,1209.0,0.0,0,12,/maricinnamon/g-research-forecast-overlap-score-0-9999,G-Research Crypto Forecasting
4593,85091897,1787.0,,0,0,/frankihalberd/notebook34b0ed51cb,G-Research Crypto Forecasting
4594,86820278,59.0,,2,6,/petersk20/tree-based-methods,G-Research Crypto Forecasting
4595,85613085,1505.0,,1,1,/watchman/lama-crypto-forecasting,G-Research Crypto Forecasting
4596,85496038,851.0,,1,12,/weiczh/g-research-crypto-forecasting-test,G-Research Crypto Forecasting
4597,85684803,528.0,,0,2,/ttyryan/crypto-forecasting-visualization,G-Research Crypto Forecasting
4598,85694178,1226.0,,5,11,/aviral23/time-series-store-sales-analysis-plotly,G-Research Crypto Forecasting
4599,85023117,720.0,,0,2,/rashmikagamage/g-research-crypto-forecast,G-Research Crypto Forecasting
4600,85962497,1580.0,0.0,17,63,/corneliuskristianto/crypto-technical-indicator-and-ml-prediction,G-Research Crypto Forecasting
4601,85811130,723.0,,6,46,/vbmokin/g-research-crypto-forecasting-baseline-fe,G-Research Crypto Forecasting
4602,85843877,1647.0,0.0,0,4,/amareshmarekar/crypto-forecasting-with-lgbm-gridsearch,G-Research Crypto Forecasting
4603,85954807,532.0,,0,3,/houssemayed/benchmarking-for-cryptocurrency-forecasting,G-Research Crypto Forecasting
4604,85918240,241.0,,0,7,/mmisty/lstm-6-features-by-r,G-Research Crypto Forecasting
4605,83947696,684.0,,0,5,/ktaichi/eda-g-research-crypto-competition,G-Research Crypto Forecasting
4606,86220117,198.0,0.0,1,5,/tanaybanerjee/exploring-g-research-crypto-and-time-series,G-Research Crypto Forecasting
4607,79280510,1779.0,,10,81,/carlmcbrideellis/plotting-ohlc-and-v-ticker-data-using-mplfinance,G-Research Crypto Forecasting
4608,85938983,195.0,,0,1,/ankit001/mlp-prediction,G-Research Crypto Forecasting
4609,86064483,1253.0,0.0,5,27,/jillanisofttech/g-research-using-the-overlap-fully-accuracy,G-Research Crypto Forecasting
4610,86064483,1253.0,0.0,5,27,/jillanisofttech/g-research-using-the-overlap-fully-accuracy,G-Research Crypto Forecasting
4611,79201287,16.0,,1,25,/ebudia/recreating-target-min-periods-3750,G-Research Crypto Forecasting
4612,86140120,1758.0,0.0,0,2,/korinyamada/notebook295f151a9f,G-Research Crypto Forecasting
4613,86153964,1260.0,0.0,1,11,/mayank00rastogi/g-research-forecast-overlap,G-Research Crypto Forecasting
4614,86153964,1260.0,0.0,1,11,/mayank00rastogi/g-research-forecast-overlap,G-Research Crypto Forecasting
4615,86754997,9.0,,2,7,/bturan19/lgb-3fold-rollingagg-lagtarget-submissioninference,G-Research Crypto Forecasting
4616,81514165,1264.0,,2,2,/saraswatitiwari/g-research-crypto-forecasting,G-Research Crypto Forecasting
4617,85044774,73.0,,2,8,/wptouxx/g-research-cointegration-analysis,G-Research Crypto Forecasting
4618,95272640,599.0,,0,0,/mobiliser/final-draft,G-Research Crypto Forecasting
4619,78864216,196.0,,4,13,/vmuzhichenko/g-research-simple-mlp-starter,G-Research Crypto Forecasting
4620,86586938,1451.0,0.0,0,3,/natnitarach/crypto-forecasting-0-1-lgbm-qho,G-Research Crypto Forecasting
4621,86632220,1538.0,,7,60,/nrcjea001/lgbm-embargocv-weightedpearson-lagtarget,G-Research Crypto Forecasting
4622,85799880,277.0,,0,5,/syxuming/pytorch-lstm-14-model-traning-inference,G-Research Crypto Forecasting
4623,84455629,229.0,,0,3,/tknakamu/eda-predict-value-from-other-assets,G-Research Crypto Forecasting
4624,85459366,1632.0,,1,19,/kitopl/g-research-data-outline,G-Research Crypto Forecasting
4625,78853469,27.0,,5,22,/berserker408/crypto-tf-keras-nn-with-asset-embedding,G-Research Crypto Forecasting
4626,94712806,160.0,,0,1,/sanjayanbu/crypto-forecasting,G-Research Crypto Forecasting
4627,80137517,546.0,,0,1,/yassinemesbahi/data-cleaning-candlestick-plot-rel-analysis,G-Research Crypto Forecasting
4628,84089652,396.0,,0,3,/stpeteishii/g-research-crypto-train-data-eda,G-Research Crypto Forecasting
4629,86614529,1532.0,,0,1,/devcon/g-research-crypto-eda-vs-binance,G-Research Crypto Forecasting
4630,86885068,482.0,,2,11,/yassershrief/lgbm-regressor-forecasting-and-evaluation,G-Research Crypto Forecasting
4631,81300661,87.0,,1,10,/osamurai/fft-analysis-tutorial,G-Research Crypto Forecasting
4632,87030978,435.0,,0,0,/zuyderzee/crypto-challenge-mlii-project-submission,G-Research Crypto Forecasting
4633,88425876,112.0,,0,3,/fritzcremer/consecutive-ones-prediction,G-Research Crypto Forecasting
4634,81438815,1592.0,,1,2,/mbonyani/step1-eda,G-Research Crypto Forecasting
4635,82192157,13.0,,9,42,/tomforbes/gresearch-submitting-lagged-features-via-api,G-Research Crypto Forecasting
4636,86654827,629.0,0.0,0,0,/vclavmatjka/notebook9a17029bcc,G-Research Crypto Forecasting
4637,86671722,1591.0,0.0,0,1,/favournwajoko/g-research-crypto-simple-xgb-regression,G-Research Crypto Forecasting
4638,83052344,28.0,,0,10,/axzhang/s-baseline-lgb-reproduce-the-lb-score,G-Research Crypto Forecasting
4639,88046063,1649.0,,5,26,/rafalradwanski/g-research-features-to-increase-your-score,G-Research Crypto Forecasting
4640,103424026,108.0,,0,2,/tangtunyu/lstm-starter,G-Research Crypto Forecasting
4641,86086266,1300.0,,39,216,/odins0n/g-research-plots-eda,G-Research Crypto Forecasting
4642,88650987,1429.0,,0,3,/kazuyasumatsudaf/team-1-arima,G-Research Crypto Forecasting
4643,94987963,3.0,,11,83,/sugghi/training-3rd-place-solution,G-Research Crypto Forecasting
4644,84616805,1446.0,,0,7,/yshiml/g-reseach-eda-baseline,G-Research Crypto Forecasting
4645,83047378,1809.0,,2,13,/jagofc/target-reconstruction-what-s-up-with-2018-01-03,G-Research Crypto Forecasting
4646,78922985,797.0,,12,43,/lucasmorin/load-external-data-yfinance-pca-t-sne-umap,G-Research Crypto Forecasting
4647,81408706,761.0,0.8332426254490041,21,38,/vaby667/roberta-infere,Jigsaw Rate Severity of Toxic Comments
4648,81673615,800.0,,3,7,/ympaik/binary-classification-w-tfidf-xgboost,Jigsaw Rate Severity of Toxic Comments
4649,85850016,862.0,0.8866877108958311,27,65,/ayhampar/very-simple-code-with-score-0-886,Jigsaw Rate Severity of Toxic Comments
4650,80140819,278.0,,3,15,/vanle73/back-translation-offline-for-data-augmentation,Jigsaw Rate Severity of Toxic Comments
4651,80113703,345.0,0.8170240557309242,4,20,/shakshyathedetector/jigsaw-inference-1st-submission,Jigsaw Rate Severity of Toxic Comments
4652,85684100,2030.0,,3,33,/aviral23/how-to-deal-with-toxic-comments,Jigsaw Rate Severity of Toxic Comments
4653,87261677,52.0,,1,35,/cdeotte/rapids-xgb-fil-silver-medal-train-0-804,Jigsaw Rate Severity of Toxic Comments
4654,87053400,2058.0,0.902906280613911,8,46,/shiv28/jigsaw,Jigsaw Rate Severity of Toxic Comments
4655,80118013,664.0,0.7510612822466529,1,2,/sadivamadaan/bert-baseline1,Jigsaw Rate Severity of Toxic Comments
4656,79169412,2069.0,,1,21,/kalilurrahman/jsrtc-toxic-or-not-comments-eda,Jigsaw Rate Severity of Toxic Comments
4657,79464453,130.0,,1,4,/masternoodlemaker/roberta-further-pretrain,Jigsaw Rate Severity of Toxic Comments
4658,84218015,1301.0,0.7770763034722978,1,1,/thanatoz/29-solution-jigsaw-2022,Jigsaw Rate Severity of Toxic Comments
4659,84218015,1301.0,0.7770763034722978,1,1,/thanatoz/29-solution-jigsaw-2022,Jigsaw Rate Severity of Toxic Comments
4660,81867851,2060.0,,0,1,/saraswatitiwari/jigsaw-rate-severity-of-toxic-comments,Jigsaw Rate Severity of Toxic Comments
4661,86329637,1233.0,0.880809839991292,0,7,/darknesszx/overfitting-lb-is-easier-than-solving-the-problem,Jigsaw Rate Severity of Toxic Comments
4662,85959516,1644.0,0.8342222705997605,0,5,/prashantpathak244/bert-model,Jigsaw Rate Severity of Toxic Comments
4663,80213534,1344.0,0.8263851093937085,0,4,/dragonzhang/jrsotc-ridgeregression-ensemble-of-3,Jigsaw Rate Severity of Toxic Comments
4664,85003953,2067.0,0.7456188091868945,0,5,/danielbruintjies/flair-a-very-simple-framework-jigsaw,Jigsaw Rate Severity of Toxic Comments
4665,84951690,1171.0,,0,8,/yshiml/jigsaw-eda-baseline-for-beginners,Jigsaw Rate Severity of Toxic Comments
4666,87009303,1303.0,,15,77,/yanhf16/0-9-try-better-parameters-better-score,Jigsaw Rate Severity of Toxic Comments
4667,79931955,159.0,0.8125612278219223,2,13,/vincentschuler/0-816-jigsaw-inference,Jigsaw Rate Severity of Toxic Comments
4668,80275928,599.0,,1,14,/leolu1998/hatebert-jigsaw-training,Jigsaw Rate Severity of Toxic Comments
4669,86011819,206.0,0.8866877108958311,0,13,/panshaohua/very-simple-code,Jigsaw Rate Severity of Toxic Comments
4670,82259683,288.0,,2,24,/devkhant24/jigsaw-comment-toxicity-bidirectional-gru,Jigsaw Rate Severity of Toxic Comments
4671,81677506,641.0,,0,1,/pavan9065/explore-jigsaw-rate-severity,Jigsaw Rate Severity of Toxic Comments
4672,79949766,852.0,0.822793077174268,5,29,/saurabhbagchi/0-824-jigsaw-inference,Jigsaw Rate Severity of Toxic Comments
4673,82092064,1474.0,0.8190921954936323,2,9,/afiaibnath/extra-dropout-jigsaw-inference,Jigsaw Rate Severity of Toxic Comments
4674,86472522,1406.0,,0,0,/hechtjp/jrstc-util,Jigsaw Rate Severity of Toxic Comments
4675,81439572,830.0,,14,75,,Jigsaw Rate Severity of Toxic Comments
4676,87091407,124.0,0.8568629585283553,0,1,/kpriyanshu256/inf-jigsaw-roberta-base-300-overfit-ridge,Jigsaw Rate Severity of Toxic Comments
4677,79907375,766.0,0.7748993142483944,25,56,/ekaterinadranitsyna/regression-ensemble-lb-0-78,Jigsaw Rate Severity of Toxic Comments
4678,87337279,94.0,,0,9,/vaincookie/how-to-use-optuna-to-get-best-cv-score,Jigsaw Rate Severity of Toxic Comments
4679,86415357,1434.0,,2,11,/sahib12/highest-score-jigsaw-0-90,Jigsaw Rate Severity of Toxic Comments
4680,80578111,671.0,,16,155,/manabendrarout/pytorch-roberta-ranking-baseline-jrstc-train,Jigsaw Rate Severity of Toxic Comments
4681,86923808,1804.0,0.9000761946228366,0,2,/hisudha/toxic-hyper-params-v1,Jigsaw Rate Severity of Toxic Comments
4682,85047715,1799.0,0.7690214433438555,0,5,/harshbansal27/baseline-model-using-multinomialnb,Jigsaw Rate Severity of Toxic Comments
4683,86422261,958.0,0.8620877326657232,5,11,/mayank00rastogi/ensemble-ridge-model,Jigsaw Rate Severity of Toxic Comments
4684,86176425,1410.0,0.8969195602481768,30,88,/thomasdubail/jigsaw-ensemble-best-public-sub-0-898,Jigsaw Rate Severity of Toxic Comments
4685,81291148,62.0,0.8111461848263851,0,4,/gauravbrills/jigsaw-cardiffnlp-twitter-model-inference,Jigsaw Rate Severity of Toxic Comments
4686,86120193,1508.0,0.785675410906716,0,0,/lllljm/jigsaw-comment-toxicity-tf-xlnet,Jigsaw Rate Severity of Toxic Comments
4687,87176612,420.0,0.7920975291172309,0,0,/ilosvigil/jigsaw-infer-debertav3-pytorch-lightning,Jigsaw Rate Severity of Toxic Comments
4688,87269696,60.0,,0,2,/bachngoh/jigsaw-ensemble-61th-place,Jigsaw Rate Severity of Toxic Comments
4689,87399918,1811.0,,0,0,/datalit/jigsaw-robert-0-8125-private-lb,Jigsaw Rate Severity of Toxic Comments
4690,79770580,1229.0,,0,11,/kaushikholla/0-752-eda-baseline-model-svm,Jigsaw Rate Severity of Toxic Comments
4691,86299391,128.0,0.871013388483727,2,0,/yaremamishchenko/jigsaw-ridge-ensemble-tfidf-fasttext-0-868,Jigsaw Rate Severity of Toxic Comments
4692,84640445,1886.0,,12,77,/toru59er/0-866-tfidf-ridge-simple-baseline,Jigsaw Rate Severity of Toxic Comments
4693,80236721,392.0,0.8307390878415152,0,2,/neoistheone/jrsotc-ridgeregression-ensemble-of-3,Jigsaw Rate Severity of Toxic Comments
4694,82737115,306.0,0.7825187765320561,0,1,/psvenom/balls,Jigsaw Rate Severity of Toxic Comments
4695,87092797,95.0,,0,0,/kaerunantoka/jigsaw4-create-additional-pair-w-jigsaw1,Jigsaw Rate Severity of Toxic Comments
4696,86937376,1232.0,0.794165668879939,0,0,/pengyf0709/jigsaw-robert,Jigsaw Rate Severity of Toxic Comments
4697,80836849,61.0,0.8046152171546751,0,3,/hengwdai/lb-804-tiny-bert,Jigsaw Rate Severity of Toxic Comments
4698,85657439,1949.0,0.8531620768477196,0,0,/maryragozina/how-to-deal-with-toxic-comments-857b51,Jigsaw Rate Severity of Toxic Comments
4699,83542856,870.0,0.8442364210297159,12,80,/vitaleey/tfidf-ridge,Jigsaw Rate Severity of Toxic Comments
4700,84979137,1105.0,,3,17,/doohaejung/bert-end-to-end-baseline-3epochs-lb-0-723,Jigsaw Rate Severity of Toxic Comments
4701,87144476,416.0,0.7741373680200283,2,15,/vineethakkinapalli/jigsaw-hatebert-inference,Jigsaw Rate Severity of Toxic Comments
4702,87743263,1319.0,,0,2,/boltmaud/simple-use-of-detoxify-trained-model,Jigsaw Rate Severity of Toxic Comments
4703,80161314,516.0,0.8259497115489278,8,28,/adityasharma01/jrsotc-ridgeregression-ensemble-of-3,Jigsaw Rate Severity of Toxic Comments
4704,87190205,77.0,0.8059214106890171,0,0,/alturutin/inference-private-0-8128,Jigsaw Rate Severity of Toxic Comments
4705,87358638,30.0,0.7522586263197997,0,7,/lucamassaron/linear-svc-ranking-private-0-80436,Jigsaw Rate Severity of Toxic Comments
4706,87451205,11.0,0.7860019592903015,0,0,/whitelily/late-sub,Jigsaw Rate Severity of Toxic Comments
4707,82706216,415.0,,3,14,/abebe9849/sentence-bert-jigsaw,Jigsaw Rate Severity of Toxic Comments
4708,79237819,287.0,,2,5,/jonathanchan/jigsaw-hf-models-naive-comparison,Jigsaw Rate Severity of Toxic Comments
4709,80458556,1302.0,,2,2,/jdoesv/baseline-data-prep,Jigsaw Rate Severity of Toxic Comments
4710,81781372,1957.0,,0,2,/tenffe/1-data-preprocess-data,Jigsaw Rate Severity of Toxic Comments
4711,83058410,2009.0,,1,16,/kumapo/reproducible-cv-strategy-by-union-find-jigsaw,Jigsaw Rate Severity of Toxic Comments
4712,84292745,966.0,0.6590834875367367,0,1,/rahulbhimani/jigsaw-13,Jigsaw Rate Severity of Toxic Comments
4713,97486677,1228.0,,0,5,/mdbodrulalam/measure-rate-severity-with-hate-speech,Jigsaw Rate Severity of Toxic Comments
4714,79164379,520.0,,0,13,/soumya9977/jrstc-baseline-model-lstm-cnn-regression,Jigsaw Rate Severity of Toxic Comments
4715,84953987,74.0,,0,4,/crischir/simple-bigru-ktrain-regression,Jigsaw Rate Severity of Toxic Comments
4716,86375793,751.0,,3,24,/ahmetarifturkmen/baseline-linear-regression,Jigsaw Rate Severity of Toxic Comments
4717,84319580,1189.0,0.7642320670512681,2,6,/coldfir3/clean-inference-with-hugingface-0-764,Jigsaw Rate Severity of Toxic Comments
4718,79191348,164.0,,10,29,/elcaiseri/jigsaw-keras-embedding-lstm,Jigsaw Rate Severity of Toxic Comments
4719,84334404,24.0,,15,52,/readoc/toxic-linear-model-pseudo-labelling-lb-0-864,Jigsaw Rate Severity of Toxic Comments
4720,87393726,1021.0,0.8602372918254054,0,7,/ducanger/private-0-79-simple-ridge-tf-idf,Jigsaw Rate Severity of Toxic Comments
4721,82121041,769.0,,0,0,/guanghan/lstm-train,Jigsaw Rate Severity of Toxic Comments
4722,85360329,1766.0,0.8045063676934799,0,6,/tisonludovic/ovr-jigsaw-sgd,Jigsaw Rate Severity of Toxic Comments
4723,86057288,68.0,,2,23,/shigeria/jigsaw-data-augmentation-using-tree,Jigsaw Rate Severity of Toxic Comments
4724,84387997,748.0,0.8269293566996844,0,0,/sunchine/0-816-jigsaw-inference11234layer2mlp,Jigsaw Rate Severity of Toxic Comments
4725,80978145,7.0,,5,43,/columbia2131/jigsaw-cv-strategy-by-union-find,Jigsaw Rate Severity of Toxic Comments
4726,87226759,196.0,0.8653532165015784,1,2,/skiller/classical-ensemble-model-0-8,Jigsaw Rate Severity of Toxic Comments
4727,82629126,138.0,,2,13,/hiroakifukuse/jigsaw-pretrain-roberta-base,Jigsaw Rate Severity of Toxic Comments
4728,84902933,9.0,,0,1,/andreippv/toxic-labels-ambiguity,Jigsaw Rate Severity of Toxic Comments
4729,80110747,632.0,,0,1,/poipii/pytorch-lightning-toxic-distilrobeta,Jigsaw Rate Severity of Toxic Comments
4730,79457612,3.0,0.5422880156743224,1,22,/steubk/jrsotc-bradley-terry-model-with-choix,Jigsaw Rate Severity of Toxic Comments
4731,118039564,1504.0,,0,3,/rishishounak/linregtox2,Jigsaw Rate Severity of Toxic Comments
4732,85315988,1280.0,0.7000108849461195,0,2,/apurvsj/lstm-emblayer-xgb,Jigsaw Rate Severity of Toxic Comments
4733,81276237,822.0,0.8411886361162513,4,9,/keivanipchihagh/jigsaw-rate-severity-of-toxic-comments,Jigsaw Rate Severity of Toxic Comments
4734,85595943,446.0,,2,2,/co21cen/jigsaw-starter1,Jigsaw Rate Severity of Toxic Comments
4735,80092804,1379.0,0.6671383476651791,8,26,/yeayates21/jigsaw-rate-severity-simple-lstm-w-augmentation,Jigsaw Rate Severity of Toxic Comments
4736,81268170,374.0,0.8542505714596713,0,1,/mm1393852116/jigsaw-ensemble-tfidf-bert,Jigsaw Rate Severity of Toxic Comments
4737,81268170,374.0,0.8542505714596713,0,1,/mm1393852116/jigsaw-ensemble-tfidf-bert,Jigsaw Rate Severity of Toxic Comments
4738,80775838,390.0,,1,3,/shravankumar147/1-basic-understanding-of-data-and-model-detoxify,Jigsaw Rate Severity of Toxic Comments
4739,88446129,88.0,,10,6,/wuharlem/simple-bert-w-hinge-loss,Jigsaw Rate Severity of Toxic Comments
4740,82180891,450.0,,0,3,/davidshyn/notebooked8d905c80,Jigsaw Rate Severity of Toxic Comments
4741,80486043,1426.0,0.731577228692718,0,3,/perevalov540/detoxify-baseline-with-no-internet-offline,Jigsaw Rate Severity of Toxic Comments
4742,79172702,366.0,,0,22,/kishalmandal/all-about-stemming-and-lemmatization-cleaning,Jigsaw Rate Severity of Toxic Comments
4743,85605094,419.0,,0,2,/jack0122/nchu-10,Jigsaw Rate Severity of Toxic Comments
4744,79947372,1065.0,0.7838249700663982,8,52,/samarthagarwal23/the-benchmark-0-81-tfidf-ridge,Jigsaw Rate Severity of Toxic Comments
4745,80022242,262.0,0.6585392402307608,3,11,/sabinaabdurakhmanova/jigsaw-comment-toxicity-lstm-starter,Jigsaw Rate Severity of Toxic Comments
4746,82940633,1152.0,0.820180690105584,0,0,/mdhdvchsd/tfidf-summed,Jigsaw Rate Severity of Toxic Comments
4747,84853876,803.0,,0,5,/sarthak221995/tfidf-ridge-regression-simple-easy-83,Jigsaw Rate Severity of Toxic Comments
4748,86642246,742.0,0.7610754326766083,0,0,/prernahrmth/jigsaw-lstm-sigmoid-post-weight-802-private-lb,Jigsaw Rate Severity of Toxic Comments
4749,81513511,343.0,0.6422118210514858,5,20,/frankmollard/nltk-sentiment-starter-within-33-seconds,Jigsaw Rate Severity of Toxic Comments
4750,86560928,1185.0,,6,11,/palash97/bert-pytorch-starter-code-training,Jigsaw Rate Severity of Toxic Comments
4751,85546535,738.0,0.8396647436595189,0,0,/dsmeena/toxiccomments-using-fastai,Jigsaw Rate Severity of Toxic Comments
4752,112660974,142.0,,0,0,/bachan/jigsaw-toxic-severity-rating-0-79874-private-lb,Jigsaw Rate Severity of Toxic Comments
4753,83812890,1776.0,0.5718950691194079,0,9,/arunkumar1809/beginners-lr-toxic-comments-classification-0-80,Jigsaw Rate Severity of Toxic Comments
4754,87304212,31.0,,2,21,/cpmpml/best-cv,Jigsaw Rate Severity of Toxic Comments
4755,85941048,1150.0,0.5266136932622184,0,0,/jery33/nltk-vader-baseline,Jigsaw Rate Severity of Toxic Comments
4756,87235798,102.0,0.7531294220093611,0,1,/marcogorelli/optimised-detoxify,Jigsaw Rate Severity of Toxic Comments
4757,80232291,1451.0,0.5538260585610101,8,9,/kibaelee/lstm-with-word2vec-khadija-bn,Jigsaw Rate Severity of Toxic Comments
4758,84111852,1316.0,0.7575922499183629,0,6,/mstamatis/jigsaw-comment-toxicity-lstm-using-custom-af,Jigsaw Rate Severity of Toxic Comments
4759,85796569,127.0,0.8152824643518014,6,43,/andre112/0-826-hate-speech-ridgeregression-ensemble,Jigsaw Rate Severity of Toxic Comments
4760,79155797,873.0,,58,312,/debarshichanda/pytorch-w-b-jigsaw-starter,Jigsaw Rate Severity of Toxic Comments
4761,79171742,1244.0,,0,9,/jpn888/jrstc-tried-augment-using-duplicates,Jigsaw Rate Severity of Toxic Comments
4762,84910810,734.0,0.7800152389245674,0,10,/sklasfeld/jigsaw-naive-bayes-explained,Jigsaw Rate Severity of Toxic Comments
4763,84771328,214.0,,16,46,/junjitakeshima/jigsaw-simple-lgbm-starter-with-tf-idf-eng,Jigsaw Rate Severity of Toxic Comments
4764,85440082,81.0,,0,6,/renokan/toxic-comments-test-valid-data-by-detoxify-model,Jigsaw Rate Severity of Toxic Comments
4765,79106865,73.0,0.7628170240557309,9,90,/abhishek/autonlp-for-toxic-ratings,Jigsaw Rate Severity of Toxic Comments
4766,86539286,1454.0,0.7949276151083052,0,0,/antoinemaby/test-notebook,Jigsaw Rate Severity of Toxic Comments
4767,79888644,994.0,0.8164798084249483,0,6,/btzkb7766/jigsaw-nlp-toxic-prediction,Jigsaw Rate Severity of Toxic Comments
4768,80319601,1260.0,0.7841515184499837,4,8,/vmuzhichenko/jigsaw-simple-toxic-transformer,Jigsaw Rate Severity of Toxic Comments
4769,79144413,723.0,,5,18,/shivansh002/very-toxic-eda,Jigsaw Rate Severity of Toxic Comments
4770,79997915,146.0,0.8080983999129204,1,44,/yasufuminakama/jigsaw4-luke-base-starter-sub,Jigsaw Rate Severity of Toxic Comments
4771,82313147,144.0,0.7700010884946119,0,0,/zxhuang1698/inference,Jigsaw Rate Severity of Toxic Comments
4772,82183166,732.0,0.8129966256667029,0,0,/woo990307/jigsaw-rate-severity-of-toxic-comments,Jigsaw Rate Severity of Toxic Comments
4773,87232676,1270.0,0.7925329269620115,0,0,/ptrikp/fork-of-jigsaw-tfidf-pipeline-c5454c,Jigsaw Rate Severity of Toxic Comments
4774,86649309,2026.0,,0,0,/estebanmarcelloni/jigsaw-toxic-rating-using-setence2vector,Jigsaw Rate Severity of Toxic Comments
4775,86649309,2026.0,,0,0,/estebanmarcelloni/jigsaw-toxic-rating-using-setence2vector,Jigsaw Rate Severity of Toxic Comments
4776,81371715,856.0,,2,21,/jirkaborovec/toxic-comments-with-lightning-flash,Jigsaw Rate Severity of Toxic Comments
4777,84543510,1966.0,0.8060302601502123,0,0,/tunminhhunh/0-816-jigsaw-inference,Jigsaw Rate Severity of Toxic Comments
4778,85624375,87.0,,0,0,/taoufikelkhaouja/toxic-comments-bert,Jigsaw Rate Severity of Toxic Comments
4779,85495524,2006.0,0.7230869707194949,0,0,/kiernanmcguigan/jigsaw-xgboostregressor,Jigsaw Rate Severity of Toxic Comments
4780,81861243,436.0,0.802002830085991,0,0,/hbendeguz/simple-solution-tfidf-multiclassridge-cascade,Jigsaw Rate Severity of Toxic Comments
4781,81866436,1138.0,0.614346358985523,0,0,/sriramanathan/0-787-regression-baseline-tf-idf,Jigsaw Rate Severity of Toxic Comments
4782,80205587,1905.0,,10,27,/get2jawa/nlp-basic-eda-cleaning-lstm-lb-0-79,Jigsaw Rate Severity of Toxic Comments
4783,80370304,1018.0,,0,2,/usaiprashanth/hf-deepspeed-jigsaw-starter-training,Jigsaw Rate Severity of Toxic Comments
4784,81935328,430.0,,0,3,/raghavendrakotala/inference-on-roberta-toxicity-model-using-dataset,Jigsaw Rate Severity of Toxic Comments
4785,82287416,1186.0,,0,30,/konradb/prepare-paired-datasets,Jigsaw Rate Severity of Toxic Comments
4786,87038705,1143.0,0.7714161314901491,0,1,/alexiscol/keras-embedding-lstm,Jigsaw Rate Severity of Toxic Comments
4787,82709954,1612.0,,4,16,/adldotori/huggingface-distilbertclassification-starter,Jigsaw Rate Severity of Toxic Comments
4788,86439558,45.0,,0,4,/mujrush/reliable-validation-data-by-sentence-transformers,Jigsaw Rate Severity of Toxic Comments
4789,84572553,1258.0,,0,0,/yezyouo/naive-bayes-lightgbm-ridge,Jigsaw Rate Severity of Toxic Comments
4790,80494892,79.0,,4,69,/its7171/jigsaw-cv-strategy,Jigsaw Rate Severity of Toxic Comments
4791,81579418,1632.0,,0,19,/ahsanhabib98/jigsaw-rate-severity-of-toxic-comments-by-ridge,Jigsaw Rate Severity of Toxic Comments
4792,85210708,1652.0,,0,0,/elodiecallea/classifierchains-rf-ranking,Jigsaw Rate Severity of Toxic Comments
4793,80467701,1310.0,0.7690214433438555,0,1,/satyanweshi/0-773-tfidf-naive-bayes-ruddit-jigsaw-data,Jigsaw Rate Severity of Toxic Comments
4794,85316961,1599.0,0.7733754217916621,0,0,/eleonoraparrag/jigsaw-severity,Jigsaw Rate Severity of Toxic Comments
4795,79673216,2091.0,0.725046261021008,0,8,/santhoshkumarv/bidirectional-lstm-pytorch-jigsaw-inference,Jigsaw Rate Severity of Toxic Comments
4796,80610709,1578.0,,1,2,/minsik/211123-toxic-01-copy-code,Jigsaw Rate Severity of Toxic Comments
4797,86504296,1249.0,0.7260259061717644,2,5,/eligijus/toxicity-grid-search-xgboost-model,Jigsaw Rate Severity of Toxic Comments
4798,88090540,118.0,,0,0,/wuyhbb/deberta-jigsaw-inference,Jigsaw Rate Severity of Toxic Comments
4799,166776147,1435.0,,40,59,/fangya/nlp-jigsaw-mindful-words-eda-tf-idf-svm,Jigsaw Rate Severity of Toxic Comments
4800,79227737,132.0,,3,12,/alibaba19/jigsaw-training-ulmfit-w-fastai,Jigsaw Rate Severity of Toxic Comments
4801,85494592,134.0,0.7645586154348536,0,4,/danielcwq/jigsaw-ulm-fastai-predictions-submitter,Jigsaw Rate Severity of Toxic Comments
4802,79140177,526.0,0.7628170240557309,0,5,/junior10/autonlp-for-toxic-ratings,Jigsaw Rate Severity of Toxic Comments
4803,79140177,526.0,0.7628170240557309,0,5,/junior10/autonlp-for-toxic-ratings,Jigsaw Rate Severity of Toxic Comments
4804,79241581,2148.0,0.4986393817350604,0,15,/mohamedbakrey/eda-model-lstm-cnn-regression-for-jigsaw,Jigsaw Rate Severity of Toxic Comments
4805,79241581,2148.0,0.4986393817350604,0,15,/mohamedbakrey/eda-model-lstm-cnn-regression-for-jigsaw,Jigsaw Rate Severity of Toxic Comments
4806,87131976,51.0,,0,0,/maruyama/detoxify-unbiased-train-0-80476-private,Jigsaw Rate Severity of Toxic Comments
4807,79188218,1899.0,0.7529117230869707,11,56,/robikscube/jiggsaw-toxic-comments-eda-twitch-stream,Jigsaw Rate Severity of Toxic Comments
4808,83337058,2125.0,,0,6,/megaslav/pytorch-template-for-toxic-comments,Jigsaw Rate Severity of Toxic Comments
4809,80622335,2129.0,,0,1,/seraphwedd18/jigsaw-toxic-severity-word-usage-scoring,Jigsaw Rate Severity of Toxic Comments
4810,87209550,1924.0,0.747251551104822,0,2,/cyrillechampion/notebooktoxic,Jigsaw Rate Severity of Toxic Comments
4811,81211000,1747.0,0.7492108414063351,0,0,/zsofislosar/my-first-submission,Jigsaw Rate Severity of Toxic Comments
4812,85099994,1437.0,,0,1,/eileends/jigsaw-es,Jigsaw Rate Severity of Toxic Comments
4813,88555946,2128.0,,0,0,/moenuddin/trying-pairwise,Jigsaw Rate Severity of Toxic Comments
4814,81304468,2104.0,,7,20,/pablorosa01/naive-bayes-modeling-base-line,Jigsaw Rate Severity of Toxic Comments
4815,82076338,1401.0,0.7096984869924894,0,0,/milenasokol/lstm-and-ranking,Jigsaw Rate Severity of Toxic Comments
4816,80286463,2163.0,0.6250136061826495,12,35,/khkuggle/simple-lstm-with-word2vec,Jigsaw Rate Severity of Toxic Comments
4817,87596399,2081.0,,0,3,/arronlacey/random-forest-w-glove-kmeans-compression,Jigsaw Rate Severity of Toxic Comments
4818,87072538,2177.0,0.6727985196473277,0,2,/tavoglc/severity-of-toxic-comments,Jigsaw Rate Severity of Toxic Comments
4819,85062016,2141.0,0.529661478175683,0,5,/suryadeepti/jigsaw,Jigsaw Rate Severity of Toxic Comments
4820,84696068,2221.0,0.190921954936323,0,6,/michaelfromoldwick/toxic-comments-model,Jigsaw Rate Severity of Toxic Comments
4821,84696068,2221.0,0.190921954936323,0,6,/michaelfromoldwick/toxic-comments-model,Jigsaw Rate Severity of Toxic Comments
4822,80419220,2182.0,,0,2,/jianluezhang/contrastive-tension-rank-toxicity,Jigsaw Rate Severity of Toxic Comments
4823,79529144,2134.0,0.6191357352781104,0,3,/ananyapam7/ensemble-technique,Jigsaw Rate Severity of Toxic Comments
4824,80776977,2103.0,,1,2,/olgaparshina/toxic-comment-model,Jigsaw Rate Severity of Toxic Comments
4825,82180915,2231.0,,1,6,/zenstat/jigsaw-baseline,Jigsaw Rate Severity of Toxic Comments
4826,81113789,2219.0,,7,5,/kush1729/xgboostregressor-with-gridsearch-cv,Jigsaw Rate Severity of Toxic Comments
4827,87094560,2259.0,,0,1,/quamarequbal/jigsaw-rate-severity-of-toxic-comments,Jigsaw Rate Severity of Toxic Comments
4828,82481142,2197.0,,0,0,/dooneen/notebookd7d2c7ae59,Jigsaw Rate Severity of Toxic Comments
4829,79527797,2239.0,,23,71,/mpwolke/toxic-kagglers-positivity,Jigsaw Rate Severity of Toxic Comments
4830,79458021,2241.0,,4,12,/urstrulysai/here-s-the-train-csv-you-are-looking-for,Jigsaw Rate Severity of Toxic Comments
4831,81828748,2244.0,0.4986393817350604,17,26,/ahmedaffan789/bert-toxic-comments-pytorch,Jigsaw Rate Severity of Toxic Comments
4832,79111024,2273.0,0.2160661804724066,2,11,/hamditarek/jrst-nb-svm-nb-svm-strong-linear-baseline,Jigsaw Rate Severity of Toxic Comments
4833,80965877,2276.0,0.3046696418852727,1,3,/yashsingh012/notebook4bc71e382f,Jigsaw Rate Severity of Toxic Comments
4834,80375814,2286.0,0.0,1,11,/samyukthamobile/beginners-submission-comment-toxic-or-not,Jigsaw Rate Severity of Toxic Comments
4835,85056763,2289.0,0.0103406988135408,0,2,/ahnyelim/practice,Jigsaw Rate Severity of Toxic Comments
4837,85358820,2.0,,1,26,/skril31/generating-a-2428-solution-in-100-lines-of-code,Santa 2021 - The Merry Movie Montage
4838,85126205,5.0,,1,15,/ks2019/santa-5th-place-2428,Santa 2021 - The Merry Movie Montage
4839,83422670,16.0,,6,29,/seshurajup/visualize-with-without-wildcard-sol-300-clones,Santa 2021 - The Merry Movie Montage
4840,81777524,21.0,2483.0,0,9,/xuxu1234/santa-baseline,Santa 2021 - The Merry Movie Montage
4841,80425093,42.0,,5,16,/solverworld/distribution-of-duplicates-and-mandatories,Santa 2021 - The Merry Movie Montage
4842,80176380,43.0,2507.0,49,245,/cdeotte/santa-2021-tsp-baseline-2500,Santa 2021 - The Merry Movie Montage
4843,84920674,44.0,2430.0,1,3,/mviola/santa-2021-randomized-wildcard-postprocessing,Santa 2021 - The Merry Movie Montage
4844,85146163,50.0,,0,5,/miguelgonzalez2/santa-2021-wildcard-insertion-lkh,Santa 2021 - The Merry Movie Montage
4845,85109432,60.0,2434.0,0,3,/taanieluleksin/wilcard-optimization-with-acvrp-up-to-2430,Santa 2021 - The Merry Movie Montage
4846,81583576,67.0,2488.0,7,38,/kmldas/baseline-rebalance-wildcard-postprocessing-2490,Santa 2021 - The Merry Movie Montage
4847,80021131,68.0,2533.0,7,31,/yosshi999/just-split-the-known-minimum-solution-for-n-7,Santa 2021 - The Merry Movie Montage
4848,83788226,83.0,,0,2,/blankaf/my-santa-vol-3,Santa 2021 - The Merry Movie Montage
4849,82595822,130.0,2452.0,2,40,/ulrich07/thanks-to-best-public-kernel,Santa 2021 - The Merry Movie Montage
4850,82567032,161.0,2446.0,0,6,/saijashwanthreddy/minmax-ctsp,Santa 2021 - The Merry Movie Montage
4851,79991948,301.0,2651.0,6,30,/kostyaatarik/santa-2021,Santa 2021 - The Merry Movie Montage
4852,84128542,309.0,2856.0,1,18,/atamazian/santa-2021-tsp-baseline-with-concorde,Santa 2021 - The Merry Movie Montage
4853,81067548,310.0,,1,5,/chinta/simplenearestneighbour,Santa 2021 - The Merry Movie Montage
4854,80540541,431.0,,9,38,/joatom/santa-2021-build-superpermutation-5913,Santa 2021 - The Merry Movie Montage
4855,82530772,441.0,,0,21,,Santa 2021 - The Merry Movie Montage
4856,80045661,536.0,2651.0,0,1,/aishikai/santa-2021,Santa 2021 - The Merry Movie Montage
4857,80103020,583.0,2521.0,17,124,/ilialar/santa-2021-baseline-and-optimization-ideas,Santa 2021 - The Merry Movie Montage
4858,80466284,587.0,,1,13,/anjum48/going-from-superpermutation-permutation-format,Santa 2021 - The Merry Movie Montage
4859,80972899,602.0,2528.0,4,24,/jazivxt/winter-fun,Santa 2021 - The Merry Movie Montage
4860,81038335,620.0,2533.0,1,13,/ted0071/santa-2021-starter,Santa 2021 - The Merry Movie Montage
4861,83742946,650.0,,34,75,/kishalmandal/santa-particle-swarm-optimisation-2548,Santa 2021 - The Merry Movie Montage
4862,81713435,686.0,,1,4,/neelakashchatterjee/santa-coming-from-6985-to-2647-naive-approach,Santa 2021 - The Merry Movie Montage
4863,80754189,697.0,,1,6,/pehahn/basic-r,Santa 2021 - The Merry Movie Montage
4864,80196664,711.0,2651.0,0,3,/saraswatitiwari/santa-2021-the-merry-movie-montage,Santa 2021 - The Merry Movie Montage
4865,81692957,772.0,,0,18,/adrienbouvais/santa-schedule-verification,Santa 2021 - The Merry Movie Montage
4866,79986805,804.0,,0,13,/rdizzl3/christmas-movie-marathon,Santa 2021 - The Merry Movie Montage
4989,83369824,164.0,0.95696,5,21,/pourchot/tps-12-simple-nn-with-skip-connection,Tabular Playground Series - Dec 2021
4990,82612599,23.0,,30,70,/ambrosm/tpsdec21-01-keras-quickstart,Tabular Playground Series - Dec 2021
4991,81694571,129.0,,3,6,/kaaveland/tps202112-parquet,Tabular Playground Series - Dec 2021
4992,85590790,132.0,,52,139,/odins0n/tps-dec-eda-modelling,Tabular Playground Series - Dec 2021
4993,81824949,160.0,,4,2,/teckmengwong/simpleautonn-softmax,Tabular Playground Series - Dec 2021
4994,139584024,244.0,,30,72,/bennyfung/keras-mlp-score-95-6,Tabular Playground Series - Dec 2021
4995,84040952,51.0,0.9570133333333334,0,4,/skanderhaddad/tps-dec-pseudolabels-ensemble,Tabular Playground Series - Dec 2021
4996,83320643,52.0,0.95659,25,60,/remekkinas/tps-12-nn-tpu-pseudolabeling-0-95690,Tabular Playground Series - Dec 2021
4997,81451688,55.0,0.9500266666666668,0,5,/omarvivas/torchmodelgpu-tpsdec21,Tabular Playground Series - Dec 2021
4998,83041901,56.0,0.9557766666666668,11,29,/kavehshahhosseini/tps-dec-2021-unsupervised-learning-features,Tabular Playground Series - Dec 2021
4999,83210074,57.0,0.95711,0,2,/skloveyyp/tps-dec-2021-simple-ensemble-public-notebooks,Tabular Playground Series - Dec 2021
5000,83210074,57.0,0.95711,0,2,/skloveyyp/tps-dec-2021-simple-ensemble-public-notebooks,Tabular Playground Series - Dec 2021
5001,83210074,57.0,0.95711,0,2,/skloveyyp/tps-dec-2021-simple-ensemble-public-notebooks,Tabular Playground Series - Dec 2021
5002,83210074,57.0,0.95711,0,2,/skloveyyp/tps-dec-2021-simple-ensemble-public-notebooks,Tabular Playground Series - Dec 2021
5003,83210074,57.0,0.95711,0,2,/skloveyyp/tps-dec-2021-simple-ensemble-public-notebooks,Tabular Playground Series - Dec 2021
5004,81439427,60.0,0.9542466666666668,20,28,/lonnieqin/tps-12-21-catboost,Tabular Playground Series - Dec 2021
5005,83071417,65.0,,4,27,/jillanisofttech/tps-dec-21-reasonable-xgboost-model,Tabular Playground Series - Dec 2021
5006,81647959,67.0,0.9546966666666666,17,32,,Tabular Playground Series - Dec 2021
5007,81681407,72.0,0.9467433333333334,4,10,,Tabular Playground Series - Dec 2021
5008,83150490,79.0,,0,4,/aditya01233/december-tps-stacking-ensembling-xgb-lgbm-cb,Tabular Playground Series - Dec 2021
5009,81236566,80.0,,0,4,/rhythmcam/h2o-automl-tps-dec-2021,Tabular Playground Series - Dec 2021
5010,82731720,81.0,0.95685,0,0,/gaolang/tps-dec-2021-simple-ensemble-public-notebooks,Tabular Playground Series - Dec 2021
5011,83641019,86.0,0.9560833333333332,36,39,/mhslearner/tps-dec-eda-resnet,Tabular Playground Series - Dec 2021
5012,84057147,94.0,,0,7,/adamwurdits/tps-12-2021-kneighbors,Tabular Playground Series - Dec 2021
5013,84210565,95.0,,56,79,/sisharaneranjana/semi-supervised-pre-training-with-tabnet,Tabular Playground Series - Dec 2021
5014,81446144,96.0,,1,3,/pavan9065/explore-tps-dec-2021,Tabular Playground Series - Dec 2021
5015,89375960,104.0,,14,14,/cv13j0/tps-dec-2021-beginner-code,Tabular Playground Series - Dec 2021
5016,82656020,25.0,,19,26,/smsajideen/tps-dec-pytorch-nn,Tabular Playground Series - Dec 2021
5017,83850928,28.0,0.9571033333333332,1,0,/mkt0309/tps-dec-2021-simple-ensemble-public-notebooks,Tabular Playground Series - Dec 2021
5018,84044407,137.0,,0,3,/sytuannguyen/tps-dec-automated-ensemble,Tabular Playground Series - Dec 2021
5019,81241195,136.0,0.93722,8,12,/lucamassaron/baseline-lightgbm-with-covtype-augmentation,Tabular Playground Series - Dec 2021
5020,82110016,130.0,,12,27,/devsubhash/tps-december-eda,Tabular Playground Series - Dec 2021
5021,81640697,41.0,,22,31,/bhuppi2898/tps-december-eda-easy,Tabular Playground Series - Dec 2021
5022,83441384,24.0,,3,10,/datastrophy/tps-end-of-the-year-14-baseline-models,Tabular Playground Series - Dec 2021
5023,82095472,6.0,0.95341,1,14,/slythe/tabular-playground-dec-2021,Tabular Playground Series - Dec 2021
5024,82095472,6.0,0.95341,1,14,/slythe/tabular-playground-dec-2021,Tabular Playground Series - Dec 2021
5025,84061238,5.0,,3,11,/casati8/kaggle-tps-dec2021-fastai,Tabular Playground Series - Dec 2021
5026,81303175,150.0,,3,8,/adaubas/tps-dec-2021-wilderness-area3-is-strange,Tabular Playground Series - Dec 2021
5027,82914134,4.0,0.95653,4,5,/te5serer/tps-december-tensorflow-nn,Tabular Playground Series - Dec 2021
5028,82614963,189.0,0.9568233333333334,34,39,/samuelcortinhas/tps-dec-eda-feat-eng-pseudolab,Tabular Playground Series - Dec 2021
5029,82315468,162.0,0.95674,7,15,/mlanhenke/tps-12-simple-nn-fe-pseudolabels-keras,Tabular Playground Series - Dec 2021
5030,82175987,220.0,0.95679,0,17,/balamurugan1603/tps-dec-21-nn-feature-engg-tf,Tabular Playground Series - Dec 2021
5031,82289465,193.0,0.9552333333333334,28,19,/gulshanmishra/tps-dec-21-xgboost-optuna,Tabular Playground Series - Dec 2021
5032,84937202,263.0,0.95464,0,9,/eugenebee/tps-dec-21-phik-features-eng-pytorch-tabnet,Tabular Playground Series - Dec 2021
5033,82136187,252.0,0.9532666666666668,2,6,/sfktrkl/tps-dec-2021-hyperparameters-tuning,Tabular Playground Series - Dec 2021
5034,83111416,222.0,0.95608,0,0,/mirenaborisova/tabular-playground-dec-2021-01,Tabular Playground Series - Dec 2021
5035,83598331,268.0,,4,17,/tunguz/tps-dec-2021-simple-linear-baseline,Tabular Playground Series - Dec 2021
5036,82380575,241.0,0.9566533333333334,0,0,/valou7/tps-dec-2021-unbalanced-data,Tabular Playground Series - Dec 2021
5037,82218576,219.0,,7,14,/siukeitin/tps122021-exploiting-sparsity-for-xgboost,Tabular Playground Series - Dec 2021
5038,89473592,239.0,,14,35,/gazu468/tps-dec-eda-modeling,Tabular Playground Series - Dec 2021
5039,81673855,250.0,,3,6,/vijayshankar756/tabular-playground,Tabular Playground Series - Dec 2021
5040,83725742,221.0,0.9550733333333332,0,1,/abhijitd16/tps-dec21-xgb-and-catb,Tabular Playground Series - Dec 2021
5041,81290622,292.0,0.9418,9,11,/stevenrferrer/tps-dec-2021-baseline-xgbm-lgbm-cb-with-gpu,Tabular Playground Series - Dec 2021
5042,81290622,292.0,0.95031,9,11,/stevenrferrer/tps-dec-2021-baseline-xgbm-lgbm-cb-with-gpu,Tabular Playground Series - Dec 2021
5043,81290622,292.0,0.9496,9,11,/stevenrferrer/tps-dec-2021-baseline-xgbm-lgbm-cb-with-gpu,Tabular Playground Series - Dec 2021
5044,86426313,206.0,0.9566966666666666,0,2,/gulerkaya/tps-dec-2021-neural-nets,Tabular Playground Series - Dec 2021
5045,81346372,264.0,,0,10,/durgancegaur/eda-for-dec-playground,Tabular Playground Series - Dec 2021
5046,83527946,283.0,,8,6,/leeyj0511/tps-dec-simpl-eda-basic-modeling-for-beginner,Tabular Playground Series - Dec 2021
5047,83733017,278.0,0.95435,1,12,/optimo/tabnet-original-paper-s-parameters,Tabular Playground Series - Dec 2021
5048,82278821,311.0,0.8964266666666667,20,29,/vardhansiramdasu/tabular-playground-series-dec-2021,Tabular Playground Series - Dec 2021
5049,82278821,311.0,0.8964266666666667,20,29,/vardhansiramdasu/tabular-playground-series-dec-2021,Tabular Playground Series - Dec 2021
5050,82030939,303.0,0.95618,1,6,/abdelrahmanrabah/december-notebook-nn,Tabular Playground Series - Dec 2021
5051,83806616,238.0,0.95104,0,3,/rizkykiky/contoh-algoritma-random-forest,Tabular Playground Series - Dec 2021
5052,81782046,284.0,,7,9,/yannbarthelemy/tps-december-first-nn,Tabular Playground Series - Dec 2021
5053,81722022,291.0,,1,1,/christoforum/tps-dec-2021-neural-network-with-gridsearchcv,Tabular Playground Series - Dec 2021
5054,84272406,327.0,,0,1,/makonori/tps-dec2021-by-keras-ensemble,Tabular Playground Series - Dec 2021
5055,84064328,322.0,,8,13,/lanukahjo/eda-feature-engineering-catboost,Tabular Playground Series - Dec 2021
5056,82745839,348.0,,6,11,/satoshiss/tps-december-xgbclassifier,Tabular Playground Series - Dec 2021
5057,83031526,306.0,0.9558433333333334,0,0,/markct/tps-202112,Tabular Playground Series - Dec 2021
5058,83918314,338.0,,0,0,/pythonash/a-way-you-can-handle-dataset-simply,Tabular Playground Series - Dec 2021
5059,82294345,317.0,0.9541633333333334,2,12,/berkayalan/logistic-regression-neural-networks-xgboost,Tabular Playground Series - Dec 2021
5060,82185519,326.0,,17,24,/gvyshnya/express-eda-with-autoviz-dec21-tcp,Tabular Playground Series - Dec 2021
5061,84073411,332.0,0.9550533333333332,0,0,/bernhardklinger/tps-v4,Tabular Playground Series - Dec 2021
5062,84036075,343.0,,0,3,/nasil2/xgb-and-more,Tabular Playground Series - Dec 2021
5063,82764167,336.0,,2,3,/jmargni/tps-dec2021-lightgbm-voting-kfolds,Tabular Playground Series - Dec 2021
5064,81930846,351.0,0.9554566666666666,2,9,/maximkazantsev/tps-12-21-eda-catboost,Tabular Playground Series - Dec 2021
5065,83086856,367.0,0.9512833333333334,0,27,/m1y7k8/tps-dec-21-eda-and-randomforest,Tabular Playground Series - Dec 2021
5066,82835884,361.0,,28,44,/alexeykolobyanin/tps-dec-svc-with-sklearnex-20x-speedup,Tabular Playground Series - Dec 2021
5067,81484763,405.0,,1,6,/sergeilepitko/tps-dec-2021-eda,Tabular Playground Series - Dec 2021
5068,83083354,383.0,0.9552833333333334,0,4,/yoonhwayam/tps-submission-data-yh,Tabular Playground Series - Dec 2021
5069,81980562,400.0,,0,1,/indiegolab/tps-dec2021-simple-eda-practice,Tabular Playground Series - Dec 2021
5070,83141278,409.0,,1,8,/yuyougnchan/tps-dec-cat-boost-solution-0-95500,Tabular Playground Series - Dec 2021
5071,82675555,440.0,,5,13,/akmeghdad/tps-1221-all-in-one-eda,Tabular Playground Series - Dec 2021
5072,83002679,380.0,,4,9,/guptashourya/tps-dec-beginners-notebook,Tabular Playground Series - Dec 2021
5073,82648231,426.0,0.95477,0,1,/burkaykirnik/notebookb94dc116ae,Tabular Playground Series - Dec 2021
5074,82733564,433.0,0.9548633333333332,4,5,/ochaaaaaaan/tabular-playground-series-dec-2021-lightgbm,Tabular Playground Series - Dec 2021
5075,83892225,454.0,0.9548633333333332,25,27,/imnaho/using-xgboost-and-catboost,Tabular Playground Series - Dec 2021
5076,82376865,430.0,0.9547033333333332,32,57,/hamzaghanmi/tps-dec-step-by-step,Tabular Playground Series - Dec 2021
5077,81763795,407.0,0.9547766666666668,4,8,/baekseungyun/tps-dec-catboost-optuna-cv-lb-0-9547,Tabular Playground Series - Dec 2021
5078,82726799,425.0,,3,4,/mohammadhossein77/tps-dec-catboost-gs,Tabular Playground Series - Dec 2021
5079,81365637,477.0,0.9398566666666668,2,3,/zhangcheche/tps-12-autogluon,Tabular Playground Series - Dec 2021
5080,81448849,490.0,,1,5,/peressim/tps-dec-2021-eda,Tabular Playground Series - Dec 2021
5081,82126494,451.0,0.9435933333333332,1,9,/docxian/tabular-playground-12-let-s-go,Tabular Playground Series - Dec 2021
5082,154136354,1038.0,,22,43,/maxdiazbattan/tps-2021-pytorch-lightning-dataparallel-2t4,Tabular Playground Series - Dec 2021
5083,83952848,475.0,0.9505833333333332,0,2,/pasuvulasaikiran/dec-tabular-catboost,Tabular Playground Series - Dec 2021
5084,82933965,469.0,0.9544666666666668,0,0,/massimod/tps-202112-catboost-base,Tabular Playground Series - Dec 2021
5085,84203002,438.0,0.9540933333333332,13,16,/suddharshan/ensemble-catboost-xgboost-randomforest,Tabular Playground Series - Dec 2021
5086,82100310,487.0,,2,3,/danieleongari/tsp-dec21-sequential-dense-nn-w-tpu,Tabular Playground Series - Dec 2021
5087,81237286,442.0,0.95241,5,14,/yazanmajzob/xgbclassifier-gpu-1-min,Tabular Playground Series - Dec 2021
5088,82875826,547.0,0.9524033333333334,0,0,/raulandresolivares/tensorflow-v2,Tabular Playground Series - Dec 2021
5089,82016153,489.0,,0,1,/hongyeob/tps-dec-2021,Tabular Playground Series - Dec 2021
5090,81845748,494.0,0.9542866666666666,10,15,/damagejun/tps-dec-2021-eda,Tabular Playground Series - Dec 2021
5091,83066645,523.0,,1,7,/maunilshah/tabular-playground-series-part-1,Tabular Playground Series - Dec 2021
5092,82254284,517.0,0.9539933333333334,63,133,/lordozvlad/tps-dec-fast-feature-importance-with-sklearnex,Tabular Playground Series - Dec 2021
5093,82319126,506.0,,9,20,/vishnukarthiklu/tps-12-basic-data-visualization-and-eda,Tabular Playground Series - Dec 2021
5094,83769616,513.0,0.9448866666666668,1,3,/gustavfredrikson/tps-dec-21-fast-easy-95-4-using-catboost,Tabular Playground Series - Dec 2021
5095,83853934,524.0,0.9539666666666666,4,10,/bibhabasumohapatra/multiclass-using-predict-proba-ensemble-part-2,Tabular Playground Series - Dec 2021
5096,82231450,563.0,0.9539633333333334,5,13,/karthikgopalkrishnan/tps-dec-2021-simple-xgboost,Tabular Playground Series - Dec 2021
5097,83820689,583.0,,0,3,/waizaidoc/tabular-playground,Tabular Playground Series - Dec 2021
5098,81358348,533.0,0.95392,0,1,/juliorsleite/tpc-12-21,Tabular Playground Series - Dec 2021
5099,83970651,579.0,,8,12,/lluis94/eda-multiple-models-exploration,Tabular Playground Series - Dec 2021
5100,81669330,558.0,,5,11,/merlinschaefer/eda-and-non-nn-models,Tabular Playground Series - Dec 2021
5101,82797241,587.0,0.9537766666666668,9,6,/sanikad/dec-tps-simply-simple-xgboost-model-explained,Tabular Playground Series - Dec 2021
5102,81585893,546.0,,2,5,/hakanerdogan/tps-dec-2021-simple-code-with-catboost,Tabular Playground Series - Dec 2021
5103,83169277,567.0,0.9532433333333332,0,0,/shaunalexander/tps-eda-tab-net-w-optuna,Tabular Playground Series - Dec 2021
5104,81324050,588.0,,2,5,/stpeteishii/tps1221-data-histplot,Tabular Playground Series - Dec 2021
5105,83756878,545.0,,4,10,/vasenkovartem/december-kaggle,Tabular Playground Series - Dec 2021
5106,81567254,575.0,0.9524766666666666,12,56,/anandhuh/tps-dec-21-simple-xgbclassifier-score-0-95247,Tabular Playground Series - Dec 2021
5107,84080192,604.0,0.95172,0,1,/haozhang607/tabular-playground-series-dec-2021,Tabular Playground Series - Dec 2021
5108,82516739,589.0,,2,1,/kreyttsfeldt/simple-keras-for-dec-2021-tabular-competition,Tabular Playground Series - Dec 2021
5109,81415734,585.0,,6,11,/naveen9192/catb-dec-series,Tabular Playground Series - Dec 2021
5110,81240978,625.0,0.92571,1,5,/kagglerrr1/tps-dec-h20-automl,Tabular Playground Series - Dec 2021
5111,84021351,596.0,,0,3,/ksamant/tps-december-first-notebook-on-kaggle-95-307,Tabular Playground Series - Dec 2021
5112,81266440,642.0,0.95285,2,9,/revathiprakash/tps-dec-ensemble-gpu,Tabular Playground Series - Dec 2021
5113,83946098,654.0,0.9511933333333332,2,7,/seungtaekim/tps-lgbm-baseline,Tabular Playground Series - Dec 2021
5114,82287976,656.0,,14,21,/omkarborikar/handling-imbalanced-data-and-xgboost-optuna-tuning,Tabular Playground Series - Dec 2021
5115,84152610,638.0,,3,3,/smritirani/tps-dec-21-eda-and-bagging-tree-classifier-95,Tabular Playground Series - Dec 2021
5116,81396154,667.0,,0,2,/tariqchhussain/xgb-optuna-oversampled-tps-dec-21-wip,Tabular Playground Series - Dec 2021
5117,96426478,681.0,,18,22,/zwartfreak/easiest-tps-prediction-full-explanation,Tabular Playground Series - Dec 2021
5118,82428285,684.0,,0,2,/ashura837/tps-dec21-teterin,Tabular Playground Series - Dec 2021
5119,82241271,702.0,0.9523333333333334,5,16,/shithavengara/tps-dec-21-xgbclassifier,Tabular Playground Series - Dec 2021
5120,81293214,696.0,,11,28,/gaganmaahi224/tps-dec-21-clean-eda-and-prediction,Tabular Playground Series - Dec 2021
5121,82762447,683.0,0.9522066666666666,21,22,/sumeetbohra/eda-feature-engineering-xgboost,Tabular Playground Series - Dec 2021
5122,83960098,695.0,0.9515566666666668,0,2,/lavrovlavrov/tps-dec-2021,Tabular Playground Series - Dec 2021
5123,83960098,695.0,0.9515566666666668,0,2,/lavrovlavrov/tps-dec-2021,Tabular Playground Series - Dec 2021
5124,81605655,685.0,,2,4,/possatti/tps-12-eda,Tabular Playground Series - Dec 2021
5125,81429966,712.0,,0,0,/jlove100/dec-tabular-playground-eda,Tabular Playground Series - Dec 2021
5126,81519042,717.0,,5,8,/aniketsharma00411/tpsdec21-exploratory-data-analysis,Tabular Playground Series - Dec 2021
5127,84058795,706.0,,1,5,/lehaaa1/dec-2021-tps,Tabular Playground Series - Dec 2021
5128,87339307,707.0,,0,2,/erofeevgleb/dec-2021,Tabular Playground Series - Dec 2021
5129,81907721,755.0,0.9468166666666666,0,3,/danielkondo/simple-model-for-dec2021-playground,Tabular Playground Series - Dec 2021
5130,81555627,729.0,0.93481,5,12,/vladlee/tabular-dec-21-lgbm-baseline,Tabular Playground Series - Dec 2021
5131,81555627,729.0,0.93481,5,12,/vladlee/tabular-dec-21-lgbm-baseline,Tabular Playground Series - Dec 2021
5132,82562894,754.0,,3,6,/sogamja/2021-dec-tps-eda,Tabular Playground Series - Dec 2021
5133,83116729,757.0,,0,9,/flezzer/tabular-playground-series-dec-2021,Tabular Playground Series - Dec 2021
5134,81909599,763.0,,16,33,/junhyeok99/multi-head-attention,Tabular Playground Series - Dec 2021
5135,81417573,765.0,0.0,1,19,/thasnihakeem/tps-dec-2021-using-linearregression,Tabular Playground Series - Dec 2021
5136,82864681,797.0,0.9476933333333334,29,27,/ranjeetshrivastav/tps-dec-21-xgb,Tabular Playground Series - Dec 2021
5137,81870227,803.0,0.9492566666666666,0,1,/heejinim/tps-dec2021-1,Tabular Playground Series - Dec 2021
5138,82886376,807.0,,3,5,/threecifanggen/practice-h20-automl,Tabular Playground Series - Dec 2021
5139,82408989,814.0,0.94869,3,3,/liberatoryohan/tabular-playground-dec-21,Tabular Playground Series - Dec 2021
5140,81984034,866.0,0.9435966666666666,0,1,/munyuju/tps-202112,Tabular Playground Series - Dec 2021
5141,84364345,882.0,0.94058,0,5,/kjw3226/t-p-s-do-it-eda-modeling,Tabular Playground Series - Dec 2021
5142,82479168,893.0,,0,0,/brthym/tps-dec-sgd-lsvc-xgb-catb-lgbm,Tabular Playground Series - Dec 2021
5143,82496555,905.0,0.5348033333333333,6,8,/megaslav/sklearn-with-transformers-and-pipelines,Tabular Playground Series - Dec 2021
5144,81851234,903.0,,1,5,/sinkevichgerman/december-2021,Tabular Playground Series - Dec 2021
5145,83697480,928.0,0.9297733333333332,11,9,/tqrahman/baseline-with-tf-and-feature-engineering,Tabular Playground Series - Dec 2021
5146,81873858,957.0,,23,23,/seungbumlim/tps-dec-2021-lgb-classifier-eda-baseline,Tabular Playground Series - Dec 2021
5147,83962657,959.0,,0,0,/etiennepinclaret/tps-dec-lgbm-optuna-tuning,Tabular Playground Series - Dec 2021
5148,81281671,979.0,,2,9,/rsesha/auto-visualization-of-tps-dec-2021-using-autoviz,Tabular Playground Series - Dec 2021
5149,81709992,981.0,,2,2,/mikhailzemskov/simple-eda-pytorch-catalyst,Tabular Playground Series - Dec 2021
5150,84120712,993.0,0.9426133333333332,1,0,/abanobmorgan/xgboost-tabular-playground,Tabular Playground Series - Dec 2021
5151,101532670,995.0,0.9035066666666668,0,1,/dgf4qu/tps-12-2021-xgboost-model,Tabular Playground Series - Dec 2021
5152,83390574,1006.0,0.9186166666666666,0,0,/boopathymsse/tps-dec21-logitboost,Tabular Playground Series - Dec 2021
5153,83114193,1013.0,0.9147566666666668,3,7,/datarohitingole/tps-dec-2021-eda-catboostclassifier,Tabular Playground Series - Dec 2021
5154,81568573,1017.0,0.9131633333333332,0,0,/sndpkirwai/tps-dec-2021-simple-linear-baseline,Tabular Playground Series - Dec 2021
5155,81621575,1018.0,,1,1,/rayhanlahdji/tps-1221-logistic-regression-bootstrapped,Tabular Playground Series - Dec 2021
5156,82602668,1023.0,,8,16,/thalesgaluchi/histograms-for-a-good-prediction,Tabular Playground Series - Dec 2021
5157,83949612,1059.0,,1,5,/shramanabhattacharya/forest-cover-type-prediction-using-random-forest,Tabular Playground Series - Dec 2021
5158,82204446,1091.0,0.47482,2,6,/namanbansalcodes/playground-dec2021-naman-svm,Tabular Playground Series - Dec 2021
5159,81297994,1112.0,,21,83,/carlmcbrideellis/some-pretty-t-sne-plots,Tabular Playground Series - Dec 2021
5160,82121981,1117.0,0.84526,1,6,/ccollado7/tps-dec-2021-eda,Tabular Playground Series - Dec 2021
5161,81473092,1121.0,0.7995533333333333,2,6,/rakesh0929b/tabular-playground-series-2021,Tabular Playground Series - Dec 2021
5162,81234545,1134.0,,0,4,/nafishamoin/tabular-playground-december-2021,Tabular Playground Series - Dec 2021
5163,82142123,1165.0,,4,9,/mohamedelsrogy/simple-nn-dr-eda-accuracy-96,Tabular Playground Series - Dec 2021
5164,82942755,1187.0,,0,3,/ayoubchaoui/dimensionality-reduction-algorithm,Tabular Playground Series - Dec 2021
5165,81574634,58.0,,2,1,/agarwalvishal00/idao-ml-bootcamp,IDAO 2022. ML Bootcamp - Insomnia
5166,89648665,368.0,,35,102,/sytuannguyen/tps-mar-2022-eda-model,Tabular Playground Series - Mar 2022
5167,89664770,296.0,,0,1,/dwoodlock/notebook2e8b91b564,Tabular Playground Series - Mar 2022
5168,90564440,217.0,,6,33,/cabaxiom/tps-mar-22-in-depth-eda-all-65-roads,Tabular Playground Series - Mar 2022
5169,89743087,387.0,,5,36,/martynovandrey/tps-mar-22-step-0-data-exploration-animation,Tabular Playground Series - Mar 2022
5170,89010793,393.0,5.059910560623355,1,7,/e0xextazy/tps-march-top-solution,Tabular Playground Series - Mar 2022
5171,91049611,397.0,,0,4,/saraswatitiwari/tps-march-2022,Tabular Playground Series - Mar 2022
5172,91712245,68.0,,0,11,/bhavesh0124/0-47-simple-neural-network,Tabular Playground Series - Mar 2022
5173,91219814,162.0,4.970940170940171,1,1,/riiatlmad/tabular-playground-series-mar-2022-lgbm-catboost,Tabular Playground Series - Mar 2022
5174,91281410,294.0,4.794871794871795,9,23,/abdullahkocak/fresh-duck-kaggler-tps-mar22,Tabular Playground Series - Mar 2022
5175,91442694,291.0,4.764102564102564,2,10,/pourchot/tps-2022-03-only-one-layer-for-neural-network,Tabular Playground Series - Mar 2022
5176,91071914,502.0,4.818803418803419,7,21,/bernhardklinger/march-tps-lgbm,Tabular Playground Series - Mar 2022
5177,89099477,148.0,5.378785618803421,3,31,/ashaykatrojwar/eda-and-auto-ml,Tabular Playground Series - Mar 2022
5178,89070121,153.0,5.242228655523349,1,6,/omarvivas/catboostmar22-v1,Tabular Playground Series - Mar 2022
5179,88999667,158.0,6.331623931623931,0,5,/pavan9065/explore-tps-mar-22,Tabular Playground Series - Mar 2022
5180,90878897,47.0,,3,6,/robertturro/tps-march-2022-useful-visuals,Tabular Playground Series - Mar 2022
5181,89149016,75.0,5.08388784359663,0,5,/rhythmcam/tps-mar-22-evalml-baseline,Tabular Playground Series - Mar 2022
5182,89149016,75.0,5.08388784359663,0,5,/rhythmcam/tps-mar-22-evalml-baseline,Tabular Playground Series - Mar 2022
5183,89246557,178.0,5.058119658119658,0,5,/eugenebee/tps-mar-22-catboost-baseline,Tabular Playground Series - Mar 2022
5184,90274085,67.0,4.895726495726496,2,16,/huseyincot/without-machine-learning-pick-the-means,Tabular Playground Series - Mar 2022
5185,91317001,185.0,,28,151,/ambrosm/tpsmar22-eda-which-makes-sense,Tabular Playground Series - Mar 2022
5186,89259463,414.0,5.109401709401709,4,5,/slythe/fight-night-ml-vs-mathematical-modelling,Tabular Playground Series - Mar 2022
5187,91344127,418.0,4.931623931623932,7,11,/packinman/tps-mar-2022-feature-engineering-and-catboost,Tabular Playground Series - Mar 2022
5188,115551421,511.0,4.986324786324786,0,11,/lonnieqin/tps-22-03-with-lstm,Tabular Playground Series - Mar 2022
5189,91303981,141.0,,11,52,/abdulravoofshaik/private-lb-top-2-google-s-tft,Tabular Playground Series - Mar 2022
5190,89117840,5.0,5.9930740760683765,0,2,/lisyuan0930/tps-mar-xgboost,Tabular Playground Series - Mar 2022
5191,91513375,326.0,4.803846153846152,0,4,/micgonzalez/tabular-playground-dataset,Tabular Playground Series - Mar 2022
5192,90075509,528.0,4.813675213675213,10,75,/alexryzhkov/lightautoml-with-fe-tps-mar-22,Tabular Playground Series - Mar 2022
5193,89099129,314.0,5.073504273504273,0,14,/matthewszhang/tps-march-automl-pycaret-and-feature-engineering,Tabular Playground Series - Mar 2022
5194,89969849,346.0,,10,28,/rbud613/tps-baseline-lgb-catboost,Tabular Playground Series - Mar 2022
5195,94232162,334.0,,6,37,/devsubhash/tps-march-eda-bokeh-holoviews-fe-modeling,Tabular Playground Series - Mar 2022
5196,90579118,449.0,4.957264957264957,3,8,/shoooono/tps-mar2022-catboost-lgb,Tabular Playground Series - Mar 2022
5197,90579118,449.0,4.957264957264957,3,8,/shoooono/tps-mar2022-catboost-lgb,Tabular Playground Series - Mar 2022
5198,89066650,112.0,,0,2,/nnjjpp/tps-mar-2022-rfr,Tabular Playground Series - Mar 2022
5199,91985933,519.0,4.98974358974359,0,34,/m1y7k8/tps-mar-2022-timeseries,Tabular Playground Series - Mar 2022
5200,90687715,195.0,4.95354663474211,4,15,/abdelrahmanrezk7/feature-engineering-catboost,Tabular Playground Series - Mar 2022
5201,91672821,391.0,4.914529914529915,8,34,/mukaseevru/tps-mar-22-fe-lama-lightautoml,Tabular Playground Series - Mar 2022
5202,90206992,522.0,4.852991452991453,0,3,/mayank00rastogi/tps-march22-lightautoml,Tabular Playground Series - Mar 2022
5203,90840182,265.0,,2,5,/sasakic/tps-mar-2022-sarimax-and-xgr,Tabular Playground Series - Mar 2022
5204,89740012,269.0,,12,26,/gazu468/eda-and-modeling-lb-5-264,Tabular Playground Series - Mar 2022
5205,91366491,413.0,,4,2,/kaicho0504/lgbm-baseline,Tabular Playground Series - Mar 2022
5206,89393562,585.0,5.104273504273504,3,10,,Tabular Playground Series - Mar 2022
5207,89393562,585.0,5.743589743589744,3,10,,Tabular Playground Series - Mar 2022
5208,91558496,299.0,,0,0,/morikawashinichi/tps-march-2022-lgbm-optuna-4-941,Tabular Playground Series - Mar 2022
5209,89586104,12.0,,0,2,/naokisugimura/tps-mar-2022-lightgbm-quickstart,Tabular Playground Series - Mar 2022
5210,89087792,317.0,,2,10,/ifashion/tps-mar-2022-forecast-based-on-yesterday,Tabular Playground Series - Mar 2022
5211,96967908,115.0,,1,6,/casati8/kaggle-tps-mar-2022-simple,Tabular Playground Series - Mar 2022
5212,89478091,298.0,,6,15,/kritidoneria/mljar-automl-tps-mar-22,Tabular Playground Series - Mar 2022
5213,90493703,29.0,,8,16,/cv13j0/tps-mar-2022-a-simple-gbt-model,Tabular Playground Series - Mar 2022
5214,91575908,7.0,4.883760683760684,10,23,/chikovalexander/tps-mar-2022-etna,Tabular Playground Series - Mar 2022
5215,92124867,15.0,,0,0,/olgapleshakova/tps-mar-2022-cosine-distance-averaging,Tabular Playground Series - Mar 2022
5216,89135962,70.0,5.935042735042735,1,8,/igorkf/tps-march-22-naive-baseline,Tabular Playground Series - Mar 2022
5217,90029900,439.0,5.097435897435897,4,6,/taranmarley/fe-eda-prediction,Tabular Playground Series - Mar 2022
5218,89712577,106.0,5.198290598290599,0,8,/zhangcheche/xgboost-tps-2022-03,Tabular Playground Series - Mar 2022
5219,89150905,426.0,,2,11,/nasil2/simple-eda,Tabular Playground Series - Mar 2022
5220,89156655,80.0,4.926495726495727,0,8,/horrip/tpsmar22-average-baseline-lb-4-992,Tabular Playground Series - Mar 2022
5221,89016607,428.0,,2,9,/sunilhule/tps-mar-2022-complete-eda-modelling,Tabular Playground Series - Mar 2022
5222,91011396,429.0,4.936752136752137,2,7,/alenic/only-median-lb-4-926,Tabular Playground Series - Mar 2022
5223,89202136,417.0,,4,14,/jwallib/clustering-morning-commutes,Tabular Playground Series - Mar 2022
5224,89997396,575.0,4.929950196192818,3,12,/abdelrahmanrabah/nn-kfold-model1,Tabular Playground Series - Mar 2022
5225,89334394,26.0,,9,35,/arootda/tps-mar-eda-modeling-with-optuna,Tabular Playground Series - Mar 2022
5226,89759825,389.0,,6,29,/wti200/advanced-mean-approaches,Tabular Playground Series - Mar 2022
5227,90087055,28.0,5.323076923076923,1,8,/alehandro35/tpsmar22-eda-boosting,Tabular Playground Series - Mar 2022
5228,91313857,593.0,,2,7,/ahmetcelik158/tps-mar-22-traffic-forecasting-boosted-hybrid,Tabular Playground Series - Mar 2022
5229,93016973,617.0,,0,0,/thomaspagesy/march-playground-tensorflow-bi-lstm-attention,Tabular Playground Series - Mar 2022
5230,90860713,233.0,,5,5,/davidhguerrero/gradient-boost-optuna-and-model-errors,Tabular Playground Series - Mar 2022
5231,89099669,222.0,,0,4,/yogeshkaushik/tabular-playgrounds-series-mar2022-eda,Tabular Playground Series - Mar 2022
5232,89230303,229.0,4.967521367521368,2,18,/samuelcortinhas/tps-mar-22-traffic-flow-forecasting,Tabular Playground Series - Mar 2022
5233,89658634,234.0,,1,2,/etiennepinclaret/quick-fe-pycaret-automl-mar-2022,Tabular Playground Series - Mar 2022
5234,89666533,237.0,,0,1,/louisheublein/xgboost-with-gpu-acceleration,Tabular Playground Series - Mar 2022
5235,91156647,258.0,4.967521367521368,1,1,/meancoder/martynov-andrey-preprocessing-deep-learning,Tabular Playground Series - Mar 2022
5236,92598833,657.0,,2,17,/masatomurakawamm/tps-mar2022-xgboost-hyperparametertuning,Tabular Playground Series - Mar 2022
5237,89448063,322.0,4.986324786324786,1,14,/ted0071/tps-mar-2022,Tabular Playground Series - Mar 2022
5238,89448063,322.0,5.016107823800134,1,14,/ted0071/tps-mar-2022,Tabular Playground Series - Mar 2022
5239,89558813,69.0,,29,74,/hasanbasriakcay/tps-mar22-eda-fe-baseline,Tabular Playground Series - Mar 2022
5240,89589522,567.0,,4,7,/imnaho/eda-tps-mar22,Tabular Playground Series - Mar 2022
5241,90127845,89.0,5.389059829059829,0,2,/coenvalk/march-2022-tps-baseline,Tabular Playground Series - Mar 2022
5242,90007781,94.0,,0,2,/shoytovma/base-line-means-no-ml-predictions-score-5-016,Tabular Playground Series - Mar 2022
5243,91821424,39.0,5.042735042735043,0,1,/thariqnugrohotomo/sklearn-gbdt-tps2022mar-39th-place,Tabular Playground Series - Mar 2022
5244,90177606,271.0,4.991452991452992,7,26,/mehrdadsadeghi/tps-mar2022-traffic-flow-eda-simple-forecast,Tabular Playground Series - Mar 2022
5245,91363793,143.0,5.063145063247858,5,10,/asifahmadshaik/prediction-using-simple-xgboost,Tabular Playground Series - Mar 2022
5246,91728747,183.0,,0,0,/bvarkoly/tabular-playground-2022-march,Tabular Playground Series - Mar 2022
5247,91364733,474.0,5.003418803418803,0,0,/r0hn00/tabplay-march,Tabular Playground Series - Mar 2022
5248,91362900,34.0,6.188034188034188,1,7,/rolerik/traffic-frequency-analysis,Tabular Playground Series - Mar 2022
5249,89651943,32.0,5.0085470085470085,0,1,/pranesh97/march-playground,Tabular Playground Series - Mar 2022
5250,89092825,645.0,5.009528070085474,0,5,/lizakonopelko/tps-mar-2022-fe-lama-lightautoml,Tabular Playground Series - Mar 2022
5251,90986337,58.0,5.094017094017094,0,3,/jorgeascencion/tps-2022-03-random-forest-regressor,Tabular Playground Series - Mar 2022
5252,90120622,209.0,,0,1,/lolienca/simple-eda-and-visualization,Tabular Playground Series - Mar 2022
5253,91741425,287.0,5.023143694865906,13,19,/klipefrem/tps-mar-2022-catboost-randomforest,Tabular Playground Series - Mar 2022
5254,89346565,320.0,5.046153846153846,0,2,/sdysch/eda-congestion-spikes-and-naive-predictions,Tabular Playground Series - Mar 2022
5255,89416919,51.0,,1,3,/mohamedayoubchettouh/road-connections,Tabular Playground Series - Mar 2022
5256,89415690,341.0,5.041025641025641,2,6,/ranjeetshrivastav/tps-march-22,Tabular Playground Series - Mar 2022
5257,91013422,360.0,,2,5,/genkiokano/automl-lightgbm-tps-mar-2022,Tabular Playground Series - Mar 2022
5258,136867542,312.0,5.034188034188034,6,27,/gkitchen/congestion-prediction,Tabular Playground Series - Mar 2022
5259,91207477,1.0,,1,5,/ottpocket/wide-neural-predictions-with-optuna,Tabular Playground Series - Mar 2022
5260,91449349,564.0,5.063373863247862,2,2,/harshhzz/march-pred,Tabular Playground Series - Mar 2022
5261,90119966,358.0,5.07008547008547,1,2,/sfktrkl/tps-mar-2022,Tabular Playground Series - Mar 2022
5262,90940106,455.0,,0,4,/tariqchhussain/xgboost-optuna-k-fold-cv-tps-march-22,Tabular Playground Series - Mar 2022
5263,90415559,273.0,,39,43,/sathyakrishnan12/kaggle-tps-march-22,Tabular Playground Series - Mar 2022
5264,89544441,599.0,,2,5,/stpeteishii/tps0322-time-course-data,Tabular Playground Series - Mar 2022
5265,90209378,213.0,12.834188034188037,0,3,/michaelsammons/march2022-kaggle-tps,Tabular Playground Series - Mar 2022
5266,91474411,319.0,,54,101,/lordozvlad/tps-mar-fast-workflow-using-scikit-learn-intelex,Tabular Playground Series - Mar 2022
5267,89968009,362.0,,6,15,/shimjongsoo/tps-mar22-rf-lgbm-rf-public-5-12,Tabular Playground Series - Mar 2022
5268,118385103,549.0,11.672198177068411,4,13,/p7476762/gradient-boost-regression-predict-eda,Tabular Playground Series - Mar 2022
5269,89620409,547.0,,1,1,/nicolashans/tps-march-2022-eda-congestion-map-animation,Tabular Playground Series - Mar 2022
5270,89455857,595.0,,0,3,/maulberto3/tps-mar-2022-roads-heatmaps,Tabular Playground Series - Mar 2022
5271,91294333,691.0,,1,6,/naotokitajima/notebookec44a52739,Tabular Playground Series - Mar 2022
5272,91602314,683.0,5.159063538461541,1,9,/ramniwashkumar/tps-fe-xgbregressor,Tabular Playground Series - Mar 2022
5273,89909683,578.0,5.166608665785772,7,25,/kimchanyoung/simple-random-forest-regression-using-gridsearch,Tabular Playground Series - Mar 2022
5274,91788997,517.0,5.241750131774864,0,3,/artyomgrishanov/catboost-for-tabular-playground,Tabular Playground Series - Mar 2022
5275,90075157,711.0,,0,1,/honghongchen/playground-regression-xgboost-catboost,Tabular Playground Series - Mar 2022
5276,91890581,697.0,,0,2,/hirenr/march-tps-eda-prediction,Tabular Playground Series - Mar 2022
5277,91451290,494.0,5.230373147863251,6,12,/prashantpathak244/xgboost-regression-for-beginner,Tabular Playground Series - Mar 2022
5278,90365367,686.0,13.77395675629293,0,5,/adwaitkesharwani/simple-linear-regression-for-beginners,Tabular Playground Series - Mar 2022
5279,90546159,625.0,,0,6,/gauravduttakiit/tps-032022-lazypredict,Tabular Playground Series - Mar 2022
5280,89259916,583.0,5.359925001790776,2,10,/akioonodera/tps-mar2022-lgbm-regression,Tabular Playground Series - Mar 2022
5281,90229353,661.0,5.774364102564101,0,7,/amarloni/tps-mar22-catboost-ohe,Tabular Playground Series - Mar 2022
5282,91945192,552.0,5.268376068376068,0,0,/boopathymsse/tpsmar22,Tabular Playground Series - Mar 2022
5283,88998055,601.0,11.555463234250483,2,9,/ebrahimhaquebhatti/tps-march-2022-pycaret-model-comparison,Tabular Playground Series - Mar 2022
5284,89880718,696.0,10.39626855017061,0,0,/nikkifitz/playground-mar22-sub-1-linear-regression-model,Tabular Playground Series - Mar 2022
5285,91983476,658.0,,7,7,/jiprud/tps-mar22-rookie-eda-submission,Tabular Playground Series - Mar 2022
5286,89897364,738.0,6.778807370372975,0,0,/rizkykiky/rf-baseline-tps-mar-2022,Tabular Playground Series - Mar 2022
5287,89100935,369.0,,0,1,/karthickp6/eda-tps-mar22,Tabular Playground Series - Mar 2022
5288,89020156,742.0,12.311111111111112,0,2,/tracyporter/mar-22-traffic-ts,Tabular Playground Series - Mar 2022
5289,89612022,631.0,5.482857871794866,1,8,/rajnishkumar546/tps-march,Tabular Playground Series - Mar 2022
5290,90957108,480.0,5.492250572625589,1,2,/chethanbr86/tabular-playground-series-mar-2022,Tabular Playground Series - Mar 2022
5291,90225276,587.0,5.323076923076923,0,3,/paulomarquies/tps-mar-22-preprocessing-and-catboost,Tabular Playground Series - Mar 2022
5292,93405186,656.0,,0,1,/harsh2040/model-prediction,Tabular Playground Series - Mar 2022
5293,90194249,635.0,,0,5,/snehangsude/in-depth-eda-congestion-hourly-weekly,Tabular Playground Series - Mar 2022
5294,89123501,715.0,,0,5,/thalesgaluchi/march-2022-playground-start-exploring,Tabular Playground Series - Mar 2022
5295,89077898,554.0,5.767521367521368,0,9,/jonigooner/pycaret-spot-checking,Tabular Playground Series - Mar 2022
5296,89026482,763.0,,0,13,/venkatkumar001/tps3-22-baseline-model-skfold,Tabular Playground Series - Mar 2022
5297,91566576,724.0,6.121367521367521,14,30,/sanjaylalwani/tps-march22-with-ensemble,Tabular Playground Series - Mar 2022
5298,91780846,702.0,,0,0,/dcrowd/knn-note,Tabular Playground Series - Mar 2022
5299,91772319,718.0,,0,1,/aboriginal3153/tps-mar-22-pytorch-lstm,Tabular Playground Series - Mar 2022
5300,89612982,752.0,,5,10,/syedhaideralizaidi/tabular-playground-series-march-22,Tabular Playground Series - Mar 2022
5301,91162617,556.0,,2,2,/thefringthing/tps-march-2022-lightgbm-with-tidymodels,Tabular Playground Series - Mar 2022
5302,90573905,784.0,,0,2,/peressim/tps-march-2022,Tabular Playground Series - Mar 2022
5303,91469736,694.0,5.651093890598301,0,0,/floopybits/time-attributes-xgboost-regression,Tabular Playground Series - Mar 2022
5304,91469736,694.0,5.651093890598301,0,0,/floopybits/time-attributes-xgboost-regression,Tabular Playground Series - Mar 2022
5305,91257264,850.0,,5,5,/duncankmckinnon/separate-prophet-models,Tabular Playground Series - Mar 2022
5306,89786399,473.0,5.705982905982906,0,1,/alexandreayari/tps-03-22-super-learner-ensemble,Tabular Playground Series - Mar 2022
5307,89406687,716.0,,0,0,/abdoulayebalde/congestion-prediction-using-xgboost-and-catboost,Tabular Playground Series - Mar 2022
5308,91182143,653.0,12.109401709401707,8,14,/samu2505/xgboost-rocks,Tabular Playground Series - Mar 2022
5309,89982537,799.0,,2,12,/wonjinkim1010/ml-with-randomforest,Tabular Playground Series - Mar 2022
5310,91114251,783.0,,0,3,/catadanna/tab-mar-2022-folds,Tabular Playground Series - Mar 2022
5311,88999616,825.0,,0,4,/yokeshkummar/the-venerable-linear-regression,Tabular Playground Series - Mar 2022
5312,90673784,848.0,470.4281975149154,0,5,/himanshusirsat/tab-ply-march22,Tabular Playground Series - Mar 2022
5313,89959080,773.0,,2,14,/jeonghyunha/tps-mar-2022-simple-preprocessing-regression,Tabular Playground Series - Mar 2022
5314,88990026,891.0,10.975190311183107,3,19,/inversion/tps-mar-22-cyclical-features,Tabular Playground Series - Mar 2022
5315,91691324,782.0,11.492307692307692,0,0,/ashishtop/stats-regression,Tabular Playground Series - Mar 2022
5316,89970700,916.0,13.307692307692308,1,1,/longzhi/tps202203,Tabular Playground Series - Mar 2022
5317,90049724,928.0,,0,3,/sourav2pal/traffic,Tabular Playground Series - Mar 2022
5318,84718561,8.0,,0,1,/haochengweng/bert-try,DM2021 ISA5810 Lab2 Homework
5319,83615733,2.0,0.6289674912232929,156,547,/cdeotte/tensorflow-longformer-ner-cv-0-633,Feedback Prize - Evaluating Student Writing
5320,82643228,20.0,,0,3,/vanle73/data-analysis-is-all-you-need-firstly,Feedback Prize - Evaluating Student Writing
5321,90410205,9.0,0.7069599623685388,2,1,/goldenlock/feedback-base,Feedback Prize - Evaluating Student Writing
5322,89377819,14.0,0.7026016581611662,0,0,/aishikai/fb-pytorch-inference,Feedback Prize - Evaluating Student Writing
5323,90930180,38.0,,6,11,/mmisty/student-writing-eda,Feedback Prize - Evaluating Student Writing
5324,100127966,35.0,,0,1,/trushk/feedback-topics-identification-with-bertopic,Feedback Prize - Evaluating Student Writing
5325,101752402,63.0,,6,10,/shigengtian/prepare-mlm-data,Feedback Prize - Evaluating Student Writing
5326,117304377,52.0,,0,0,/aman1391/topic-and-subtopics-graph-using-umap,Feedback Prize - Evaluating Student Writing
5327,118860860,64.0,,0,1,/ktgiahieu/rapids-umap-tfidf-kmeans-discovers-15-topics,Feedback Prize - Evaluating Student Writing
5328,83023270,47.0,,3,28,/bacicnikola/sequence-bucketing-pytorch-implementation,Feedback Prize - Evaluating Student Writing
5329,92154260,81.0,,0,0,/bachan/feedback-prize-2021-0-714-private-lb,Feedback Prize - Evaluating Student Writing
5330,84451177,98.0,,0,1,/intjerlu/tensorflow-longformer-v1,Feedback Prize - Evaluating Student Writing
5331,88212920,121.0,,0,1,/mauricefunk/two-longformers-are-better-than-1,Feedback Prize - Evaluating Student Writing
5332,83862448,109.0,,15,32,/nbroad/iob-bio-format-for-ner-feedback-prize,Feedback Prize - Evaluating Student Writing
5333,88290147,129.0,,2,13,/dinowun/eda-simplified-feedback-prize,Feedback Prize - Evaluating Student Writing
5334,86933263,96.0,,0,1,/longhuqin/discovers-keywords,Feedback Prize - Evaluating Student Writing
5335,87923074,138.0,,0,28,/yama09/nlp-on-student-writing-eda,Feedback Prize - Evaluating Student Writing
5336,85815633,160.0,,8,21,/zaakciiru/tf-huggingface-roformer-tpu-train,Feedback Prize - Evaluating Student Writing
5337,83303421,178.0,,41,191,/robikscube/student-writing-competition-twitch-stream,Feedback Prize - Evaluating Student Writing
5338,89380395,182.0,,0,0,/charliezimmerman/add-nothing-label-to-submission-dataframe,Feedback Prize - Evaluating Student Writing
5339,87947390,208.0,,0,0,/renokan/analysis-of-discourse-type-text-columns,Feedback Prize - Evaluating Student Writing
5340,107386528,166.0,,1,9,/verracodeguacas/feedback-3-eda-sentence-transformers,Feedback Prize - Evaluating Student Writing
5341,84635347,235.0,,0,2,/leemop/sec-nlp-study-prize-feedback,Feedback Prize - Evaluating Student Writing
5342,84231021,258.0,,9,70,/andypenrose/text-augmentation-with-nlpaug,Feedback Prize - Evaluating Student Writing
5343,87352673,232.0,,0,0,/fmc123/notebook2d9ed4b867,Feedback Prize - Evaluating Student Writing
5344,89299879,282.0,0.6910858764497494,23,82,,Feedback Prize - Evaluating Student Writing
5345,85359124,545.0,0.6902150481960136,7,51,/fxalll/0-690-try-better-parameters,Feedback Prize - Evaluating Student Writing
5346,89419340,430.0,,12,63,/mikiota/data-augmentation-csv-txt-using-back-translation,Feedback Prize - Evaluating Student Writing
5347,82860951,316.0,0.2258255058073797,28,202,/julian3833/feedback-baseline-sentence-classifier-0-226,Feedback Prize - Evaluating Student Writing
5348,87619739,359.0,0.6891818328909081,0,0,/kausheeki01/advantage-of-2-longformers-over-1,Feedback Prize - Evaluating Student Writing
5349,90865238,371.0,,0,1,/ollibolli/q-a-pytorch,Feedback Prize - Evaluating Student Writing
5350,85299778,1024.0,,0,1,/somesh88/inference-longformer,Feedback Prize - Evaluating Student Writing
5351,86742955,402.0,,2,7,/vickeytomer/eda-student-writing-vk,Feedback Prize - Evaluating Student Writing
5352,87716887,616.0,,2,7,/hechtjp/bert-pytorch-lightning-baseline-training,Feedback Prize - Evaluating Student Writing
5353,88715966,584.0,,1,1,/priyankawawdhane/autoviml,Feedback Prize - Evaluating Student Writing
5354,82465496,877.0,,2,8,/prohor/check-for-intersecting-entities,Feedback Prize - Evaluating Student Writing
5355,82709427,870.0,0.5920259128911824,12,83,/zzy990106/pytorch-ner-infer,Feedback Prize - Evaluating Student Writing
5356,86594321,688.0,0.6902150481960138,0,27,/luhuihu/nlp-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5357,86594321,688.0,0.6902150481960138,0,27,/luhuihu/nlp-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5358,86594321,688.0,0.6902150481960136,0,27,/luhuihu/nlp-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5359,89689848,690.0,,8,13,/kalilurrahman/feedback-prize-eda-first,Feedback Prize - Evaluating Student Writing
5360,88074553,706.0,,0,3,/derrickmwiti/bert-base-uncased,Feedback Prize - Evaluating Student Writing
5361,87896622,711.0,,0,0,/vincentholmes/competition,Feedback Prize - Evaluating Student Writing
5362,90197891,896.0,0.6897116980883148,1,0,/valentinlaurent2/two-longformers-inference,Feedback Prize - Evaluating Student Writing
5363,83722128,1239.0,,9,62,/kaggleqrdl/v4expmt-tensorflow-longformer-ner-cv-0-634,Feedback Prize - Evaluating Student Writing
5364,85812447,939.0,,2,23,/seshurajup/feedback-predict-oof-for-two-longformers,Feedback Prize - Evaluating Student Writing
5365,82479587,952.0,,1,11,/darknesszx/bert-large,Feedback Prize - Evaluating Student Writing
5366,82380484,954.0,0.0381365465609996,5,56,/ilialar/feedback-prize-simple-eda,Feedback Prize - Evaluating Student Writing
5367,85317466,961.0,0.689181832890908,0,26,/parikshitsharma2001/two-longformers-are-better-than-1,Feedback Prize - Evaluating Student Writing
5368,85519481,978.0,0.689181832890908,0,8,/jaypeng/feedback-prize,Feedback Prize - Evaluating Student Writing
5369,82707933,984.0,0.1456423401312986,0,9,/rnepal2/a-baseline-solution,Feedback Prize - Evaluating Student Writing
5370,85519775,1012.0,,0,3,/ramjanamyadav/rapids-umap-tfidf-kmeans-discovers-15-topics,Feedback Prize - Evaluating Student Writing
5371,83174278,1017.0,,0,1,/tengwang0318/longformertorchbasedonchris,Feedback Prize - Evaluating Student Writing
5372,85992119,1019.0,,0,3,/nikhilsatani/feedback-prize-1,Feedback Prize - Evaluating Student Writing
5373,83256179,1030.0,,0,4,/hjhgjghhg/feedback-prize-itpt,Feedback Prize - Evaluating Student Writing
5374,82969856,1052.0,0.0381365465609996,0,2,/saraswatitiwari/feedback-prize-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5375,86047835,1057.0,0.689181832890908,0,4,/konstantinplashinnov/the-essay-recognizer,Feedback Prize - Evaluating Student Writing
5376,87011275,1073.0,,5,17,/sasukess1/bert-baseline-0-462-val,Feedback Prize - Evaluating Student Writing
5377,85933700,1097.0,,1,9,/ycca1018/feedbackprize-startereda-jp-en,Feedback Prize - Evaluating Student Writing
5378,87853890,1220.0,,2,18,/narukawa/eda-feedback-prize-2021,Feedback Prize - Evaluating Student Writing
5379,88175646,1144.0,,0,0,/penpen926/baseline2-longformer,Feedback Prize - Evaluating Student Writing
5380,86858594,1226.0,,1,4,/gopidurgaprasad/new-prediction-string,Feedback Prize - Evaluating Student Writing
5381,88476101,910.0,0.3936276334540283,0,3,/leekh7411/fbpz-tensorflow-2-bert-base-cased,Feedback Prize - Evaluating Student Writing
5382,89053319,1177.0,,8,15,/nulldata/patchworklib-combine-multiple-py-charts-easily,Feedback Prize - Evaluating Student Writing
5383,90184375,930.0,,12,52,/jillanisofttech/2-longformers-are-better-than-1,Feedback Prize - Evaluating Student Writing
5384,85421760,1179.0,,0,7,/ashwinvijayanpillai/length-mismatch-analysis,Feedback Prize - Evaluating Student Writing
5385,82828219,1234.0,,1,8,/revathiprakash/feedback-prize-baseline-ner-pytorch-inference,Feedback Prize - Evaluating Student Writing
5386,85375242,1187.0,,0,1,/arunamenon/feedback-prize-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5387,82489061,948.0,,0,12,/swaralipibose/highly-indetailed-eda-observing-relation-in-data,Feedback Prize - Evaluating Student Writing
5388,82622621,972.0,,0,5,/rhythmcam/eda-feedback-prize-2021,Feedback Prize - Evaluating Student Writing
5389,83077836,913.0,0.0634841714996942,0,4,/aliasgherman/simple-starter-code-distillibert-token-classific,Feedback Prize - Evaluating Student Writing
5390,86086357,1243.0,,33,137,/odins0n/feedback-prize-eda,Feedback Prize - Evaluating Student Writing
5391,86313939,1267.0,,1,21,/jdoesv/topics-identification,Feedback Prize - Evaluating Student Writing
5392,82726000,1253.0,0.051268886976038,0,1,/neosoonhua/1-naive-bayes-with-stemmer,Feedback Prize - Evaluating Student Writing
5393,87877966,1288.0,,9,105,/cpmpml/faster-metric-computation,Feedback Prize - Evaluating Student Writing
5394,89591793,1316.0,,0,3,/amulil/simple-longformer-n-fold-train,Feedback Prize - Evaluating Student Writing
5395,89271145,1327.0,,0,0,,Feedback Prize - Evaluating Student Writing
5396,82375922,1507.0,,0,16,,Feedback Prize - Evaluating Student Writing
5397,83059348,1358.0,,0,0,/patipanrattanawin/feedback-prize-part-infer,Feedback Prize - Evaluating Student Writing
5398,85301025,1377.0,,0,3,/narendra/feedback-prize-statistical-eda,Feedback Prize - Evaluating Student Writing
5399,82516169,1436.0,,0,4,/pavan9065/feedback-prize-eda-and-modeling,Feedback Prize - Evaluating Student Writing
5400,84542109,1517.0,,6,33,/katsuyanomura/eda-topic-of-essay,Feedback Prize - Evaluating Student Writing
5401,82961299,1405.0,,1,4,/vladlee/evaluatingwriting-eda,Feedback Prize - Evaluating Student Writing
5402,84954757,1453.0,,3,11,/abdelamgeed/rnn-lstm,Feedback Prize - Evaluating Student Writing
5403,87049467,1478.0,0.6289674912232929,0,7,/dingli/evaluating-student-writing-error-visualization,Feedback Prize - Evaluating Student Writing
5404,88320958,1484.0,0.6289674912232929,0,1,/paulmineau/tensorflow-longformer-ner-cv-0-633,Feedback Prize - Evaluating Student Writing
5405,84746822,1547.0,,0,1,/winun1127/fp-tf-baseline-longformer,Feedback Prize - Evaluating Student Writing
5406,84746822,1547.0,,0,1,/winun1127/fp-tf-baseline-longformer,Feedback Prize - Evaluating Student Writing
5407,82421266,1567.0,,10,20,/au1206/feedback-prize-the-first-glance-eda,Feedback Prize - Evaluating Student Writing
5408,82534800,1685.0,,1,2,/vabatista/feedback-prize-yet-another-eda-stats-and-nlp,Feedback Prize - Evaluating Student Writing
5409,83035805,1714.0,,2,4,/csarolivares/evaluating-student-writing-eda-data-cleaning,Feedback Prize - Evaluating Student Writing
5410,82458085,1692.0,,5,29,/coldfir3/eda-w-outlier-exploration-naive-baseline,Feedback Prize - Evaluating Student Writing
5411,82840825,1717.0,0.5955647793714404,0,6,/karthikbhandary2/feedback,Feedback Prize - Evaluating Student Writing
5412,91392652,1760.0,,0,0,/hrodbert/playground-notebook,Feedback Prize - Evaluating Student Writing
5413,140004963,1798.0,,0,1,/haozhang607/feedback-prize-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5414,89074695,1804.0,,0,0,/lvcvesaul/nlp-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5415,87432851,1827.0,,2,21,/reymaster/sentence-classification-with-svm-and-tf-idf,Feedback Prize - Evaluating Student Writing
5416,85348546,1828.0,0.523679398999672,0,3,/ksmshankar/evaluating-student-writing-roberta,Feedback Prize - Evaluating Student Writing
5417,86964641,1871.0,,3,19,/markwijkhuizen/preprocessing-oversampling,Feedback Prize - Evaluating Student Writing
5418,86409312,1875.0,0.0636364219670368,0,2,/irynaalshakova/fork-of-2-1-statement-types-similarity-doc2vec-lr,Feedback Prize - Evaluating Student Writing
5419,82563500,1896.0,0.22744280615079,1,18,/abhishekme19b069/eda-full-classification-pipeline-bert,Feedback Prize - Evaluating Student Writing
5420,83364831,1927.0,,0,6,/ibrezmohd/feedback-price-eda-markov-transition-matrix,Feedback Prize - Evaluating Student Writing
5421,88908727,1919.0,0.2144938303738411,0,0,/singhnavleen/feedback-prize-evaluating-student-writing,Feedback Prize - Evaluating Student Writing
5422,100192872,1934.0,,2,8,/chandraprajapati/feedback-prize-logistic-regression,Feedback Prize - Evaluating Student Writing
5423,83628745,1953.0,,0,8,/saiedalimoradi/baseline-ulmfit,Feedback Prize - Evaluating Student Writing
5424,90035926,1973.0,0.1499379742139798,0,2,/sjsn2002/rf-tfidf,Feedback Prize - Evaluating Student Writing
5425,90035926,1973.0,0.1499379742139798,0,2,/sjsn2002/rf-tfidf,Feedback Prize - Evaluating Student Writing
5426,88975420,1979.0,0.1480635767742585,2,20,/nehapawar/tfidf-random-forest-classifier,Feedback Prize - Evaluating Student Writing
5427,88840471,1987.0,0.1475736817006704,0,0,/ashuto7h/roberta-from-simpletransformer,Feedback Prize - Evaluating Student Writing
5428,82957908,1985.0,0.0506929370626271,0,8,/travistyler/student-writing-eda-and-testing,Feedback Prize - Evaluating Student Writing
5429,85466600,1989.0,,0,2,/gbalachandhiran/eda-of-the-corpus,Feedback Prize - Evaluating Student Writing
5430,82400772,2021.0,0.0147728957719006,1,6,/karthikeya14/eda-bert,Feedback Prize - Evaluating Student Writing
5431,82400772,2021.0,0.0147728957719006,1,6,/karthikeya14/eda-bert,Feedback Prize - Evaluating Student Writing
5432,82400772,2021.0,0.0,1,6,/karthikeya14/eda-bert,Feedback Prize - Evaluating Student Writing
5433,85481504,2044.0,,0,2,/dokeefe/training-data-to-bow,Feedback Prize - Evaluating Student Writing
5434,83943128,49.0,,0,1,/lichifang/code-lcf,110NYCUpython
5435,85955696,6.0,,0,2,/weixuanyou/110368002-frozenlake,Frozen Lake
5436,85360741,291.0,4.080665308063993,6,20,/mehrankazeminia/delete-feb29th-2016-fork-keras-quickstart,Tabular Playground Series - Jan 2022
5437,84270599,208.0,5.008970528717617,7,20,/bernhardklinger/tps-jan-2022,Tabular Playground Series - Jan 2022
5438,84220453,259.0,7.902893106437318,9,17,/pourchot/tps-2022-01-baseline-and-eda,Tabular Playground Series - Jan 2022
5439,84220453,259.0,7.816896511137726,9,17,/pourchot/tps-2022-01-baseline-and-eda,Tabular Playground Series - Jan 2022
5440,84220453,259.0,5.918559723961653,9,17,/pourchot/tps-2022-01-baseline-and-eda,Tabular Playground Series - Jan 2022
5441,86709749,40.0,,4,14,/jbomitchell/boltzmann-ensemble-kaggle-stores,Tabular Playground Series - Jan 2022
5442,86197780,97.0,4.002895976042821,5,25,/sytuannguyen/tps-jan-2022-automated-ensembling,Tabular Playground Series - Jan 2022
5443,84401734,178.0,10.415332318885245,2,10,/ankitkalauni/tps-jan-22-noob-learning,Tabular Playground Series - Jan 2022
5444,86020258,321.0,,4,16,/akmeghdad/tps-0122-all-in-one-preprocessing-feature-eng,Tabular Playground Series - Jan 2022
5445,84153513,294.0,43.92651278936777,2,10,/karthikbhandary2/playground-series-analysis-randomforestregresor,Tabular Playground Series - Jan 2022
5446,84442941,84.0,4.963348452610481,8,21,/meetnagadia/tps-22-eda-prediction,Tabular Playground Series - Jan 2022
5447,116469905,286.0,8.02859754486687,6,12,/lonnieqin/tps-01-22-with-catboost,Tabular Playground Series - Jan 2022
5448,84857561,223.0,,1,14,/arhitbosetagore/visualization-forecasting-sarimax-fb-prophet,Tabular Playground Series - Jan 2022
5449,86734889,246.0,,7,40,/mhslearner/tps-jan-2022-time-series-forcasting,Tabular Playground Series - Jan 2022
5450,84286754,304.0,6.458602706852955,1,1,/saraswatitiwari/tabular-playground-series-jan-2022,Tabular Playground Series - Jan 2022
5451,84386701,265.0,,23,97,/hasanbasriakcay/playground-jan-22-eda-feature-engineering,Tabular Playground Series - Jan 2022
5452,84134859,241.0,,0,4,/rhythmcam/tps-01-22-pycaret-lightgbm,Tabular Playground Series - Jan 2022
5453,86080228,859.0,12.277161004553829,2,6,/caneiro/tps-2022-01-jan-prophet-baseline,Tabular Playground Series - Jan 2022
5454,84538511,245.0,,0,8,/eugenebee/tps-jan22-phik-fe-discussion,Tabular Playground Series - Jan 2022
5455,84156664,147.0,,14,37,/akmalmir/pycaret-for-starters-tps-jan-2022,Tabular Playground Series - Jan 2022
5456,84140695,225.0,,11,14,/ebrahimhaquebhatti/eureka-eureka-visualizations,Tabular Playground Series - Jan 2022
5457,84561837,1.0,,11,141,/ambrosm/tpsjan22-01-eda-which-makes-sense,Tabular Playground Series - Jan 2022
5458,86264986,204.0,5.259885239716344,4,15,/lisyuan0930/tps-jan-2022-xgboost-gdp,Tabular Playground Series - Jan 2022
5459,84248965,44.0,,3,19,/sardorabdirayimov/tps-jan-2022-visualization,Tabular Playground Series - Jan 2022
5460,84168656,45.0,5.476926759140642,0,0,/kavehshahhosseini/tps-jan-2022-pycaret,Tabular Playground Series - Jan 2022
5461,84233033,48.0,,1,5,/shravankoninti/tps-jan-2022-ts-eda,Tabular Playground Series - Jan 2022
5462,84818925,34.0,,1,10,/anirudhyadav9784/xg-boost-with-gdp-amazon-s-sales-data,Tabular Playground Series - Jan 2022
5463,85647222,165.0,,40,136,/usharengaraju/tensorflow-tf-data-keraspreprocessinglayers-w-b,Tabular Playground Series - Jan 2022
5464,85018635,190.0,8.435001293602403,3,17,/sasakic/tps-jan-22-simple-lstm,Tabular Playground Series - Jan 2022
5465,85018635,190.0,8.435001293602403,3,17,/sasakic/tps-jan-22-simple-lstm,Tabular Playground Series - Jan 2022
5466,85135789,153.0,16.248210759947735,14,15,/anjalisrajan/tps-jan-2022-simple-model-using-xgboost,Tabular Playground Series - Jan 2022
5467,94043273,188.0,,6,40,/devsubhash/tps-jan-2022-eda-pycaret-blend,Tabular Playground Series - Jan 2022
5468,84361191,132.0,,0,9,/pavan9065/tps-jan22-eda-model,Tabular Playground Series - Jan 2022
5469,85607764,261.0,4.331618399269523,29,65,/maxencefzr/tps-jan22-eda-fe-simple-catboost,Tabular Playground Series - Jan 2022
5470,85443252,13.0,,4,20,/paddykb/tps-2022-01-a-look-at-ambrosm-s-linear-model,Tabular Playground Series - Jan 2022
5471,86671192,234.0,4.059737265787029,2,2,/alexandreayari/tps-01-22-catboost-w-pycaret,Tabular Playground Series - Jan 2022
5472,85088839,250.0,,2,8,/victordonjuan/tps-jan-2022-eda-feature-e-linear-model,Tabular Playground Series - Jan 2022
5473,84259481,214.0,6.185679649692186,33,49,/cv13j0/tps-jan22-quick-eda-xgboost,Tabular Playground Series - Jan 2022
5474,84307096,123.0,,10,8,/mohammadhossein77/tps-jan2022-ploty-gridsearch-xgboost,Tabular Playground Series - Jan 2022
5475,85800984,101.0,,3,7,/slythe/tps-jan-22-eda-pycaret-baseline,Tabular Playground Series - Jan 2022
5476,86206196,221.0,13.33281636272598,19,32,/sarabhian/free-time-learning,Tabular Playground Series - Jan 2022
5477,86568046,207.0,4.0732983179902,8,36,/chikovalexander/tps-jan-2022-etna,Tabular Playground Series - Jan 2022
5478,85984568,155.0,,12,49,/lucamassaron/festivities-in-finland-norway-sweden,Tabular Playground Series - Jan 2022
5479,86035233,282.0,6.920293235212779,1,4,/asnikitin/lightautoml,Tabular Playground Series - Jan 2022
5480,84857546,140.0,,0,7,/sabinaabdurakhmanova/ensemble-again-maximizing-the-score-metrics,Tabular Playground Series - Jan 2022
5481,84620205,357.0,5.830033677931064,2,19,,Tabular Playground Series - Jan 2022
5482,84255757,407.0,,0,3,/pelagial/tps-january-22-eda,Tabular Playground Series - Jan 2022
5483,85648807,16.0,,25,58,/samuelcortinhas/tps-jan-22-eda-modelling,Tabular Playground Series - Jan 2022
5484,84940902,27.0,6.20670706746163,9,18,/isha20/tps-jan-2022-catboost-eda,Tabular Playground Series - Jan 2022
5485,84752372,118.0,4.894295647958103,0,8,/tobarr/catboost-es-feature-engine-no-gdp-data-4-89lb,Tabular Playground Series - Jan 2022
5486,84712543,7.0,,0,9,/l3llff/prophet,Tabular Playground Series - Jan 2022
5487,86955402,5.0,4.135229851807168,1,5,/junkoda/holiday-kernel,Tabular Playground Series - Jan 2022
5488,84249692,262.0,,0,6,/jacobbarton/playground-jan-2022-eda,Tabular Playground Series - Jan 2022
5489,85820914,115.0,10.768442880858004,20,49,/satoshiss/tps-jan-with-xgboost,Tabular Playground Series - Jan 2022
5490,85319156,24.0,,1,12,/nancysamuel/tps-jan-2022-eda,Tabular Playground Series - Jan 2022
5491,86454556,325.0,4.631431536256455,2,11,/abdulravoofshaik/tps-jan-2022-random-forest-based-ensemble,Tabular Playground Series - Jan 2022
5492,84922762,150.0,,1,6,/rizkykiky/tpsjan22-03-linear-model,Tabular Playground Series - Jan 2022
5493,142030204,375.0,,0,0,/haozhang607/tabular-playground-series-jan-2022,Tabular Playground Series - Jan 2022
5494,84424184,398.0,,2,9,/ccollado7/complete-eda,Tabular Playground Series - Jan 2022
5495,84357881,373.0,,2,16,/siukeitin/tps012022-detrending-case-study-i,Tabular Playground Series - Jan 2022
5496,85511276,341.0,14.277352860266156,2,7,/samir95/baseline-randomforests,Tabular Playground Series - Jan 2022
5497,86542671,462.0,4.661450564315195,4,9,/harshul23/tps-jan22-eda-fe-catboost,Tabular Playground Series - Jan 2022
5498,84738320,434.0,,5,10,/kailex/tabular-playground-22ts,Tabular Playground Series - Jan 2022
5499,86187739,405.0,,4,10,/torii0139/stacking-baseline-and-quick-eda-tps-jan-2022,Tabular Playground Series - Jan 2022
5500,85597777,388.0,4.665017747691024,9,12,/kratos2597/tabular-playground-series-jan-2022,Tabular Playground Series - Jan 2022
5501,84540868,346.0,,2,2,/vladlee/tps-jan2022-lgbm-optuna,Tabular Playground Series - Jan 2022
5502,84560082,342.0,,1,4,/lexplua/exponential-smoothing,Tabular Playground Series - Jan 2022
5503,86016094,327.0,,7,7,/kdsharmaai/tps-jan-2022-multiple-linear-regression,Tabular Playground Series - Jan 2022
5504,86381533,472.0,,1,2,/khaymon24/tps-jan2022-gbm,Tabular Playground Series - Jan 2022
5505,84582196,659.0,4.918126297729208,35,92,/mfedeli/tabular-playground-series-jan-2022,Tabular Playground Series - Jan 2022
5506,84619800,413.0,,0,3,/marcocavaco/tabular-playground-train-model-using-pycaret,Tabular Playground Series - Jan 2022
5507,84627474,628.0,5.032361681770899,0,2,/kjw3226/tps-jan-2022-base-lightgbm,Tabular Playground Series - Jan 2022
5508,85991496,606.0,4.970104752647019,0,1,/hotdog1029/my-tabular-playground-series-jan-2022,Tabular Playground Series - Jan 2022
5509,84591287,602.0,5.756435423968481,0,3,/valou7/tps-jan22-date-engineering,Tabular Playground Series - Jan 2022
5510,86603464,397.0,6.629129493602459,1,0,/andrewgustyjrstudent/tabularplayground,Tabular Playground Series - Jan 2022
5511,86362535,400.0,,0,1,/stevenzhou905/tab-method-pt2,Tabular Playground Series - Jan 2022
5512,85356137,660.0,,0,4,/ayhampar/simple-code-with-score-8-25215,Tabular Playground Series - Jan 2022
5513,86655483,768.0,5.385924645319977,0,0,/mayank00rastogi/tps-j22-mean-of-xgboost-catboost-lgbm,Tabular Playground Series - Jan 2022
5514,84923893,515.0,5.757862732448217,23,68,/adamwurdits/tps-01-2022-catboost-seed-averaging,Tabular Playground Series - Jan 2022
5515,87019876,384.0,5.479505712456556,9,89,/carlmcbrideellis/tps-jan-2022-a-simple-average-model-no-ml,Tabular Playground Series - Jan 2022
5516,84530787,379.0,9.89746259695646,7,18,/rnepal2/tps-time-series-prediction-with-neuralprophet,Tabular Playground Series - Jan 2022
5517,85167380,586.0,7.630426901721476,2,6,/naokisugimura/tps-jan-2022-feature-engineering-quickstart,Tabular Playground Series - Jan 2022
5518,86163395,807.0,,0,5,/chachiawacef/series-using-stack-of-lgbm-catboost-xgboost,Tabular Playground Series - Jan 2022
5519,85776740,537.0,,1,6,/hlgdatascience/kaggle-store-sales-eda,Tabular Playground Series - Jan 2022
5520,84800421,442.0,,4,7,/kztwt10/xgboost-tps-jan-2022-english,Tabular Playground Series - Jan 2022
5521,85537379,646.0,,26,49,/nishantdhingra/detailed-eda-and-vizualizations-tps-january-2022,Tabular Playground Series - Jan 2022
5522,84469613,396.0,,0,3,/notnamed/tps-2022-january-holidays-since-until-pycaret,Tabular Playground Series - Jan 2022
5523,84502577,592.0,12.832963637612783,1,6,/dextermojo/eda-of-tps-2022-fbprophet-baseline,Tabular Playground Series - Jan 2022
5524,84501802,719.0,,0,3,/ox0000dead/tps-jan-22-dnn-for-tabular-with-smape,Tabular Playground Series - Jan 2022
5525,86266270,611.0,,7,12,/casati8/kaggle-tps-jan2022-fastai,Tabular Playground Series - Jan 2022
5526,111583429,767.0,,5,14,/tylerjthomas9/julia-stacking-baseline-tps-jan2022,Tabular Playground Series - Jan 2022
5527,86149869,715.0,,0,2,/paulreiners/loadpandasdataframe,Tabular Playground Series - Jan 2022
5528,85192447,475.0,,0,4,/pranaytiwari/tps-2022-eda-linear-regression-baseline,Tabular Playground Series - Jan 2022
5529,86278078,474.0,6.83545102534244,5,17,/prashantpathak244/lgm-boost,Tabular Playground Series - Jan 2022
5530,85795452,482.0,,0,3,/adipif/tps-jan2022-a-little-dumb-easy-way,Tabular Playground Series - Jan 2022
5531,156349623,621.0,,0,5,/srsses/tabular-playground-jan-2022-using-xgboost,Tabular Playground Series - Jan 2022
5532,84380194,443.0,7.816771953999717,5,45,/gunesevitan/tabular-playground-series-jan-2022-prophet,Tabular Playground Series - Jan 2022
5533,86477382,600.0,,0,2,/fonlor/tabular-pg-with-ensemble-on-scikit-models,Tabular Playground Series - Jan 2022
5534,84231160,544.0,,0,4,/tracyporter/jan-22-tabular-hist-grad-boost-reg,Tabular Playground Series - Jan 2022
5535,87037228,507.0,,2,0,/leesstephanie/tps-jan-2022-leesstephanie,Tabular Playground Series - Jan 2022
5536,86472418,618.0,5.964110830042072,2,5,/jazzbasscd/prophet-stock-market-data-kalman-filter-in-r,Tabular Playground Series - Jan 2022
5537,84567527,639.0,,1,1,/ameerhamza319/baseline-catboost-tps-jan-2k22,Tabular Playground Series - Jan 2022
5538,86756435,473.0,,0,3,/irillit/basic-xgbregressor,Tabular Playground Series - Jan 2022
5539,84505550,564.0,6.002410613775712,1,5,/vishalmishra1400/xgboost-hyperparameter-tuning,Tabular Playground Series - Jan 2022
5540,116847014,467.0,6.479447723689412,33,38,/p7476762/8-models-add-xgboost-compare-score-mse,Tabular Playground Series - Jan 2022
5541,84377003,558.0,6.099084558883245,4,10,/mohammadkashifunique/xgboost-hyperparameteroptimization-optuna,Tabular Playground Series - Jan 2022
5542,86798977,526.0,,6,9,/hosseinbehjat/time-series-linearmodel-with-tps-jan-22,Tabular Playground Series - Jan 2022
5543,85323367,1123.0,6.132592239200412,3,10,/danielkorth/tps-jan22-fastai,Tabular Playground Series - Jan 2022
5544,86216593,504.0,,1,3,/hikarumoriya/tabular-playground-eda-jpn,Tabular Playground Series - Jan 2022
5545,86463403,932.0,7.196491163137986,3,6,/jorgeascencion/tps-2022-01-xgboost-regressor-optuna,Tabular Playground Series - Jan 2022
5546,85094114,733.0,6.360947047625371,2,12,/hassanmojab/tps-jan-2022-catboost,Tabular Playground Series - Jan 2022
5547,86119307,647.0,,0,3,/tariqchhussain/xgboost-optuna-tps-jan-2022,Tabular Playground Series - Jan 2022
5548,85600525,650.0,6.380729759419741,1,19,/ranjeetshrivastav/tps-jan-22-base-xgb-lgb,Tabular Playground Series - Jan 2022
5549,86011064,857.0,6.431555302902511,3,8,/sherey/tpsjan2022,Tabular Playground Series - Jan 2022
5550,85946811,721.0,,0,4,/uzdavinys/tps-22-jan-sklearn-desicion-tree,Tabular Playground Series - Jan 2022
5551,85699411,877.0,6.460627140686073,2,5,/vvkhdk/used-data-from-worldbank-org-api-tps-jan-22,Tabular Playground Series - Jan 2022
5552,85391618,758.0,,0,7,/peressim/tps-jan-2022-eda,Tabular Playground Series - Jan 2022
5553,84909003,803.0,,54,113,/lordozvlad/tps-jan-fast-pycaret-with-scikit-learn-intelex,Tabular Playground Series - Jan 2022
5554,86138594,801.0,,2,7,/venkatkumar001/tps-jan-22-baseline-eda-cat-xgb,Tabular Playground Series - Jan 2022
5555,84335615,902.0,,1,7,/utsavk02/tabular-playground-series-jan-2022-eda,Tabular Playground Series - Jan 2022
5556,85325160,809.0,,1,10,/mmellinger66/tps-jan-22-xgboost-cv-oof,Tabular Playground Series - Jan 2022
5557,84547167,918.0,6.761640277431755,0,7,/zhangcheche/tps-2022-jan-xgboost-baseline,Tabular Playground Series - Jan 2022
5558,87720733,914.0,26.80068741518736,3,5,/vijaykris/tabular-jan-22-regressor,Tabular Playground Series - Jan 2022
5559,84210611,970.0,,1,4,/danie1yan9/tps2022jan-a-short-and-brief-understanding,Tabular Playground Series - Jan 2022
5560,86590052,612.0,,3,5,/amaneamane/eda-ml-for-beginner,Tabular Playground Series - Jan 2022
5561,86547384,800.0,6.912714644122969,1,2,/vishugupta0509/jan22playground,Tabular Playground Series - Jan 2022
5562,86644627,1020.0,7.154806822757948,0,5,/imnaho/simple-xgboost-model,Tabular Playground Series - Jan 2022
5563,86294774,1054.0,,0,4,/hari141v/tabular-playground-series-jan-2022-basic-eda-ipynb,Tabular Playground Series - Jan 2022
5564,84683514,711.0,,1,9,/alehandro35/lightautoml-regression-task,Tabular Playground Series - Jan 2022
5565,86558278,1030.0,6.970355071721583,0,0,/boopathymsse/tps-jan22-with-xgboost,Tabular Playground Series - Jan 2022
5566,86558278,1030.0,6.970355071721583,0,0,/boopathymsse/tps-jan22-with-xgboost,Tabular Playground Series - Jan 2022
5567,89514008,950.0,,0,5,/maulberto3/tps-jan2022-simple-exploratory-visualizations,Tabular Playground Series - Jan 2022
5568,85134138,1007.0,6.983061706715392,5,6,/prateek1202/tps-jan2022,Tabular Playground Series - Jan 2022
5569,84818905,870.0,,2,8,/abhijitd16/neural-prophet-and-simple-nn,Tabular Playground Series - Jan 2022
5570,84821132,1016.0,,0,6,/drcapa/tps-2022-01-starter,Tabular Playground Series - Jan 2022
5571,85847476,994.0,7.022571443693246,0,0,/kubervarshney/tps-jan-2022,Tabular Playground Series - Jan 2022
5572,85366745,1017.0,7.358881561767124,2,15,/masatomurakawamm/tps-jan2022-xgboost-and-optuna-baseline,Tabular Playground Series - Jan 2022
5573,86473548,824.0,,4,4,/joppegeluykens/simple-feedforward-neural-net-with-pytorch,Tabular Playground Series - Jan 2022
5574,85399987,774.0,,1,4,/christopherchaves/m-encoding-vs-simple-encoding,Tabular Playground Series - Jan 2022
5575,85593792,1042.0,7.093467670502926,6,18,/phuc16102001/tps-2022-xgboost,Tabular Playground Series - Jan 2022
5576,86290525,1008.0,7.103326217580534,0,1,/parthavjoshi/notebook-1,Tabular Playground Series - Jan 2022
5577,84574554,956.0,9.669201523504563,0,6,/rsesha/jan22-tps-featurewiz-lightgbm-9-4-score,Tabular Playground Series - Jan 2022
5578,86606860,966.0,7.336722334329242,1,11,/quamarequbal/tabular-playground-series-regression-algos,Tabular Playground Series - Jan 2022
5579,86980713,839.0,,2,8,/buzzini/eda-predictions-tabular-playground-jan-2022,Tabular Playground Series - Jan 2022
5580,84147541,890.0,7.478959677643148,3,9,/medaxone/r-passing-benchmark-with-insights-and-zero-model,Tabular Playground Series - Jan 2022
5581,87318604,989.0,,0,4,/maheswarareddyp/tabular-jan-2022,Tabular Playground Series - Jan 2022
5582,84577115,1035.0,11.606996066376125,1,5,/sumeetbohra/tps-jan-22,Tabular Playground Series - Jan 2022
5583,85596925,1024.0,8.24579739026686,0,5,/shoytovma/tps-jan-2022-base-line-model,Tabular Playground Series - Jan 2022
5584,84694760,728.0,,1,8,/rumasinha/exploratory-data-analysis,Tabular Playground Series - Jan 2022
5585,84391692,1125.0,,0,2,/kohjiahng/jan-2022-tbp-eda,Tabular Playground Series - Jan 2022
5586,86124398,1091.0,,0,3,/quentincarle/tabular-playground-series-january-2022,Tabular Playground Series - Jan 2022
5587,85537131,894.0,,0,4,/andreabignardi/tps-jan-2022-fe-eda-regression-wip,Tabular Playground Series - Jan 2022
5588,85973467,1041.0,,0,2,/pinstripezebra/january-tps,Tabular Playground Series - Jan 2022
5589,84101058,783.0,9.0186935438065,0,3,/ant3ng/simple-lightgbm-tps-jan-2022,Tabular Playground Series - Jan 2022
5590,84422120,1167.0,12.638114306467788,3,12,/bcruise/tps-jan-2022-linear-baseline,Tabular Playground Series - Jan 2022
5591,86519280,1085.0,9.710076449120637,0,0,/nikhilsatani/tpg-0122,Tabular Playground Series - Jan 2022
5592,86251396,1112.0,10.482457944095636,4,9,/mustafamu/tps-jan-2022-cnn,Tabular Playground Series - Jan 2022
5593,85353326,1129.0,10.526499277631771,0,7,/paveltrusov/tps-jan-2022-prophet,Tabular Playground Series - Jan 2022
5594,86326448,1092.0,76.86387319519396,1,11,/demko1/tabular-playground-xgboost,Tabular Playground Series - Jan 2022
5595,84251110,1124.0,,0,2,/abhishekaggarwal896/kaggleplayground,Tabular Playground Series - Jan 2022
5596,84454895,1162.0,11.052311927912486,0,9,/sagnik1511/fast-walkthrough-tps-jan-2k22,Tabular Playground Series - Jan 2022
5597,84454895,1162.0,10.836014355979326,0,9,/sagnik1511/fast-walkthrough-tps-jan-2k22,Tabular Playground Series - Jan 2022
5598,87711336,1222.0,,11,20,/ammarabbasi1040/tps-simple-eda-fe-modelling,Tabular Playground Series - Jan 2022
5599,84196394,1218.0,11.577822475115148,0,5,/datarohitingole/tps-jan-2022-eda-catboostregressor,Tabular Playground Series - Jan 2022
5600,86401475,1236.0,20.965228886128163,2,7,/vadimabronin/tabular-playground-series-with-catboost,Tabular Playground Series - Jan 2022
5601,85502712,1223.0,,1,12,/samu2505/ensemble-and-gradient-boosting-in-scikit-learn,Tabular Playground Series - Jan 2022
5602,88306999,1366.0,,1,2,/mahditavakol/jan22-visualization,Tabular Playground Series - Jan 2022
5603,87033374,1209.0,14.095751141356072,2,7,/chiranjeevbit/time-series-notebook,Tabular Playground Series - Jan 2022
5604,87033374,1209.0,11.645390556775263,2,7,/chiranjeevbit/time-series-notebook,Tabular Playground Series - Jan 2022
5605,86367378,1174.0,12.573358177858598,0,0,/r0hn00/competition-1,Tabular Playground Series - Jan 2022
5606,84556848,1351.0,12.834210245130809,2,8,/stpeteishii/tps0122-multi-prophet,Tabular Playground Series - Jan 2022
5607,101883932,1289.0,,0,2,/abdalrahmanashour/tabular-playground-series-jan-2022-prediction,Tabular Playground Series - Jan 2022
5608,85387145,1211.0,12.805689266837922,2,9,/nourajo/tps-eda-xgboost,Tabular Playground Series - Jan 2022
5609,86433351,1259.0,25.56322534924724,0,3,/anologicon/back-to-the-data-science,Tabular Playground Series - Jan 2022
5610,84122179,1360.0,,8,29,/jeongbinpark/tps-jan-simple-eda-and-fbprophet,Tabular Playground Series - Jan 2022
5611,85136256,1291.0,,19,21,/sathyakrishnan12/kaggle-tps-jan-12,Tabular Playground Series - Jan 2022
5612,85594152,1244.0,,0,2,/snehangsude/jan-2022-tps-explained-eda-v-1-0,Tabular Playground Series - Jan 2022
5613,84574407,1427.0,18.237596526064443,0,7,/farelarden/tabular-jan-2022-using-facebook-prophet,Tabular Playground Series - Jan 2022
5614,86639474,1383.0,20.526828770997632,1,1,/himanshusirsat/tabular-play-jan22,Tabular Playground Series - Jan 2022
5615,84542989,1478.0,,0,5,/hongyongmin/baseline,Tabular Playground Series - Jan 2022
5616,84641754,1497.0,,1,11,/ayoubchaoui/lightgbm-vs-xgboost-vs-decision-tree,Tabular Playground Series - Jan 2022
5617,86176743,1525.0,,0,9,/pranalibose/tabularplaygroundseries-jan-starter-notebook,Tabular Playground Series - Jan 2022
5618,86181622,1502.0,,1,4,/zurriyatafatni/eda-linear-and-random-forest-regression,Tabular Playground Series - Jan 2022
5619,85975432,1521.0,,0,8,/moizkhan11/tabplay-jan2022-smape-45,Tabular Playground Series - Jan 2022
5620,84102562,1518.0,,2,3,/abhiroopbasak/salesdataregression,Tabular Playground Series - Jan 2022
5621,85507209,1560.0,,0,4,/takkimsncn/specific-items-sales-prediction,Tabular Playground Series - Jan 2022
5622,86554672,1583.0,,6,5,/souravsahabec/eda-with-plotly-and-seaborn,Tabular Playground Series - Jan 2022
5623,85765194,1.0,,0,6,/mananjhaveri/pog001-spacy-and-tfidf-features,Predict Youtube Video Likes (Pog Series #1)
5624,84952815,1.0,,4,17,/schopenhacker75/catboost-starter-eda,WiDS Datathon 2022
5625,88941891,8.0,17.692579949701148,0,3,/kostoglot/wids2022-18-5x-private,WiDS Datathon 2022
5626,88896874,4.0,19.15749620872329,0,7,/bablos/excel-style-top50-solution-wids2022,WiDS Datathon 2022
5627,84772471,7.0,,5,13,/ggxgboostgg/wids-2022-shap-values-validation,WiDS Datathon 2022
5628,87228631,22.0,44.94034948317099,4,5,/cristianlazoquispe/automl-h2o-shap-explanation,WiDS Datathon 2022
5629,87228631,22.0,44.94034948317099,4,5,/cristianlazoquispe/automl-h2o-shap-explanation,WiDS Datathon 2022
5630,89304415,24.0,19.095312368893268,0,1,/jinluo/wids-building-signature-clean,WiDS Datathon 2022
5631,87725537,59.0,20.3530296511273,0,2,/omarvivas/xgbkagglewids22opt-v1,WiDS Datathon 2022
5632,89118157,109.0,,0,4,/pavelvod/wids2022-find-city-of-each-building,WiDS Datathon 2022
5633,84844077,62.0,,2,13,/ccollado7/wids-complete-eda,WiDS Datathon 2022
5634,88550576,220.0,,5,34,/amdionascu/wids2022-eda,WiDS Datathon 2022
5635,88978029,147.0,,0,7,/uyangas/eda-wids-2022,WiDS Datathon 2022
5636,88845708,64.0,23.575169175424225,2,4,/kiranchowdary/wids-modelling-light-gbm,WiDS Datathon 2022
5637,88691942,101.0,48.37587896979639,0,4,/jananishankar/wids-datathon-2022-fastai,WiDS Datathon 2022
5638,84985249,237.0,44.04611547753471,2,12,/ulrich07/wids-2022-ann-tf-starter,WiDS Datathon 2022
5639,87044106,153.0,32.57858007397285,1,19,/suradechk/wids-ml-voting,WiDS Datathon 2022
5640,86237345,145.0,35.1541079499373,5,31,,WiDS Datathon 2022
5641,87099226,135.0,52.52418115184722,0,13,/abh1jeetpandey/wids-nn-for-genrating-embeddings,WiDS Datathon 2022
5642,84722227,150.0,,8,29,/shrutisaxena/wids2022-starter-code,WiDS Datathon 2022
5643,88815341,162.0,,0,8,/gavisr/wids-2022-lgbm-for-beginners,WiDS Datathon 2022
5644,84636425,177.0,39.66173863097901,0,7,/rhythmcam/automl-h2o-wids2002,WiDS Datathon 2022
5645,88119194,196.0,58.94125711710892,0,2,/madagasygirl/wids-datathon-regression-with-h2o-in-r,WiDS Datathon 2022
5646,87497863,210.0,52.38786204352301,0,3,/shamiaaftab/wids-2022-basic-ols-sfs,WiDS Datathon 2022
5647,85951859,221.0,,2,9,/yunlinlew/wids-22-eda-lightgbm-comparecatencoding-shap,WiDS Datathon 2022
5648,88555559,215.0,,2,17,/kritidoneria/wids2022-automl-mljar,WiDS Datathon 2022
5649,88676135,242.0,,0,1,/binitagiri/kaggle-sub-feb24-binita,WiDS Datathon 2022
5650,88676929,267.0,,0,10,/henaghonia/fttransformer,WiDS Datathon 2022
5651,86472595,277.0,28.17393032349724,4,39,/icfstat/starter-baseline-wids-2022-workshop,WiDS Datathon 2022
5652,88284388,284.0,,5,35,/angiengkh/wids-2022-eda-feature-engineering,WiDS Datathon 2022
5653,86643197,319.0,,0,3,/lizakonopelko/wids-2022-catboost,WiDS Datathon 2022
5654,85038412,331.0,50.48927756631711,9,18,/ahana91/wids-2022-eda-comparison-of-5-simple-models,WiDS Datathon 2022
5655,86411684,295.0,,13,47,/shreyasajal/wids-datathon-2022-explainable-ai-walkthrough,WiDS Datathon 2022
5656,85195559,354.0,,2,9,/aliphya/using-the-blending-strategy,WiDS Datathon 2022
5657,86432774,340.0,,34,85,/farazrahman/bee-building-energy-efficiency-eda,WiDS Datathon 2022
5658,86917841,348.0,,2,10,/isha20/wids-2022-eda,WiDS Datathon 2022
5659,86987269,353.0,,0,10,/iprogrammer/wids-2022-datathon-maastricht-2nd-day,WiDS Datathon 2022
5660,85841586,405.0,35.9037863383104,2,10,/lonnieqin/wids-datathon-2022-with-catboost,WiDS Datathon 2022
5661,88956767,470.0,42.2800308313038,0,2,/vpalotai/wids-2022-eda-feature-engineering-ensembles,WiDS Datathon 2022
5662,93762812,505.0,,0,8,/avinashreddykovvuri/a01-vitb-avinash-s-wids-mark-6,WiDS Datathon 2022
5663,87283576,484.0,,0,22,/pranalibose/wids-temp-feature-engineering,WiDS Datathon 2022
5664,84837405,563.0,,12,13,/sanu123/wids-2022-autoencoder,WiDS Datathon 2022
5665,85337849,583.0,,0,4,/annerb/notebook528d6fcead,WiDS Datathon 2022
5666,158794349,587.0,,0,0,/lxkhati/eda-wids-2022,WiDS Datathon 2022
5667,88725330,665.0,,0,1,/hebamahmoud000/notebook-2,WiDS Datathon 2022
5668,89886208,668.0,,0,4,/sadiqueabdullah/wids-datathon2022,WiDS Datathon 2022
5669,86681757,718.0,,0,4,/kamaljp/building-energy-usage-edanmodeling,WiDS Datathon 2022
5670,88760200,633.0,,0,2,/chakryamenh/datathon2022-practicefromtheguideline,WiDS Datathon 2022
5671,88497365,705.0,,0,6,/sagarikajadon/wids-in-depth-eda,WiDS Datathon 2022
5672,88714630,710.0,58.360275018316415,2,7,/virajkadam/wids-catboost-regressor-with-optuna,WiDS Datathon 2022
5673,88714630,710.0,58.36428599264295,2,7,/virajkadam/wids-catboost-regressor-with-optuna,WiDS Datathon 2022
5674,87007982,805.0,100.80535359747633,0,3,/shrutishrestha/wids-kathmandu,WiDS Datathon 2022
5675,85727985,802.0,,0,8,/komaldiwe/wids2022,WiDS Datathon 2022
5676,85363599,8.0,,0,1,/hariaakashk/fifa-notebook,Kick-off 2022
5837,90986059,9.0,,0,1,/chabir/funny-patterns-v1,Netflix Appetency
5838,91850820,3.0,,0,5,/hamzaouammou/netflix-3rd-place-basic-solution,Netflix Appetency
5839,91285132,8.0,0.7780546460677363,4,19,/docxian/netflix-appetency-h2o-starter,Netflix Appetency
5840,87631897,4.0,0.7872225210790976,0,1,/jayjay75/netflix-automl-1,Netflix Appetency
5841,90255153,39.0,,47,88,/mehrdadsadeghi/netflix-appetency-consumer-classification,Netflix Appetency
5842,90715617,94.0,0.6980830122236572,1,3,/kaanguven/netflix-appetency-the-neural-network-approach,Netflix Appetency
5843,88452960,44.0,0.7872396950743925,0,4,/nichin/netflix-appetency-eda-modeling-by-lgbm-optuna,Netflix Appetency
5844,90164871,57.0,0.7872555479931261,1,3,/orkunaran/netflix-appetency-power-averaging,Netflix Appetency
5845,87002796,20.0,,6,15,/towhidultonmoy/netflix-appetency-understanding-the-dataset,Netflix Appetency
5846,87561711,42.0,0.7724676151291802,4,5,/sravanneeli/netflix-appetency,Netflix Appetency
5847,89328968,35.0,,0,2,/pasuvulasaikiran/fork-of-netflix-axgb-feature-engg,Netflix Appetency
5848,87231565,84.0,,1,5,/guptadikshant/netflix-challenge-eda-and-kfold,Netflix Appetency
5849,89963940,69.0,,14,56,/gopidurgaprasad/netflix-appetency-stater-eda-model,Netflix Appetency
5850,87078838,129.0,,2,7,/ismailaseck/starters-starter-netflix-appetency-eda,Netflix Appetency
5851,86930789,97.0,,4,12,/rnepal2/netflix-appetency-a-lot-of-things-to-do,Netflix Appetency
5852,122900185,100.0,,0,0,/pawan2905/netflix-appetency,Netflix Appetency
5853,87378254,119.0,,7,7,/default404/data-cleaning-model-building-imp-feature-ranking,Netflix Appetency
5854,87161218,19.0,0.7851925548352459,1,12,/alexryzhkov/19th-place-solution-lightautoml-for-netflix,Netflix Appetency
5855,87161218,19.0,0.7851759092705755,1,12,/alexryzhkov/19th-place-solution-lightautoml-for-netflix,Netflix Appetency
5856,87161218,19.0,0.7850806596505171,1,12,/alexryzhkov/19th-place-solution-lightautoml-for-netflix,Netflix Appetency
5857,92032246,130.0,0.7775042195185363,1,3,/rsesha/netflix-appetency-with-featurewiz,Netflix Appetency
5858,91477391,78.0,0.783562346358796,2,6,/abhinavmukherjee22/netflix-appetency-consumer-classification,Netflix Appetency
5859,87833417,101.0,,0,3,/gauravduttakiit/netflix-appetency-flaml-f1,Netflix Appetency
5860,117373390,85.0,,11,28,/jacoporepossi/this-is-why-pandas-describe-is-useful,Netflix Appetency
5861,91214798,117.0,0.7834611518942124,2,3,/rocklen/netflix-appetency-2,Netflix Appetency
5862,87872389,132.0,,0,3,/sourabhy/netflix-apptency-eda-h2o-automl,Netflix Appetency
5863,86821790,114.0,,0,5,/magicfox94/feature-eng-xgboost,Netflix Appetency
5864,87001785,160.0,,4,8,/samu2505/netflix-visualization-simple-baseline,Netflix Appetency
5865,91703899,164.0,0.744164540614121,0,0,/sivsankar/netflix-appetency-using-boruta-worth-a-try,Netflix Appetency
5866,90210482,166.0,,0,0,/sharmaakshat/ds-evaluation,Netflix Appetency
5867,91623530,179.0,,0,0,/pankajsonawane1998/netflix-appetency-kaggle-hackathon-code-file,Netflix Appetency
5868,88698875,185.0,,9,18,/lakhankumawat/data-preprocessing,Netflix Appetency
5869,86956654,190.0,0.6700497675962114,0,12,/aliaslm99/netflix-appetency-beginner-s-guide,Netflix Appetency
5870,88433556,67.0,0.9403254972875226,9,17,/santhoshkumarv/autism-xgboost-shap-values,ML Olympiad - Autism Prediction Challenge
5871,87730101,70.0,,3,10,/venkatkumar001/apc1-automatic-eda-tf-df,ML Olympiad - Autism Prediction Challenge
5872,89026038,45.0,0.9453405017921148,10,20,/mhslearner/ml-olympiad-autism-prediction-challenge,ML Olympiad - Autism Prediction Challenge
5873,86884171,52.0,0.9415130324221234,7,16,,ML Olympiad - Autism Prediction Challenge
5874,109511006,68.0,,40,95,/aishwarya2210/ml-olympiad-prediction-of-likelihood-autism,ML Olympiad - Autism Prediction Challenge
5875,89549639,34.0,,0,6,/arnavr10880/autism-pred-eda-xgboost,ML Olympiad - Autism Prediction Challenge
5876,89361610,42.0,0.948252688172043,6,24,/samuelcortinhas/asd-prediction-eda-weighted-ensemble,ML Olympiad - Autism Prediction Challenge
5877,87459575,43.0,,0,3,/suchighurka/autism-prediction-detailed-eda,ML Olympiad - Autism Prediction Challenge
5878,88260603,13.0,0.9434202161474888,0,7,/docxian/autism-prediction-evalml,ML Olympiad - Autism Prediction Challenge
5879,86985060,10.0,,0,5,/gauravduttakiit/autism-prediction-autoviz,ML Olympiad - Autism Prediction Challenge
5880,89659890,44.0,,0,3,/sohithbandari/ml-olympiad-autism-predictor-with-basic-dnn,ML Olympiad - Autism Prediction Challenge
5881,87502415,14.0,0.9423606696333968,8,11,/vadimabronin/best-score-in-open-notebooks-like-please,ML Olympiad - Autism Prediction Challenge
5882,86590606,21.0,0.9404534859080314,14,21,/igorkf/mlolympiad-autismpredictionchallenge-eda-baseline,ML Olympiad - Autism Prediction Challenge
5883,87905823,29.0,0.7783428692519602,0,9,/sidharkal/autism-prediction-with-random-forest,ML Olympiad - Autism Prediction Challenge
5884,87037381,1.0,,1,8,/aliphya/eda-autism-prediction,ML Olympiad - Autism Prediction Challenge
5885,87890305,47.0,,0,2,/sanjay147/lgbm-classifier-regressor-ensemble-with-5-fold-cv,ML Olympiad - Autism Prediction Challenge
5886,87221198,37.0,0.9196863742318288,0,2,/sohailshaik272/autism-prediction-using-logistic-regression,ML Olympiad - Autism Prediction Challenge
5887,88438759,64.0,,9,18,/anjalisharma123/ml-olympiad-autism-prediction,ML Olympiad - Autism Prediction Challenge
5888,88496046,103.0,,0,4,/harsh2040/try-simple-eda-techniques,ML Olympiad - Autism Prediction Challenge
5889,131579712,77.0,0.7934587813620072,8,25,/gkitchen/autism-prediction,ML Olympiad - Autism Prediction Challenge
5890,87945748,92.0,,5,14,/gabrieldu69/data-viz-ml,ML Olympiad - Autism Prediction Challenge
5891,88303923,95.0,,3,6,/tajinderpalsingh61/autism-prediction-challenge-pycaret,ML Olympiad - Autism Prediction Challenge
5892,89868141,81.0,,2,5,/furkangokmen/autism-prediction-challenge,ML Olympiad - Autism Prediction Challenge
5893,86849492,101.0,,4,8,/taranmarley/extra-trees-with-pycaret,ML Olympiad - Autism Prediction Challenge
5894,87576359,100.0,,27,47,/ninjaac/mlolymplad-complete-eda,ML Olympiad - Autism Prediction Challenge
5895,87475810,74.0,0.8044077134986226,2,7,/rahimanshu/ml-olympiad-6-ml-algos-eda-multi-results-roc-80,ML Olympiad - Autism Prediction Challenge
5896,87782507,83.0,,3,25,/amanrosekaursethi/autismprediction-eda-sl,ML Olympiad - Autism Prediction Challenge
5897,88140918,94.0,,10,26,/aradhanapratap/autism-prediction-eda-classification-analysis,ML Olympiad - Autism Prediction Challenge
5898,90965048,4.0,,12,14,/kdsharmaai/4th-place-sol-asd-prediction-ridge-classifier,ML Olympiad - Autism Prediction Challenge
5899,87772650,91.0,,1,7,/stpeteishii/ml-olympiad-lgbm-optuna-auc-roc,ML Olympiad - Autism Prediction Challenge
5900,88259390,1.0,,64,240,/ambrosm/tpsfeb22-01-eda-which-makes-sense,Tabular Playground Series - Feb 2022
5901,89039032,3.0,,7,12,/oxzplvifi/tpsfeb22-et-knn-pseudolabel-lightautoml-ffnn,Tabular Playground Series - Feb 2022
5902,89009231,4.0,0.990863912454194,4,9,/e0xextazy/tps-feb-2022-blending-knn-resnet-softvoting,Tabular Playground Series - Feb 2022
5903,86821362,10.0,,2,10,/sytuannguyen/eda-lgbm-model,Tabular Playground Series - Feb 2022
5904,88977030,14.0,,0,2,/adegladius/tp-feb-2022-using-denoising-autoencoder-network,Tabular Playground Series - Feb 2022
5905,87757298,20.0,0.978414738215953,22,49,/hamzaghanmi/welcome-tps-feb-2022,Tabular Playground Series - Feb 2022
5906,87211961,154.0,0.9140605391295618,0,3,/mirenaborisova/tabular-playground-feb-2022-01,Tabular Playground Series - Feb 2022
5907,87211961,154.0,0.908739521108378,0,3,/mirenaborisova/tabular-playground-feb-2022-01,Tabular Playground Series - Feb 2022
5908,87211961,154.0,0.9122032026504694,0,3,/mirenaborisova/tabular-playground-feb-2022-01,Tabular Playground Series - Feb 2022
5909,87907199,156.0,0.9766076000200792,0,5,/arshdeepsingh6991/tpsfeb22-4-extra-trees-classifier-with-gcd,Tabular Playground Series - Feb 2022
5910,88822555,108.0,0.9885547914261332,1,9,/martynovandrey/et-cv-clustering,Tabular Playground Series - Feb 2022
5911,87666354,157.0,0.984237739069324,8,41,/max1mum/extra-trees-cv-voting,Tabular Playground Series - Feb 2022
5912,87360099,152.0,0.9041212790522564,2,11,/rhythmcam/tps-02-22-xgb-simple-baseline,Tabular Playground Series - Feb 2022
5913,88937737,39.0,0.9902113347723508,13,63,/alexryzhkov/tps-feb-22-lightautoml-pseudolabel,Tabular Playground Series - Feb 2022
5914,87066534,41.0,0.9874002309121028,4,24,/mhslearner/tps-feb-2022-lgbm-pseudo-labeling,Tabular Playground Series - Feb 2022
5915,106793238,82.0,,0,4,/agorinenko/feb-2022-part1-exploratorydataanalysis,Tabular Playground Series - Feb 2022
5916,88330340,163.0,0.909994478188846,2,7,/muhammedhamzamalik/tps-feb-22-0-98684-score,Tabular Playground Series - Feb 2022
5917,88330340,163.0,0.917875608654184,2,7,/muhammedhamzamalik/tps-feb-22-0-98684-score,Tabular Playground Series - Feb 2022
5918,88330340,163.0,0.9262587219517092,2,7,/muhammedhamzamalik/tps-feb-22-0-98684-score,Tabular Playground Series - Feb 2022
5919,88605834,48.0,0.9887053862757894,19,42,/lisyuan0930/tps-feb-resnet,Tabular Playground Series - Feb 2022
5920,86981055,94.0,0.9643592189147132,7,12,/alyalsamal/bagging-extra-tree,Tabular Playground Series - Feb 2022
5921,88654730,114.0,0.9747502635409868,2,20,/ashaykatrojwar/extra-trees-and-lgbm-with-kfold-cross-validation,Tabular Playground Series - Feb 2022
5922,87283078,118.0,0.9631042618342452,6,19,/atrisaxena/let-s-do-voting-playground-series-feb22,Tabular Playground Series - Feb 2022
5923,87704789,119.0,0.9070327794789418,2,3,/saraswatitiwari/tps-feb-2022,Tabular Playground Series - Feb 2022
5924,88963250,128.0,0.9726419356458008,0,1,/nnjjpp/tabular-playground-feb-2022-extra-trees,Tabular Playground Series - Feb 2022
5925,87309991,151.0,,4,19,/vpallares/when-a-million-trees-is-not-enough,Tabular Playground Series - Feb 2022
5926,87132953,139.0,,0,13,/pelegshilo/tps-feb2022-eda-why-do-we-have-duplicate-data,Tabular Playground Series - Feb 2022
5927,86765153,57.0,,2,14,/kaggleqrdl/quick-estimators-check,Tabular Playground Series - Feb 2022
5928,88155179,64.0,,27,54,/vanguarde/tps-feb22-deep-eda-classifier-submission,Tabular Playground Series - Feb 2022
5929,103894850,103.0,,36,100,/devsubhash/tps-feb-2022-eda-models-extratrees-rf-xgb,Tabular Playground Series - Feb 2022
5930,87647775,135.0,0.9895085588072888,28,46,/dmitryuarov/forest-of-extra-trees-0-9895-up-to-4th-place,Tabular Playground Series - Feb 2022
5931,88050957,196.0,0.9874504291953216,9,19,/ebrahimhaquebhatti/pseudo-labeling,Tabular Playground Series - Feb 2022
5932,86796939,179.0,,3,7,/rrrohit/fastai-starter-baseline,Tabular Playground Series - Feb 2022
5933,87294354,199.0,0.987350032628884,3,10,/nikhilkhetan/pseudo-labelling-tps-feb-2022,Tabular Playground Series - Feb 2022
5934,87720188,173.0,,1,5,/faisalalsrheed/nested-cross-validation-xgboost-gridsearchcv,Tabular Playground Series - Feb 2022
5935,88302795,167.0,0.9858942824155412,0,18,/m1y7k8/tps-feb-2022-eda-classifier-rf-vs-et-bagging,Tabular Playground Series - Feb 2022
5936,87200454,176.0,0.9838863510867928,32,72,/remekkinas/super-learner-ensemble-extree-tuned-lda-umap,Tabular Playground Series - Feb 2022
5937,87200454,176.0,0.9736459013101753,32,72,/remekkinas/super-learner-ensemble-extree-tuned-lda-umap,Tabular Playground Series - Feb 2022
5938,86776285,177.0,,5,13,/mohitsahal/eda-using-shap-with-feature-interaction-feb-2022,Tabular Playground Series - Feb 2022
5939,88625068,198.0,,5,8,/abdulravoofshaik/tpsfeb22-randomforest-cluster-info,Tabular Playground Series - Feb 2022
5940,88678763,193.0,,5,12,/hopeowens/principal-component-bacterial-genetic-analysis,Tabular Playground Series - Feb 2022
5941,89019921,213.0,,12,30,/slythe/tps-feb-22-analysis-of-paper-with-11-models,Tabular Playground Series - Feb 2022
5942,86762361,228.0,,1,6,/felipedutralisboa/catboost-starter,Tabular Playground Series - Feb 2022
5943,87432335,252.0,0.9865970583806034,25,75,/sfktrkl/tps-feb-2022,Tabular Playground Series - Feb 2022
5944,87432335,252.0,0.9862456703980724,25,75,/sfktrkl/tps-feb-2022,Tabular Playground Series - Feb 2022
5945,87432335,252.0,0.9867476532302596,25,75,/sfktrkl/tps-feb-2022,Tabular Playground Series - Feb 2022
5946,87432335,252.0,0.9872998343456654,25,75,/sfktrkl/tps-feb-2022,Tabular Playground Series - Feb 2022
5947,87432335,252.0,0.9870990412127906,25,75,/sfktrkl/tps-feb-2022,Tabular Playground Series - Feb 2022
5948,87931191,221.0,,50,68,/kavehshahhosseini/tps-feb-22-autoencoder-dimensionality-reduction,Tabular Playground Series - Feb 2022
5949,87447662,246.0,,0,7,/cv13j0/a-pycaret-model,Tabular Playground Series - Feb 2022
5950,87799854,301.0,,1,5,/kucsikz/tps2202-tensorflow-optimization-with-optuna-tpu,Tabular Playground Series - Feb 2022
5951,86763796,266.0,,6,15,/munumbutt/extratrees-starter,Tabular Playground Series - Feb 2022
5952,87157057,290.0,0.9868480497966968,15,82,/maxencefzr/tps-feb22-eda-extratrees,Tabular Playground Series - Feb 2022
5953,88866477,270.0,0.9872998343456654,1,2,/egorovalexeyd/tps-2202-0-9878-trees-additional-bias,Tabular Playground Series - Feb 2022
5954,86838279,257.0,,2,16,/wti200/one-vs-rest-approach,Tabular Playground Series - Feb 2022
5955,88048630,245.0,0.9876010240449776,31,63,/adamml/classify-bacteria-species-with-acc-98-tps-feb22,Tabular Playground Series - Feb 2022
5956,87212302,289.0,0.9874002309121028,3,10,/arjunprasadsarkhel/tps-feb-k-best-features,Tabular Playground Series - Feb 2022
5957,88860010,285.0,0.9739972892927062,21,51,/samuelcortinhas/tps-feb-22-model-for-train-test-drift,Tabular Playground Series - Feb 2022
5958,88596020,268.0,0.9867476532302596,0,1,/mahdiislam/tabular-february,Tabular Playground Series - Feb 2022
5959,88596020,268.0,0.987350032628884,0,1,/mahdiislam/tabular-february,Tabular Playground Series - Feb 2022
5960,88596020,268.0,0.9862456703980724,0,1,/mahdiislam/tabular-february,Tabular Playground Series - Feb 2022
5961,88596020,268.0,0.9870990412127906,0,1,/mahdiislam/tabular-february,Tabular Playground Series - Feb 2022
5962,88596020,268.0,0.9859946789819788,0,1,/mahdiislam/tabular-february,Tabular Playground Series - Feb 2022
5963,87761804,269.0,0.9872496360624466,0,6,/mayank00rastogi/tpsf22-extra-trees-classifier-with-optimization,Tabular Playground Series - Feb 2022
5964,87328753,282.0,0.950504492746348,12,22,/marcinstasko/big-data-pipelines-eager-looking-by-dask,Tabular Playground Series - Feb 2022
5965,88120038,253.0,0.9867978515134782,0,2,/jorgeascencion/tps-feb22-kneighborsclassifier-optuna-optimiz,Tabular Playground Series - Feb 2022
5966,88816243,318.0,0.9748004618242057,1,6,/rsizem2/tps-02-22-separating-high-low-resolution-data,Tabular Playground Series - Feb 2022
5967,88816243,318.0,0.977009186285829,1,6,/rsizem2/tps-02-22-separating-high-low-resolution-data,Tabular Playground Series - Feb 2022
5968,87456615,295.0,0.9867476532302596,7,22,/chaudharypriyanshu/febtabular-eda-fast-baseline,Tabular Playground Series - Feb 2022
5969,88215873,309.0,,2,9,/alexandreayari/tps-02-22-extratrees-gcd-memory-opti,Tabular Playground Series - Feb 2022
5970,88031655,329.0,,5,14,/aussie84/classic-pca-for-visual-exploration-modeling,Tabular Playground Series - Feb 2022
5971,114048273,332.0,,5,4,/maulberto3/tps-feb-22-feat-sel-w-gas,Tabular Playground Series - Feb 2022
5972,86893721,340.0,,3,8,/cristianminas/eda-kfold,Tabular Playground Series - Feb 2022
5973,100102292,358.0,,0,4,/edwardakalarrywelch/understanding-ensemble-models,Tabular Playground Series - Feb 2022
5974,87791721,350.0,0.9820792128909192,7,14,/leehomhuang/simple-k-neighbors,Tabular Playground Series - Feb 2022
5975,88811893,434.0,0.9157170824757792,9,26,/mmellinger66/tps-feb-22-eda-lgbm-optuna-cv-oof,Tabular Playground Series - Feb 2022
5976,86776055,390.0,,21,34,/vivek468/3-fast-5-furious-working-with-heavy-datasets,Tabular Playground Series - Feb 2022
5977,87141073,365.0,0.9788665227649216,27,38,/berkkarabilliolu/tpsfeb22-basic-eda-modeling,Tabular Playground Series - Feb 2022
5978,88967352,395.0,0.9787159279152652,5,11,/lszlbebesi/playing-with-bacteria-data,Tabular Playground Series - Feb 2022
5979,86744653,376.0,0.934742231815672,6,31,/odins0n/tps-feb-22-h20-automl,Tabular Playground Series - Feb 2022
5980,86803457,403.0,0.9550725365192512,5,12,/anmolmittalll/tab-feb-22-eda-feature-selection-modelling,Tabular Playground Series - Feb 2022
5981,88546665,386.0,0.9717885648310828,2,5,/sahilzawar/bagging-with-extratree-classification,Tabular Playground Series - Feb 2022
5982,88008215,385.0,,4,8,/byeongjoon/tps-feb-eda-hypotheses-testing-modeling,Tabular Playground Series - Feb 2022
5983,89213065,426.0,,12,17,/samu2505/bacteria-dna-classification,Tabular Playground Series - Feb 2022
5984,91444781,455.0,,3,5,/mohamedayoubchettouh/tps-feb22-distributionblur,Tabular Playground Series - Feb 2022
5985,88668066,422.0,0.8967923297023241,6,12,/docxian/tpg-2022-feb-eda-gbm-starter,Tabular Playground Series - Feb 2022
5986,86995148,416.0,,3,8,/vladmos/catboost-tabular,Tabular Playground Series - Feb 2022
5987,88981095,441.0,,0,0,/blueotter99/tps-feb-extree-knn-nn-lgbm-ensemble,Tabular Playground Series - Feb 2022
5988,87730975,421.0,0.9675719090407108,2,4,/antonellomartiello/tps0222-tensorflow-random-forest,Tabular Playground Series - Feb 2022
5989,86864667,474.0,0.9727925304954572,16,71,/lucamassaron/basic-eda-and-model-to-start,Tabular Playground Series - Feb 2022
5990,88531626,448.0,0.407258671753426,56,74,/kartik2khandelwal/stratified-kfold-with-knn-improved-score,Tabular Playground Series - Feb 2022
5991,86917353,452.0,,3,9,/ifashion/adversarial-analysis-tps-2022-feb-lgbm,Tabular Playground Series - Feb 2022
5992,87535401,464.0,,31,91,/hasanbasriakcay/tps-feb22-eda-ignore-important-cols,Tabular Playground Series - Feb 2022
5993,86904188,463.0,0.9330856884694544,0,5,/rnepal2/tps-feb-22-getting-started-with-lightgbm,Tabular Playground Series - Feb 2022
5994,88980141,453.0,0.970884995733146,0,1,/winsonrong/tps-feb2022-part1,Tabular Playground Series - Feb 2022
5995,88980339,470.0,0.974549470408112,2,5,/andreal314159/tps-feb-2022-bacteria-qualification,Tabular Playground Series - Feb 2022
5996,87580419,497.0,,4,11,/arindamroy23/experiment-explaination-eda-feature-selection,Tabular Playground Series - Feb 2022
5997,88760917,515.0,0.951408061844285,0,5,/sdysch/bacteria-clf-randomforest-with-hyperopt-tuning,Tabular Playground Series - Feb 2022
5998,88580107,496.0,0.9735957030269564,0,3,/michiexile/mvj-sample-solutions,Tabular Playground Series - Feb 2022
5999,87376166,461.0,,28,36,/alexeykolobyanin/tps-feb-knn-with-sklearnex-13x-speedup,Tabular Playground Series - Feb 2022
6000,86977454,511.0,0.8323879323327142,5,12,/venkatkumar001/tps-1-initial-adaboost,Tabular Playground Series - Feb 2022
6001,88427980,513.0,0.9727423322122384,0,2,/paulomarquies/tps-feb-2022-pycaret-and-extra-trees-classifier,Tabular Playground Series - Feb 2022
6002,86736194,522.0,0.9713367802821145,3,8,/yerzhanimanmalik/extratrees-and-randomforest,Tabular Playground Series - Feb 2022
6003,86736194,522.0,0.9706340043170524,3,8,/yerzhanimanmalik/extratrees-and-randomforest,Tabular Playground Series - Feb 2022
6004,86805235,542.0,0.8995532352793535,3,7,/pasuvulasaikiran/lightgbm-basic,Tabular Playground Series - Feb 2022
6005,88395117,551.0,0.940515034385824,1,2,/suharkov/tps-feb-2022-with-xgboost-and-different-metrics,Tabular Playground Series - Feb 2022
6006,86889032,560.0,,20,43,/kalelpark/tps-feb-2022-compare-models-good-idea-ac-96-9,Tabular Playground Series - Feb 2022
6007,97297353,553.0,0.9434265348125094,0,6,/mustafakeser4/xgb-and-lgbm-with-gpu-eda-pca,Tabular Playground Series - Feb 2022
6008,88921104,583.0,0.9686762712715226,2,7,/himanshusirsat/tabular-play-feb-22,Tabular Playground Series - Feb 2022
6009,88464354,597.0,,2,15,/lovroselic/dna-segments-feb-2022-ls-v3,Tabular Playground Series - Feb 2022
6010,88927397,603.0,,8,9,/rocklen/tabular-playground-series-feb-2022,Tabular Playground Series - Feb 2022
6011,86762208,591.0,0.9644596154811506,4,7,/snnclsr/tps-feb-2022-hyperparameter-tuning-with-optuna,Tabular Playground Series - Feb 2022
6012,88680059,612.0,0.7559861452738317,1,3,/bartmaciszewski/support-vector-machines,Tabular Playground Series - Feb 2022
6013,88680059,612.0,0.7559861452738317,1,3,/bartmaciszewski/support-vector-machines,Tabular Playground Series - Feb 2022
6014,88640403,609.0,0.964208624065057,0,4,/kigett/genomic-analysis-of-bacteria,Tabular Playground Series - Feb 2022
6015,88773662,619.0,,3,10,/akshayr009/tabular-playground-series1,Tabular Playground Series - Feb 2022
6016,116849025,622.0,0.9648110034636816,11,15,/p7476762/xg-extree-dl-3-model-prediciton,Tabular Playground Series - Feb 2022
6017,88905409,630.0,,14,17,/dulithajayakodige/simple-ml-model-to-predict-bacteria-type,Tabular Playground Series - Feb 2022
6018,88013396,627.0,0.9062798052306612,6,9,/sophieali/simple-neural-net-model,Tabular Playground Series - Feb 2022
6019,86975884,629.0,0.8949851915064505,4,15,/coenvalk/tps-feb-2022,Tabular Playground Series - Feb 2022
6020,89473582,641.0,,3,11,/edoardoba/classify-bacteria-species-97-accuracy,Tabular Playground Series - Feb 2022
6021,87024711,650.0,0.960343356257216,5,17,/stpeteishii/tps0222-lgbm-predict-proba,Tabular Playground Series - Feb 2022
6022,87150651,636.0,,1,3,/buzzini/tps-feb-22-eda-predictions,Tabular Playground Series - Feb 2022
6023,87870189,621.0,,2,7,/gopalgoyal612002/tps-feb1-knn-for-beginners,Tabular Playground Series - Feb 2022
6024,88895252,649.0,0.8661713769389087,9,14,/imnaho/2022feb-tps,Tabular Playground Series - Feb 2022
6025,88248801,657.0,0.9558255107675316,5,6,/rudragujarathi/tps-feb-2022-bacteria-classification,Tabular Playground Series - Feb 2022
6026,93117779,647.0,,56,101,/kellibelcher/genetic-analysis-of-bacteria-with-pca,Tabular Playground Series - Feb 2022
6027,87713015,663.0,,27,34,/ammarabbasi1040/tps-feb22-eda-modelling-extratrees-97acc,Tabular Playground Series - Feb 2022
6028,88538013,652.0,,1,8,/phanttan/eda-tpsfeb2022,Tabular Playground Series - Feb 2022
6029,87363765,664.0,,2,7,/agpriyanka/simplest-random-forest,Tabular Playground Series - Feb 2022
6030,87880372,682.0,,10,16,/sardorabdirayimov/ipython-beyond-python,Tabular Playground Series - Feb 2022
6031,87320201,1118.0,,1,3,/nitishkumar3099/basic-random-forest-classifier-tps-feb2022,Tabular Playground Series - Feb 2022
6032,87171746,720.0,,9,12,/taranmarley/eda-and-extra-trees-prediction,Tabular Playground Series - Feb 2022
6033,88829145,721.0,0.8493549520606395,7,13,/zhangcheche/a-simple-pytorch-neural-network-2022-tps-2,Tabular Playground Series - Feb 2022
6034,87166672,729.0,0.9422217760152602,6,18,/towhidultonmoy/tps-feb-2022-automl-autogluon,Tabular Playground Series - Feb 2022
6035,142027955,725.0,,0,0,/haozhang607/tabular-playground-series-feb-2022,Tabular Playground Series - Feb 2022
6036,87661323,701.0,0.9424225691481352,0,5,/siaa512/eda-plus-basic-models-comparison,Tabular Playground Series - Feb 2022
6037,87743471,735.0,,19,28,/sahilrajpal121/dimensionality-reduction-viz,Tabular Playground Series - Feb 2022
6038,87657777,749.0,0.8830380001003966,0,3,/mustafamu/tabular-playground-series-feb-2022-cnn,Tabular Playground Series - Feb 2022
6039,87264047,746.0,,0,1,/jdranpariya/tabular-feb-2022,Tabular Playground Series - Feb 2022
6040,88321161,762.0,0.9505546910295668,0,6,/rajnishkumar546/tabular-playgound-feb2022,Tabular Playground Series - Feb 2022
6041,88319439,801.0,,4,5,/peressim/tps-feb-2022-eda,Tabular Playground Series - Feb 2022
6042,88327279,755.0,0.9501531047638172,2,4,/sanskriti17/predict-bacteria-randomforest,Tabular Playground Series - Feb 2022
6043,88940826,811.0,,2,10,/casati8/kaggle-tps-feb2022-fastai,Tabular Playground Series - Feb 2022
6044,87489483,807.0,,0,1,/lordxerxes/emms-tabular-playground-series,Tabular Playground Series - Feb 2022
6045,88930419,803.0,,7,16,/himanshunayal/tps-feb-2022-xgboost-optuna,Tabular Playground Series - Feb 2022
6046,119854549,804.0,,20,35,/arunasivapragasam/tps-feb-2022-random-forest,Tabular Playground Series - Feb 2022
6047,87881550,823.0,0.9442297073440088,0,4,/paveltrusov/tps-feb-2022-in-45-lines-of-code,Tabular Playground Series - Feb 2022
6048,88751463,821.0,,2,3,/dcrowd/xgboost-model-first-comp-keep-improving,Tabular Playground Series - Feb 2022
6049,88208167,815.0,,58,116,/lordozvlad/fast-random-forest-using-scikit-learn-intelex,Tabular Playground Series - Feb 2022
6050,88443200,854.0,0.9408162240851364,5,13,/ranjeetshrivastav/tps-feb-22-lightgbm,Tabular Playground Series - Feb 2022
6051,87459075,865.0,,2,4,/naokisugimura/tps-feb-2022-simple-extratree,Tabular Playground Series - Feb 2022
6052,89030370,882.0,0.906480598363536,0,2,/thomaspagesy/30-tensorflow-2d-convnet-blending,Tabular Playground Series - Feb 2022
6053,91499032,925.0,,0,1,/boopathymsse/tps-feb22-xgboost-with-hyper-parameter-tuning,Tabular Playground Series - Feb 2022
6054,87725149,927.0,0.0954269363987751,1,7,/samir95/image-classification-approach,Tabular Playground Series - Feb 2022
6055,86852591,940.0,0.9006073992269464,0,1,/vladlee/tps-feb-2022-lgbm-baseline,Tabular Playground Series - Feb 2022
6056,86931045,944.0,0.8332413031474324,1,5,/paulreiners/bacteria-stochastic-gradient-descent,Tabular Playground Series - Feb 2022
6057,87023531,951.0,0.8737011194217158,9,16,/ankitkalauni/nnnnnnnnn,Tabular Playground Series - Feb 2022
6058,87894333,968.0,0.9044726670347876,0,3,/tariqchhussain/xgboost-tps-feb-2022-wip,Tabular Playground Series - Feb 2022
6059,86951124,1005.0,,10,17,/raj401/simple-clean-eda-tps-feb,Tabular Playground Series - Feb 2022
6060,86838104,1004.0,0.9058280206816928,1,7,/gavisr/tpsfeb22-lgbm-for-beginners,Tabular Playground Series - Feb 2022
6061,87390990,1029.0,0.9058782189649114,2,7,/tatyy555/tps-feb-2022-bacteria-species-keras-best-tune,Tabular Playground Series - Feb 2022
6062,89366981,1017.0,,0,2,/jiprud/simple-submission-xgb-light-gbm,Tabular Playground Series - Feb 2022
6063,87852755,1033.0,0.902966718538226,0,1,/danielkondo/a-simple-model-for-tabular-pg-feb-22,Tabular Playground Series - Feb 2022
6064,86834350,1025.0,,2,5,/drcapa/tps-feb-2022-starter,Tabular Playground Series - Feb 2022
6065,88260036,1045.0,0.8270167160283118,0,2,/cinciadedadoscomr/lightgbm-classifier-very-simple-and-fast,Tabular Playground Series - Feb 2022
6066,88845507,1057.0,0.8988504593142914,0,2,/sayansh001/bacteria-genetic-eda-modelling-lgbm,Tabular Playground Series - Feb 2022
6067,88535058,1046.0,,0,1,/nilpatil299/notebook4556a45a3d,Tabular Playground Series - Feb 2022
6068,88560025,1068.0,0.8856985091109884,0,2,/rvalieris/tabular-playg-feb2022,Tabular Playground Series - Feb 2022
6069,87679078,1082.0,,0,1,/ggopinathan/feb-tps-2022-eda-pycaret-modeling-simple-start,Tabular Playground Series - Feb 2022
6070,91761186,1090.0,,2,12,/ritvik1909/feature-tokenizer-transformer,Tabular Playground Series - Feb 2022
6071,88005599,1142.0,0.8468450378997038,7,9,/tqrahman/tf-deep-neural-network-w-kfold,Tabular Playground Series - Feb 2022
6072,87910656,1146.0,,8,14,/austinpowers/turn-it-into-a-toon-tps-feb-22,Tabular Playground Series - Feb 2022
6073,88975740,1153.0,0.849103960644546,0,1,/swagician/feb-r-neural-jamboree,Tabular Playground Series - Feb 2022
6074,88856483,1179.0,,2,8,/mahmoudlimam/tabular-feb-22-competition-pca-random-forest,Tabular Playground Series - Feb 2022
6075,87008180,1195.0,,4,9,/sophieb/tps-feb-2022-eda,Tabular Playground Series - Feb 2022
6076,86778141,1209.0,0.6937402740826264,2,8,/tracyporter/code-with-me-tab-feb-22,Tabular Playground Series - Feb 2022
6077,87833949,1220.0,,3,4,/quamarequbal/tabular-playground-series-feb-2022,Tabular Playground Series - Feb 2022
6078,87550978,1226.0,0.3546006726569951,0,1,/karlpetz/first-bacteria-classification-competition-model,Tabular Playground Series - Feb 2022
6079,88912322,1245.0,,0,3,/shivijaiswal/tabular-playground-series,Tabular Playground Series - Feb 2022
6080,87110430,1250.0,,6,12,/khkuggle/easy-and-fast-eda-and-modeling-for-tps-feb-22,Tabular Playground Series - Feb 2022
6081,87023548,7.0,,31,106,/ks2019/happywhale-tfrecords,Happywhale - Whale and Dolphin Identification
6082,87145457,8.0,,1,16,/kwentar/species-classification,Happywhale - Whale and Dolphin Identification
6083,90221760,13.0,0.7507352578337012,26,96,/yamsam/simple-ensemble-of-public-best-kernels,Happywhale - Whale and Dolphin Identification
6084,91929430,19.0,,0,13,/ragnar123/happywhale-tf-records-detic-box-768x768,Happywhale - Whale and Dolphin Identification
6085,87160494,40.0,0.1128053293856402,0,5,/heye0507/happy-whale-eda-baseline,Happywhale - Whale and Dolphin Identification
6086,92619566,26.0,0.7608117443868732,0,0,/shangyuxie/simple-ensemble-of-public-best-kernels-v-2-2-0,Happywhale - Whale and Dolphin Identification
6087,92602284,30.0,,1,7,/deepkim/strange-data,Happywhale - Whale and Dolphin Identification
6088,89531441,29.0,,3,21,/lextoumbourou/happywhale-comprehensive-eda,Happywhale - Whale and Dolphin Identification
6089,89548562,50.0,,18,92,/remekkinas/whales-feature-matching-loftr-kornia,Happywhale - Whale and Dolphin Identification
6090,91793095,61.0,,0,2,/blankaf/happywhale-fb-b7-train-weights-tpu,Happywhale - Whale and Dolphin Identification
6091,88618699,80.0,,0,2,/qi0239/prepare-data-6329,Happywhale - Whale and Dolphin Identification
6092,92108787,70.0,,1,7,/nealart/fastai-baseline-model,Happywhale - Whale and Dolphin Identification
6093,88865810,78.0,0.2863903281519857,19,73,/taindow/pytorch-metric-learning-effnet-arcface,Happywhale - Whale and Dolphin Identification
6094,88117970,75.0,,1,16,/frlemarchand/happywhale-camera-viewpoint-classification,Happywhale - Whale and Dolphin Identification
6095,88219712,95.0,,0,13,/dwchen/fixed-train-set-with-folds,Happywhale - Whale and Dolphin Identification
6096,89274025,86.0,,0,12,/jirkaborovec/whale-dolphin-eda-classify-lit-flash,Happywhale - Whale and Dolphin Identification
6097,87359710,115.0,,0,5,/parksu92/whale-eda,Happywhale - Whale and Dolphin Identification
6098,89188911,117.0,,1,13,/ksork6s4/happywhale-data-visualization,Happywhale - Whale and Dolphin Identification
6099,92752237,153.0,,2,33,/seabutterfly95/ensemble-of-public-and-beluga-fullbody,Happywhale - Whale and Dolphin Identification
6100,91809041,230.0,,4,29,/poverlu/simple-ensemble-of-public-best-kernels-v3,Happywhale - Whale and Dolphin Identification
6101,91924106,222.0,0.7591191709844548,1,12,/djacon/simple-ensemble-of-public-best-kernels-v-2-2-0,Happywhale - Whale and Dolphin Identification
6102,93221615,268.0,0.7895953614606448,0,3,/masterray/ensemble-of-public-and-beluga-fullbody-pro-0-789,Happywhale - Whale and Dolphin Identification
6103,90882769,224.0,0.5010461386627142,1,8,/jimmysmith1009/pytorch-effnet-infer-384-384img-size,Happywhale - Whale and Dolphin Identification
6104,108227389,242.0,,13,28,/cbeaud/happywhale-ensemble-of-public-best-kernels,Happywhale - Whale and Dolphin Identification
6105,91444150,461.0,,1,8,/bryanb/resize-images-using-multiprocessing,Happywhale - Whale and Dolphin Identification
6106,88715667,296.0,0.1135726622255119,42,79,/ammarnassanalhajali/cnn-with-keras-stater,Happywhale - Whale and Dolphin Identification
6107,92035603,308.0,,31,41,/leoooo333/background-remove-tutorial,Happywhale - Whale and Dolphin Identification
6108,89556660,314.0,0.0226350851221317,0,9,/somesh88/whale-inference,Happywhale - Whale and Dolphin Identification
6109,88543242,318.0,,4,22,/knightbearr/python-cheat-sheet-knightbearr,Happywhale - Whale and Dolphin Identification
6110,87397423,475.0,,0,7,/dername/the-boring-model,Happywhale - Whale and Dolphin Identification
6111,88432892,399.0,,29,161,/usharengaraju/tensorflow-tpu-involutionalneuralnetworks,Happywhale - Whale and Dolphin Identification
6112,90058771,407.0,,6,17,/danielwe14/image-analysis-happwhale,Happywhale - Whale and Dolphin Identification
6113,87625299,415.0,0.112691833209968,0,5,/jasonczh/pretrained-model-with-keras,Happywhale - Whale and Dolphin Identification
6114,86766103,422.0,,3,11,/karthickp6/happy-whales-and-dolphins-eda,Happywhale - Whale and Dolphin Identification
6115,88871997,471.0,,3,8,/dqhdqmcttdqx/hw-data-finetune-splits,Happywhale - Whale and Dolphin Identification
6116,88300719,540.0,,11,72,/gpreda/happy-whales-and-dolphins,Happywhale - Whale and Dolphin Identification
6117,91780767,542.0,0.7581519861830732,16,39,,Happywhale - Whale and Dolphin Identification
6118,87040248,571.0,,3,13,/tensorchoko/happywhale-eda-jp-en,Happywhale - Whale and Dolphin Identification
6119,87891495,522.0,0.0921218850234394,2,25,/yerramvarun/happywhale-dbscan-efficientnet-baseline,Happywhale - Whale and Dolphin Identification
6120,91538870,541.0,,1,12,/poissonyzr/build-happy-whales-image-retrieval-from-scratch,Happywhale - Whale and Dolphin Identification
6121,91525968,581.0,,0,11,/phanttan/eda-happywhale,Happywhale - Whale and Dolphin Identification
6122,90692711,599.0,,0,8,/robertturro/happywhale-1st-notebook,Happywhale - Whale and Dolphin Identification
6123,91918266,624.0,,0,5,/kayvanshah/eda-whale-dolphin-identification,Happywhale - Whale and Dolphin Identification
6124,91270562,630.0,,0,5,/swaralipibose/image-feature-extraction,Happywhale - Whale and Dolphin Identification
6125,86778943,750.0,,10,82,/debarshichanda/pytorch-happywhale-siamese-starter,Happywhale - Whale and Dolphin Identification
6126,86964686,754.0,,2,31,/abhranta/starter-eda-aug,Happywhale - Whale and Dolphin Identification
6127,95762593,792.0,,7,32,/lunapandachan/happywhale-eda,Happywhale - Whale and Dolphin Identification
6128,91813518,887.0,,0,7,/rajankumar/visuals-of-happywhale,Happywhale - Whale and Dolphin Identification
6129,91604515,956.0,0.6654527510486061,7,41,/riadalmadani/fastai-baseline-model,Happywhale - Whale and Dolphin Identification
6130,88098935,923.0,,6,15,/sahilchachra/whales-dolphins-eda-insights-analysis,Happywhale - Whale and Dolphin Identification
6131,89891977,981.0,,0,2,/yinqishuo/whales-dolphins-effnet-train-rapids-clusters,Happywhale - Whale and Dolphin Identification
6132,88647276,1001.0,,0,5,/sourabhy/happywhale-eda-arcface-simplified,Happywhale - Whale and Dolphin Identification
6133,89385532,1007.0,,30,108,/sahamed/eda-visualization-augmentation,Happywhale - Whale and Dolphin Identification
6134,87232477,1053.0,,2,8,/tianmin/happy-whale-interactive-playground,Happywhale - Whale and Dolphin Identification
6135,89105523,1082.0,,0,5,/timchang1997/happywhale,Happywhale - Whale and Dolphin Identification
6136,90818698,1119.0,,0,1,/npc0302/v00001,Happywhale - Whale and Dolphin Identification
6137,86884890,1125.0,0.1128053293856402,0,6,/tomato0813/happywhale-id-eda,Happywhale - Whale and Dolphin Identification
6138,86884890,1125.0,0.1128053293856402,0,6,/tomato0813/happywhale-id-eda,Happywhale - Whale and Dolphin Identification
6139,89388642,1131.0,,2,11,/art3mis/220227-happy-whales-yolo-cropping-implementation,Happywhale - Whale and Dolphin Identification
6140,86746651,1132.0,,0,17,/ayuraj/happywhale-eda-ids-to-images-using-w-b-tables,Happywhale - Whale and Dolphin Identification
6141,87434759,1138.0,,0,7,/rhythmcam/make-training-n-folds-csv,Happywhale - Whale and Dolphin Identification
6142,87276899,1140.0,,2,13,/derrickmwiti/simple-convolutional-neural-network,Happywhale - Whale and Dolphin Identification
6143,88109416,1155.0,,3,18,/vsedelnik/happywhale-dataset-image-normalization,Happywhale - Whale and Dolphin Identification
6144,87176295,1165.0,,2,9,/sadivamadaan/fastai-efficientnet-starter,Happywhale - Whale and Dolphin Identification
6145,88711988,1302.0,0.0973945225758697,9,22,/meetnagadia/happywhale-2022-using-cnn,Happywhale - Whale and Dolphin Identification
6146,89195227,1185.0,,2,16,/samir95/species-classification,Happywhale - Whale and Dolphin Identification
6147,88289876,1203.0,0.3458549222797925,2,34,/raininbox/pytorch-train-infer,Happywhale - Whale and Dolphin Identification
6148,90358783,1207.0,,8,15,/meenakshiramaswamy/tf-keras-mobilevit,Happywhale - Whale and Dolphin Identification
6149,87696144,1211.0,,2,8,/kiernanmcguigan/efficient-net-for-species-classification,Happywhale - Whale and Dolphin Identification
6150,88851114,1232.0,,2,10,/syzygyfy/happy-whale-to-hdf5-224x224,Happywhale - Whale and Dolphin Identification
6151,87121196,1363.0,,1,9,/icozma/some-simple-eda,Happywhale - Whale and Dolphin Identification
6152,87313383,1319.0,,0,2,/akhileshdkapse/dataframe-startnotebook,Happywhale - Whale and Dolphin Identification
6153,88623456,1274.0,,0,9,/akshayr009/notebooka51b24fb5b,Happywhale - Whale and Dolphin Identification
6154,88003081,1293.0,,0,14,/divyanshtyagi/happy-whales-identify-the-mammal-species,Happywhale - Whale and Dolphin Identification
6155,86978344,1307.0,0.1137577103380212,0,8,/chiranjeevbit/whale-dolphin-identification-image-data,Happywhale - Whale and Dolphin Identification
6156,87017684,1308.0,,1,6,/nmayank10/is-it-whale-or-dolphin,Happywhale - Whale and Dolphin Identification
6157,90610194,1314.0,,0,4,/rachidrahal/whale-and-dolphin-vgg16-preprocessing,Happywhale - Whale and Dolphin Identification
6158,86765519,1328.0,0.1128053293856402,0,8,/qwertai/notebookfcc0483f51,Happywhale - Whale and Dolphin Identification
6159,86886002,1330.0,0.1128053293856402,0,10,/zzk1box/all-new-individual,Happywhale - Whale and Dolphin Identification
6160,87318271,1337.0,,0,7,/stpeteishii/whale-dolphin-transfer-learning3,Happywhale - Whale and Dolphin Identification
6161,87992140,1387.0,,24,65,/kalelpark/happy-whale-dolphin-eda-with-pytorch-a-z,Happywhale - Whale and Dolphin Identification
6162,92520477,1424.0,,1,5,/pratik1120/happywhale-data-processing,Happywhale - Whale and Dolphin Identification
6163,94584928,1515.0,0.1250012336540835,1,1,/jaykumar2862/happy-whale-competition,Happywhale - Whale and Dolphin Identification
6164,87738372,1441.0,,27,49,/bsridatta/happywhale,Happywhale - Whale and Dolphin Identification
6165,87506785,1433.0,0.0292869479397976,2,29,/drcapa/happywhale-2022-starter,Happywhale - Whale and Dolphin Identification
6166,86792595,1456.0,,0,8,/zwartfreak/whales-dolphins-in-neural-network,Happywhale - Whale and Dolphin Identification
6167,88880140,1485.0,,0,6,/venkatkumar001/vs-starter-simple-flash-efficientb0,Happywhale - Whale and Dolphin Identification
6168,89585721,1487.0,,0,1,/chasset/first-dive-in-data-happywhale,Happywhale - Whale and Dolphin Identification
6169,88876349,1522.0,,0,3,/kanosawa/and-classification,Happywhale - Whale and Dolphin Identification
6170,87204221,1540.0,0.0069059955588453,0,19,/palash97/happywhale-pytorch-vgg16-starter,Happywhale - Whale and Dolphin Identification
6171,90495834,1550.0,,0,1,/williamlin8/happywhale,Happywhale - Whale and Dolphin Identification
6172,87068769,1555.0,,0,10,/mohitsahal/tf-similarity-happywhale-whale-and-dolphin,Happywhale - Whale and Dolphin Identification
6173,87069729,1570.0,3.700962250185048e-05,0,8,/umbertofasci/happy-whales-and-dolphins-starter,Happywhale - Whale and Dolphin Identification
6174,87030725,1572.0,,1,9,/manatoyaguchi/simple-eda-japanese-version,Happywhale - Whale and Dolphin Identification
6175,91369240,1583.0,,0,1,/myncoder0908/notebook4d33cf4e2e,Happywhale - Whale and Dolphin Identification
6176,86824231,20.0,0.5922463017998464,7,115,/theoviel/evaluation-metric-folds-baseline,NBME - Score Clinical Patient Notes
6177,91393705,13.0,,2,40,/yufuin/nbme-japanese,NBME - Score Clinical Patient Notes
6178,91775508,64.0,0.8850499295187378,0,0,/aman1391/ak-deberta-xlarge-inf,NBME - Score Clinical Patient Notes
6179,93348092,39.0,,12,57,/anyai28/fast-inference-by-padding-optimization,NBME - Score Clinical Patient Notes
6180,94661225,11.0,0.8906826862209458,0,11,/zacchaeus/nbme-infer-blend,NBME - Score Clinical Patient Notes
6181,94164167,50.0,,6,55,/leemop/version-4-simply-understand-competition-itself,NBME - Score Clinical Patient Notes
6182,88286498,78.0,,9,79,/wuyhbb/get-more-training-data-with-exact-match,NBME - Score Clinical Patient Notes
6183,92031966,141.0,,0,10,/gauravbrills/helpers-for-the-ride-folds,NBME - Score Clinical Patient Notes
6184,91262425,48.0,0.8691882360996988,11,60,/junkoda/be-aware-of-white-space-deberta-roberta,NBME - Score Clinical Patient Notes
6185,93847858,103.0,0.0012639455323738,0,0,/liampay/nbme-infer,NBME - Score Clinical Patient Notes
6186,92129053,144.0,,0,4,/yshiml/nbme-eda-for-beginners,NBME - Score Clinical Patient Notes
6187,87962381,105.0,,0,0,/szymonog/nbme-dataexploration,NBME - Score Clinical Patient Notes
6188,91362222,126.0,,0,0,/jdoesv/pn-spellcheck,NBME - Score Clinical Patient Notes
6189,91129866,132.0,,6,46,/maximegatineau/nbme-post-processing-and-ensemble-tools,NBME - Score Clinical Patient Notes
6190,88479867,250.0,,1,6,/librauee/get-token,NBME - Score Clinical Patient Notes
6191,92367290,242.0,,0,25,/apap950419/relative-positions-of-annotations-within-notes,NBME - Score Clinical Patient Notes
6192,88200086,659.0,,0,11,/joeonaka/nbme-data-overview-jp,NBME - Score Clinical Patient Notes
6193,92193300,136.0,,0,2,/nqbinh17/roberta-error-analysis,NBME - Score Clinical Patient Notes
6194,87542390,193.0,0.8769542122092145,5,29,/manojprabhaakr/nbme-deberta-large-baseline-inference,NBME - Score Clinical Patient Notes
6195,94695968,176.0,0.8867172071096389,0,3,/n1kkqt/ensemble,NBME - Score Clinical Patient Notes
6196,87154543,261.0,,3,6,/arunamenon/score-patient-notes-eda-ner-model,NBME - Score Clinical Patient Notes
6197,90587593,531.0,,0,0,/ryryrymyg/ryryry-nbme-detailed-eda,NBME - Score Clinical Patient Notes
6198,88920578,706.0,0.8824789846711719,2,14,/guanghan/deberta-v3-large-baseline-deepshare,NBME - Score Clinical Patient Notes
6199,90401458,227.0,,7,54,/masato114/nbme-technical-terms-among-tokenizers,NBME - Score Clinical Patient Notes
6200,95778292,199.0,,2,20,/lunapandachan/nbme-eda-pseudo-label,NBME - Score Clinical Patient Notes
6201,89631477,615.0,0.8817054515310265,10,64,/thanhns/deberta-v3-large-0-883-lb,NBME - Score Clinical Patient Notes
6202,92648675,265.0,,13,28,/ammarnassanalhajali/nbme-fine-tuning-deberta-tensorflow,NBME - Score Clinical Patient Notes
6203,90138804,669.0,,20,73,/utcarshagrawal/nbme-complete-eda,NBME - Score Clinical Patient Notes
6204,89672018,381.0,,0,0,/senaerdogan/qa-deberta-v0,NBME - Score Clinical Patient Notes
6205,92726465,405.0,,0,1,/sakamotoyuto/notebookf3f6ba8fa5,NBME - Score Clinical Patient Notes
6206,87869715,408.0,,11,36,/iamsdt/pytorch-bert-baseline-nbme,NBME - Score Clinical Patient Notes
6207,87725352,726.0,,10,11,/somesh88/nbme-clinical-patients-eda,NBME - Score Clinical Patient Notes
6208,91123546,856.0,,1,5,/emircanerol/keyword-extraction,NBME - Score Clinical Patient Notes
6209,90164900,920.0,,8,18,/kei96kag/nbme-momorandum-bert-study-by-a-beginner,NBME - Score Clinical Patient Notes
6210,87931234,779.0,,2,5,/crischir/mockup-ner-nbme-poc,NBME - Score Clinical Patient Notes
6211,87397630,969.0,,49,263,/odins0n/nbme-detailed-eda,NBME - Score Clinical Patient Notes
6212,88361475,1009.0,,0,4,/arvinddevarkonda/bert-nbme-inference-3,NBME - Score Clinical Patient Notes
6213,86855549,1007.0,,7,47,/tchaye59/nbme-tensorflow-bert-baseline,NBME - Score Clinical Patient Notes
6214,92721557,1008.0,,0,7,/raghavendrakotala/problem-understanding-and-data-analysis,NBME - Score Clinical Patient Notes
6215,87603042,1069.0,0.8614629878984879,0,6,/anerishingde/nbme-deberta-base-baseline-inference,NBME - Score Clinical Patient Notes
6216,93911775,1134.0,,0,0,/nestorteodorochavez/nbme-deberta-infer-kn95,NBME - Score Clinical Patient Notes
6217,93290738,1144.0,0.8582967515364354,0,1,/arunaabhpant/nbme-deberta-base-baseline-inference,NBME - Score Clinical Patient Notes
6218,90089329,1158.0,,0,0,/tejasgokulbaraskar/notebook30be1d9f7c,NBME - Score Clinical Patient Notes
6219,87108127,1166.0,,3,12,/samarthagarwal23/understanding-data-creation-multi-span,NBME - Score Clinical Patient Notes
6220,90159317,1177.0,,0,1,/narendra/nbme-hight-level-eda,NBME - Score Clinical Patient Notes
6221,91453021,1199.0,0.8311785566726346,1,7,/starlitlolith/patient-notes,NBME - Score Clinical Patient Notes
6222,91453021,1199.0,0.8311785566726346,1,7,/starlitlolith/patient-notes,NBME - Score Clinical Patient Notes
6223,87094247,1232.0,,0,6,/kaushaltalapady/nbme-eda-and-starter,NBME - Score Clinical Patient Notes
6224,87066810,1245.0,,0,4,/sagniksanyal/scored-patient-notes-using-scapy,NBME - Score Clinical Patient Notes
6225,88926637,1262.0,0.8099186023426642,16,41,/jillanisofttech/nbme-score-clinical-patient-notes,NBME - Score Clinical Patient Notes
6226,90427726,1278.0,,0,0,/progpug314/bio-bert-spacy-data-preparation-and-training,NBME - Score Clinical Patient Notes
6227,88285867,1276.0,,1,2,/vedantj/eda-nbme-score-clinical-patient-notes,NBME - Score Clinical Patient Notes
6228,88166658,1290.0,0.0,0,1,/awaldeep/first-look-eda-visualizations,NBME - Score Clinical Patient Notes
6229,89473544,1336.0,,10,33,/gazu468/nbme-details-eda,NBME - Score Clinical Patient Notes
6230,86866348,1324.0,,5,20,/swaralipibose/the-eda-you-need,NBME - Score Clinical Patient Notes
6231,94395606,1355.0,0.6327074395428924,0,0,/michelbrabants/patient-notes-8a-10g,NBME - Score Clinical Patient Notes
6232,88755863,1361.0,,6,47,/drcapa/nbme-starter,NBME - Score Clinical Patient Notes
6233,86824404,1363.0,,0,7,/yekahaaagayeham/nbme-quick-eda-sentiment-analysis,NBME - Score Clinical Patient Notes
6234,93115240,1389.0,,0,2,/henriqueabpassos/nbme-creating-vocabulary,NBME - Score Clinical Patient Notes
6235,88905111,1387.0,,8,41,/zahaviguy/eda-what-is-the-medical-meaning-of-nbme-features,NBME - Score Clinical Patient Notes
6236,89745126,1388.0,,10,17,/okanzkaya/detailed-eda-with-pie-charts-and-scatter-plots,NBME - Score Clinical Patient Notes
6237,93644855,1413.0,0.5017511432731886,0,0,/llnovall/nbme-submission-7,NBME - Score Clinical Patient Notes
6238,88110061,1433.0,,0,0,/yeayates21/yet-another-nbme-eda-notebook,NBME - Score Clinical Patient Notes
6239,87815088,1460.0,0.0,2,7,/bestesakar/nbme-score-clinical-patient-notes-eda,NBME - Score Clinical Patient Notes
6240,94950033,1.0,0.9984177999762948,5,10,/szeyeung/football-prediction-by-xgboost,Football Match Probability Prediction
6241,90858287,67.0,,0,8,/nikolayluzhynski/fill-na-values-with-analysis,Football Match Probability Prediction
6242,94998988,3.0,0.9949826368743578,0,4,/alexandreurwald/2nd-place-solution-football-prob-prediction,Football Match Probability Prediction
6243,91054691,2.0,,8,21,/seraquevence/top-5-football-prob-prediction-lstm-v01,Football Match Probability Prediction
6244,94713188,4.0,0.9956860199234192,3,0,/tangtunyu/fork-of-football-prob-lstm-v03,Football Match Probability Prediction
6245,94758822,6.0,0.9965366152188724,3,7,/youneseloiarm/football-prob-prediction-lstm-002,Football Match Probability Prediction
6246,95014534,8.0,,0,3,/hamzaouammou/top-7-football-match-probability-prediction,Football Match Probability Prediction
6247,94994080,9.0,0.9960936039877633,1,1,/claraljm/footballprediction-v3,Football Match Probability Prediction
6248,94994080,9.0,0.9960936039877633,1,1,/claraljm/footballprediction-v3,Football Match Probability Prediction
6249,92789631,24.0,1.0528785808095749,14,7,/curiosityquotient/investigation-into-rating-feature-octosport,Football Match Probability Prediction
6250,92620287,60.0,1.0272283115654322,0,8,/uzdavinys/xg-expected-goals-with-simple-sklearn-models,Football Match Probability Prediction
6251,93728157,66.0,1.0034006296003817,0,2,/tarique7/simple-lightgbm-with-aggregated-features,Football Match Probability Prediction
6252,90036585,80.0,1.0052340305608485,3,7,/ravi07bec/lstm-and-feature-engineering-top8,Football Match Probability Prediction
6253,87897863,94.0,1.0059884453036343,18,44,/igorkf/football-match-probability-prediction-lstm-starter,Football Match Probability Prediction
6254,93357504,81.0,,2,8,/aboriginal3153/football-match-simple-implementation-lightgbm,Football Match Probability Prediction
6255,88418565,140.0,,1,16,/henriqueweber/football-results-prediction,Football Match Probability Prediction
6256,95761530,149.0,,11,37,/shariful07/football-match-probability-prediction,Football Match Probability Prediction
6257,91773843,176.0,1.019313932348394,0,1,/arjunjanamatti/notebook931e348ab2,Football Match Probability Prediction
6258,90426387,152.0,1.0134015261053642,2,8,/purvansharora/football-probability-prediction,Football Match Probability Prediction
6259,90525906,145.0,,2,19,/anandaramg/football-match-target-prediction-dtreeviz,Football Match Probability Prediction
6260,91115790,250.0,,7,8,/joanponsv/data-leakage,Football Match Probability Prediction
6261,89686142,355.0,4.800071356453739,0,0,/srijita97/football-eda-and-model,Football Match Probability Prediction
6262,92490176,364.0,,0,3,/olalekandamola/footmatch-prediction-with-logisticregression,Football Match Probability Prediction
6263,118194982,1.0,,0,0,/senkin13/hm-create-dataset-samples,H&M Personalized Fashion Recommendations
6264,87941914,2.0,,9,82,/paweljankiewicz/hm-create-dataset-samples,H&M Personalized Fashion Recommendations
6265,89608394,6.0,0.0231245422442074,14,131,/titericz/h-m-ensembling-how-to,H&M Personalized Fashion Recommendations
6266,92289362,23.0,,18,67,/negoto/h-m-best-selling-items-catalog-like-eda,H&M Personalized Fashion Recommendations
6267,95238782,22.0,,1,25,/iwatatakuya/22nd-place-lgbm-model-single-train,H&M Personalized Fashion Recommendations
6268,91891582,47.0,,3,19,/guoyonfan/improved-h-m-pure-pytorch-baseline,H&M Personalized Fashion Recommendations
6269,92709689,54.0,0.02321694883625,1,4,/qianyetang/h-m-ensembling-with-lstm-be7226,H&M Personalized Fashion Recommendations
6270,89038200,45.0,0.0217291712642,2,22,/tarique7/hnm-exponential-decay-with-alternate-items,H&M Personalized Fashion Recommendations
6271,87582086,52.0,,0,13,/jacob34/popular-benchmark-in-29-lines-of-code,H&M Personalized Fashion Recommendations
6272,91503425,63.0,,0,6,/hanejiyuto/validate-for-astrung-insight,H&M Personalized Fashion Recommendations
6273,94874998,98.0,0.024090390305072,0,6,/algerwang/lb-0-0240-h-m-ensemble-magic-multi-blend,H&M Personalized Fashion Recommendations
6274,92523365,116.0,,0,6,/hjimbean/annotation-public-notebooks-for-the-beginner,H&M Personalized Fashion Recommendations
6275,94216657,137.0,0.0238413580250014,1,8,/nealhams/lb-0-0238-h-m-ensembling-how-to-get-bronze,H&M Personalized Fashion Recommendations
6276,94216657,137.0,0.0238413580250014,1,8,/nealhams/lb-0-0238-h-m-ensembling-how-to-get-bronze,H&M Personalized Fashion Recommendations
6277,94216657,137.0,0.0238413580250014,1,8,/nealhams/lb-0-0238-h-m-ensembling-how-to-get-bronze,H&M Personalized Fashion Recommendations
6278,94216657,137.0,0.0238413580250014,1,8,/nealhams/lb-0-0238-h-m-ensembling-how-to-get-bronze,H&M Personalized Fashion Recommendations
6279,94216657,137.0,0.0238413580250014,1,8,/nealhams/lb-0-0238-h-m-ensembling-how-to-get-bronze,H&M Personalized Fashion Recommendations
6280,88117749,134.0,,12,200,/cdeotte/customers-who-bought-this-frequently-buy-this,H&M Personalized Fashion Recommendations
6281,95066146,159.0,,0,1,/ktakita/h-m-ensembling-weightoptimization,H&M Personalized Fashion Recommendations
6282,88823301,153.0,0.0216380107424863,4,120,/mayukh18/time-decaying-popularity-benchmark-0-0216,H&M Personalized Fashion Recommendations
6283,91599582,177.0,,0,10,/igjit1/my-first-h-m-submission-with-r,H&M Personalized Fashion Recommendations
6284,95380102,200.0,0.0210422517712366,1,1,/prashants2403/radek-s-lgbmranker-starter-pack,H&M Personalized Fashion Recommendations
6285,93163345,221.0,,0,12,/marcogorelli/radek-s-lgbmranker-starter-pack-warmup,H&M Personalized Fashion Recommendations
6286,87904951,302.0,,6,9,/hiroshisakiyama/recommending-top-12-articles,H&M Personalized Fashion Recommendations
6287,94745830,230.0,0.0223533305987611,1,0,/zinmurata/h-m-011-v4svd,H&M Personalized Fashion Recommendations
6288,89757426,504.0,,0,2,/gbalachandhiran/eda-classes-of-rich,H&M Personalized Fashion Recommendations
6289,94291841,245.0,,0,1,/derposoft/hm-recbole-model,H&M Personalized Fashion Recommendations
6290,94207398,256.0,0.0238413580250014,6,66,/chaudhariharsh/lb-0-0238-h-m-ensembling-how-to-get-bronze,H&M Personalized Fashion Recommendations
6291,117329270,444.0,,0,0,/akshitkeoliya/lb-0-0236-ensemble-gives-you-bronze-medal,H&M Personalized Fashion Recommendations
6292,87564381,296.0,0.0080891626467894,0,7,/joelqv/h-m-exploration-baseline,H&M Personalized Fashion Recommendations
6293,95180903,258.0,0.0240578539424689,0,3,/blankaf/h-m-fashion-ensemble-v3-best,H&M Personalized Fashion Recommendations
6294,91496388,277.0,,0,2,/ynmr0123/eda-correlation-between-num-of-sales-and-price,H&M Personalized Fashion Recommendations
6295,95268826,440.0,,0,1,/ashwinm500/hm-final,H&M Personalized Fashion Recommendations
6296,92086133,327.0,0.0235423527122629,6,38,/baekseungyun/lb-0-0235-ensemble-gives-you-bronze-medal,H&M Personalized Fashion Recommendations
6297,88448800,331.0,,4,10,/deepakkaura/h-m-insightful-plots-and-prediction,H&M Personalized Fashion Recommendations
6298,90640471,1082.0,,19,75,/astrung/recbole-lstm-sequential-for-recomendation-tutorial,H&M Personalized Fashion Recommendations
6299,89243525,1243.0,,0,4,/rickykonwar/h-m-exploratorydataanalysis,H&M Personalized Fashion Recommendations
6300,90250954,363.0,,0,0,/kentawatanabetotosya/h-m-eda,H&M Personalized Fashion Recommendations
6301,96482712,386.0,,0,0,/splav12341/lgbmranker,H&M Personalized Fashion Recommendations
6302,89775976,428.0,,0,4,/pyy0715/let-s-predict-the-articles-with-the-will-be-sold,H&M Personalized Fashion Recommendations
6303,88273029,322.0,,0,0,/jasonbian/h-m-personalized-fashion-model-1,H&M Personalized Fashion Recommendations
6304,87491604,228.0,,0,8,/takaito/h-m-topic-model-tutorial,H&M Personalized Fashion Recommendations
6305,90561351,489.0,0.0198761642351771,2,9,/yangranran/lb0-0198-h-m-pure-pytorch-baseline-just-add-bn,H&M Personalized Fashion Recommendations
6306,88877447,312.0,0.0225397154713421,10,119,/byfone/h-m-trending-products-weekly,H&M Personalized Fashion Recommendations
6307,87530618,536.0,,1,15,/tensorchoko/h-m-personalized-eda-jp-en,H&M Personalized Fashion Recommendations
6308,94773852,528.0,,30,46,/lorenzopagliaro01/h-m-ranker-pyspark-lgbmranker,H&M Personalized Fashion Recommendations
6309,93465866,570.0,,0,1,/danielarmel/notebookfirstrl,H&M Personalized Fashion Recommendations
6310,94425733,613.0,,4,11,/vincentbrunner/h-m-image-embeddings,H&M Personalized Fashion Recommendations
6311,87686672,638.0,,0,3,/masaponto/h-and-m-split-dataset-by-year,H&M Personalized Fashion Recommendations
6312,87755240,648.0,,26,201,/gpreda/h-m-eda-and-prediction,H&M Personalized Fashion Recommendations
6313,90314536,670.0,,0,0,/zhaoxf7/ctr-model-gbdt-lr,H&M Personalized Fashion Recommendations
6314,88280315,462.0,,0,19,/takanobu0210/h-m-customer-only-women,H&M Personalized Fashion Recommendations
6315,87380267,552.0,0.0184629233036635,1,28,/hengzheng/time-is-our-best-friend,H&M Personalized Fashion Recommendations
6316,92079410,728.0,,0,26,/hirotakanogami/h-m-eda-customer-clustering-by-kmeans,H&M Personalized Fashion Recommendations
6317,91367877,748.0,0.0234393372439581,1,21,/jaloeffe92/h-m-ensembling-lb-0-0234,H&M Personalized Fashion Recommendations
6318,92251988,804.0,,0,3,/devanshchowdhury/hm-eda-2,H&M Personalized Fashion Recommendations
6319,88638255,815.0,0.0052549999267681,0,0,/nozarchos/grouped-recommendation,H&M Personalized Fashion Recommendations
6320,88928295,838.0,,10,67,/wti200/cold-start,H&M Personalized Fashion Recommendations
6321,89351919,848.0,,0,1,/hechtjp/eda-based-on-timeseries,H&M Personalized Fashion Recommendations
6322,91269347,851.0,0.021288328263016,11,52,/ebn7amdi/trending,H&M Personalized Fashion Recommendations
6323,93863972,876.0,,0,5,/akshatpathak/h-m-recommendation,H&M Personalized Fashion Recommendations
6324,88503939,916.0,0.0200716224814954,0,13,/mdjafrilalamshihab/h-m-magic-of-eda-awesome-score,H&M Personalized Fashion Recommendations
6325,92752088,764.0,,0,3,/whutglaucous/funksvd-solution,H&M Personalized Fashion Recommendations
6326,92771885,989.0,,0,4,/yutaimsk/understanding-the-evaluation-metric,H&M Personalized Fashion Recommendations
6327,88330534,1075.0,,0,12,,H&M Personalized Fashion Recommendations
6328,90672392,1076.0,0.0231837117611354,11,52,/atulverma/h-m-ensembling-with-lstm,H&M Personalized Fashion Recommendations
6329,88062408,1094.0,,13,83,/lichtlab/h-m-data-deep-dive-chap-1-understand-article,H&M Personalized Fashion Recommendations
6330,88735445,1107.0,0.0036160659870615,0,3,/shigeeeru/add-gender-feature,H&M Personalized Fashion Recommendations
6331,87478853,1108.0,0.0064795574010347,4,52,/abhilashawasthi/not-so-fancy-but-fast-benchmark,H&M Personalized Fashion Recommendations
6332,88860524,1114.0,,89,662,/vanguarde/h-m-eda-first-look,H&M Personalized Fashion Recommendations
6333,97487203,1124.0,,0,5,/mdbodrulalam/h-m-personalized-fashion-recommendations,H&M Personalized Fashion Recommendations
6334,87969312,1050.0,,2,5,/oberfink/content-based-image-filtering-for-recommendation,H&M Personalized Fashion Recommendations
6335,91590075,1145.0,,0,4,/dnyaneshwalwadkar/pyspark-eda-for-h-m-recommendations-using,H&M Personalized Fashion Recommendations
6336,88037257,1147.0,,5,30,/shubhamsindal0098/h-m-data-visualization,H&M Personalized Fashion Recommendations
6337,91006830,1222.0,0.0191163911604619,23,156,/aerdem4/h-m-pure-pytorch-baseline,H&M Personalized Fashion Recommendations
6338,95762835,1379.0,,6,70,/lunapandachan/h-m-eda,H&M Personalized Fashion Recommendations
6339,90622346,1244.0,,0,3,/markuslill/h-m-data-preparation,H&M Personalized Fashion Recommendations
6340,89429873,1245.0,0.022619389519463,1,19,/yukou00takahashi/h-m-0-0226-faster-version,H&M Personalized Fashion Recommendations
6341,89429873,1245.0,0.022619389519463,1,19,/yukou00takahashi/h-m-0-0226-faster-version,H&M Personalized Fashion Recommendations
6342,87463161,1279.0,,2,12,/tianmin/data-exploration-of-h-m-product-recommendation,H&M Personalized Fashion Recommendations
6343,93399217,1246.0,,1,4,/chenyubang/hm-recommend-items-always-purchased-after,H&M Personalized Fashion Recommendations
6344,95127775,1282.0,,0,11,/daisukenagao/0-0226-h-m-eda-customer-clustering-by-kmeans,H&M Personalized Fashion Recommendations
6345,90685944,1441.0,,0,6,/kaicho0504/projection-nlp-features,H&M Personalized Fashion Recommendations
6346,97577862,1193.0,,0,0,/xuzicang/customers-who-bought-this-frequently-buy-th-2fa14e,H&M Personalized Fashion Recommendations
6347,89368794,1306.0,,4,15,/rayanaay/h-m-resnet18-encoding-within-your-reach,H&M Personalized Fashion Recommendations
6348,88647535,1321.0,,0,0,/rashmikagamage/eda-v1,H&M Personalized Fashion Recommendations
6349,88388467,1322.0,,0,5,/lightening3rd/eda-of-customers-and-articles,H&M Personalized Fashion Recommendations
6350,88531360,1421.0,,0,5,/shionhonda/h-m-overview-of-tabular-part,H&M Personalized Fashion Recommendations
6351,100891713,1359.0,,0,7,/emphymachine/eda-practice-01-h-m-trending-analysis,H&M Personalized Fashion Recommendations
6352,94351818,1495.0,,1,0,/srinivassateesh/recommend-customer-s-most-expensive-lb-0072,H&M Personalized Fashion Recommendations
6353,89818297,1614.0,,0,3,/kavyagowdala/h-m-data-analysis,H&M Personalized Fashion Recommendations
6354,97230826,1669.0,,2,13,/sanjaylalwani/h-msolution,H&M Personalized Fashion Recommendations
6355,87274472,1510.0,,3,37,/odins0n/h-m-image-resizer-dataset-256x256,H&M Personalized Fashion Recommendations
6356,88496911,1561.0,,0,5,/melodyyiphoiching/h-m-recommendations,H&M Personalized Fashion Recommendations
6357,89294296,1642.0,,0,6,/ikerhonorato/h-m-collaborative-np,H&M Personalized Fashion Recommendations
6358,87376007,1622.0,,6,20,/tomooinubushi/folk-of-time-is-our-best-friend,H&M Personalized Fashion Recommendations
6359,90256126,1699.0,,0,0,/jashanjotsinghbindra/h-m-101903159-datascienceass2,H&M Personalized Fashion Recommendations
6360,89206650,1708.0,,1,5,/rudiboiii/paired-items-by-sex-0-0212,H&M Personalized Fashion Recommendations
6361,88295392,1692.0,,7,21,/aussie84/product-profiling-and-price-trend-analysis,H&M Personalized Fashion Recommendations
6362,91358519,1732.0,0.0207005077136607,2,14,/ceshine/h-m-recently-purchased-item-baseline,H&M Personalized Fashion Recommendations
6363,90218259,1749.0,,0,2,/beezus666/eda-basics,H&M Personalized Fashion Recommendations
6364,90520841,1814.0,,0,1,/tea0925ds/dtale-eda,H&M Personalized Fashion Recommendations
6365,87298478,1832.0,,0,7,/derrickmwiti/using-fbprophet-to-forecast-the-total-price,H&M Personalized Fashion Recommendations
6366,90505716,1809.0,,0,12,/junkoda/article-id-and-release-date,H&M Personalized Fashion Recommendations
6367,87503716,1890.0,0.0200716224814954,4,30,/jillanisofttech/h-m-personalized-fashion-recommendation,H&M Personalized Fashion Recommendations
6368,87567977,1895.0,,5,24,/chiranjeevbit/h-m-personalized-recommendation-eda-wordcloud,H&M Personalized Fashion Recommendations
6369,95647308,1916.0,,0,0,/harshitvish/ds-eval1,H&M Personalized Fashion Recommendations
6370,88557717,1970.0,0.0195849030940009,10,43,/maricinnamon/h-m-fashion-eda-predictions,H&M Personalized Fashion Recommendations
6371,91091850,1983.0,0.0195849030940009,0,4,/nmayank10/h-m-personalized-fashion-recommendations,H&M Personalized Fashion Recommendations
6372,96696044,1995.0,,0,0,/calsonnetshikulwe/fork-of-final-1,H&M Personalized Fashion Recommendations
6373,87794826,1996.0,0.0191959852079324,2,7,/leejunseok97/h-m-personalize-fashion-recommendation,H&M Personalized Fashion Recommendations
6374,87470890,2010.0,0.0178696952223265,6,36,/edwardcrookenden/eda-co-occurence-baseline-0-017,H&M Personalized Fashion Recommendations
6375,88092308,2044.0,0.018364099888576,0,2,/nikhilgulwade/h-m-recommendations-implicit-als-with-gpu-0-018,H&M Personalized Fashion Recommendations
6376,88589384,2039.0,,0,16,/george86/calculate-map-12-fast-faster-fastest,H&M Personalized Fashion Recommendations
6377,94427066,2114.0,0.0141232329917478,15,51,/viji1609/h-m-basic-retrieval-model-tf-recommender,H&M Personalized Fashion Recommendations
6378,95178695,2095.0,,0,0,/namanoberoi/grouping-users-and-items-basic-approach,H&M Personalized Fashion Recommendations
6379,89284763,2085.0,,0,0,/noahjadallah/final-notebook,H&M Personalized Fashion Recommendations
6380,87628252,2104.0,,8,10,/sravanneeli/h-m-eda,H&M Personalized Fashion Recommendations
6381,87520628,2130.0,0.0140591416537197,1,7,/anerishingde/h-m-implicit-als-model-0-013,H&M Personalized Fashion Recommendations
6382,92794492,2129.0,,3,9,/harsh2040/h-m-with-ploty-express,H&M Personalized Fashion Recommendations
6383,91410940,2141.0,,8,41,/yshiml/h-m-eda-for-beginners,H&M Personalized Fashion Recommendations
6384,93702403,2147.0,0.0124087936563373,0,5,/peterpetrov826/fork-of-using-recbole,H&M Personalized Fashion Recommendations
6385,93272226,2176.0,0.012711912929893,0,1,/dariussingh/h-m-recommendation-system-v1,H&M Personalized Fashion Recommendations
6386,89104005,2192.0,,7,43,/susnato/h-m-lightfm,H&M Personalized Fashion Recommendations
6387,93968783,2202.0,,0,0,/windownapat/hm-eda,H&M Personalized Fashion Recommendations
6388,140648476,2205.0,,0,3,/inapark/230822,H&M Personalized Fashion Recommendations
6389,91256982,2231.0,,0,0,/uchiiyusaku/h-m-eda,H&M Personalized Fashion Recommendations
6390,91562978,2251.0,,0,1,/andreiflorea04/h-m-eda,H&M Personalized Fashion Recommendations
6391,90369732,2253.0,0.0078374038003691,32,87,/junjitakeshima/h-m-easy-grouping-by-sex-attribute-age-en-jp,H&M Personalized Fashion Recommendations
6392,88131414,2283.0,0.0075895330543628,2,9,/growbigger/matrix-recommender-als,H&M Personalized Fashion Recommendations
6393,94848473,2262.0,,0,0,/tomaszporzycki/h-m-recommendation-with-seasonality,H&M Personalized Fashion Recommendations
6394,91218894,2322.0,,2,11,/pmanresa6/simple-baseline-with-local-validation-template,H&M Personalized Fashion Recommendations
6395,95793585,2323.0,,0,2,/tbierhance/basic-data-prep-memory-performance-saver,H&M Personalized Fashion Recommendations
6396,87309035,2333.0,,9,22,/hamditarek/h-m-fashion-recommendations,H&M Personalized Fashion Recommendations
6397,94946276,2274.0,0.0070173098988826,0,0,/suneeth84/h-m-analytics-rfm-item-based-recommendation,H&M Personalized Fashion Recommendations
6398,89286712,2355.0,,0,9,/luisrodri97/item-based-collaborative-filtering,H&M Personalized Fashion Recommendations
6399,90965162,2358.0,0.0050567811122029,0,6,/abhishekraikaushik/h-and-m,H&M Personalized Fashion Recommendations
6400,90825254,2383.0,,0,6,/bell2psy/h-m-prediction-eda-version0-1,H&M Personalized Fashion Recommendations
6401,88891305,2354.0,,0,0,/yahelnachum/h-m-eda-mine,H&M Personalized Fashion Recommendations
6402,93664814,2425.0,,2,7,/akashbiswas92/tensorflow-recommenders,H&M Personalized Fashion Recommendations
6403,90995875,2406.0,,0,4,/maharanasaroj/h-m-python-simple-eda,H&M Personalized Fashion Recommendations
6404,88665433,2411.0,,18,34,/bipinkapri/h-m-data-exploration-plots-insights,H&M Personalized Fashion Recommendations
6405,96833261,2429.0,,0,1,/craving1030/r-version-22nd-place-lgbm-model-single-train,H&M Personalized Fashion Recommendations
6406,93309549,2469.0,,0,0,/narendra/transaction-eda,H&M Personalized Fashion Recommendations
6407,89543218,2465.0,,3,3,/johnnync13/collaborative-recsys-based-item,H&M Personalized Fashion Recommendations
6408,94797879,2483.0,0.0029834641716982,0,0,/sanvidpunde/h-m-prediction-using-decision-tree,H&M Personalized Fashion Recommendations
6409,88108179,2496.0,,0,1,/thieuma06/h-m-table-eda,H&M Personalized Fashion Recommendations
6410,88393938,2517.0,,2,45,/konradb/product-embeddings,H&M Personalized Fashion Recommendations
6411,92371404,2513.0,0.003144681323133,0,1,/arunkumar1809/hm-recommender,H&M Personalized Fashion Recommendations
6412,89147619,2547.0,,3,18,/salmaneunus/h-m-personalized-recommendation-simple-eda,H&M Personalized Fashion Recommendations
6413,125835062,2575.0,0.0083655613084958,0,0,/xgarve/popularity-based-recommender-using-polars,H&M Personalized Fashion Recommendations
6414,92120135,2612.0,,0,12,/figfiglol/lightfm-recommendation-system-with-h-m-data,H&M Personalized Fashion Recommendations
6415,92182846,2623.0,,3,9,/matveyspiridonov/h-m-little-eda,H&M Personalized Fashion Recommendations
6416,95603962,2689.0,,0,0,/ericajingwei/h-m-eda,H&M Personalized Fashion Recommendations
6417,91834882,2518.0,,0,2,/ihedot/eda-of-h-m-items-customers-transaction-data,H&M Personalized Fashion Recommendations
6418,94271913,2702.0,,0,0,/michaeltkuo/h-m-kaggle-competition-initial-practice,H&M Personalized Fashion Recommendations
6419,93401271,2715.0,0.0016057990143322,0,3,/saadelkouari/h-m-recommendation-system-code,H&M Personalized Fashion Recommendations
6420,87396076,2720.0,,1,63,/kaerunantoka/h-m-eda-w-pyspark,H&M Personalized Fashion Recommendations
6421,89299730,2744.0,,0,0,/yujihirano/h-and-m-kaggle-eda,H&M Personalized Fashion Recommendations
6422,90331252,2781.0,,2,43,/mohammedobeidat/content-based-filtering-with-pca,H&M Personalized Fashion Recommendations
6423,87742845,2808.0,,0,0,/juststas/hm-recsys-first-runs,H&M Personalized Fashion Recommendations
6424,87520218,2819.0,,0,1,/krsnewwave/standard-reco-eda,H&M Personalized Fashion Recommendations
6425,88807524,2849.0,,0,6,/ransakaravihara/item-similarity-for-content-based-recommendation,H&M Personalized Fashion Recommendations
6426,88264236,2855.0,,3,15,/ginkobalboa/h-m-word-counting,H&M Personalized Fashion Recommendations
6427,88326703,2863.0,,1,4,/cosmosankur/handm-eda-and-first-look,H&M Personalized Fashion Recommendations
6428,91517183,2881.0,0.0,0,1,/rimmir/notebookf9c08b11f7,H&M Personalized Fashion Recommendations
6429,95193549,2951.0,0.0,0,6,/luckypen/personalized-fashion-recommendations,H&M Personalized Fashion Recommendations
6430,87918805,29.0,,2,13,/venkatkumar001/herbarium-22-fgvc9-baseline,Herbarium 2022 - FGVC9
6431,88750059,37.0,,17,28,/jirkaborovec/herbarium-eda-baseline-flash-efficientnet,Herbarium 2022 - FGVC9
6432,91154280,84.0,,0,2,/myncoder0908/fgvc-9,Herbarium 2022 - FGVC9
6433,89931430,114.0,,1,11,/danasone/herbarium-transformers-trainer-submit,Herbarium 2022 - FGVC9
6434,87930263,121.0,,18,46,/odins0n/json-pandas-herbarium-2022,Herbarium 2022 - FGVC9
6435,89308303,123.0,,2,3,/paulreiners/myherbariumnotebook,Herbarium 2022 - FGVC9
6436,88595117,122.0,,0,8,/sytuannguyen/herbarium-2022-fast-eda,Herbarium 2022 - FGVC9
6437,87858950,117.0,6.533406601568325e-09,8,18,/hamzaghanmi/welcome-herbarium-2022,Herbarium 2022 - FGVC9
6438,88961606,118.0,,1,7,/drcapa/herbarium-2022-starter,Herbarium 2022 - FGVC9
6439,87930956,125.0,,1,11,/roshanr11/herbarium-2022-complete-starter-nb,Herbarium 2022 - FGVC9
6440,88859294,128.0,,0,20,/salaheddinelahmadi/exploration-preprocessing-baseline-cnn,Herbarium 2022 - FGVC9
6441,96509740,2.0,,2,16,/leonshangguan/birdnet-inference,BirdCLEF 2022
6442,96465265,1.0,0.8844362925917091,0,2,/ivanpan/fork-of-fork-of-cls-exp-1-870246-021187-967146,BirdCLEF 2022
6443,93590445,6.0,,0,14,/shinmurashinmura/birdclef2022-soundscape-visualisations,BirdCLEF 2022
6444,96592560,15.0,,0,2,/kunihikofurugori/birdclef2022-updateannotation,BirdCLEF 2022
6445,97371205,34.0,,1,17,/nomorevotch/create-the-same-mel-from-librosa-and-torchaudio,BirdCLEF 2022
6446,96649481,67.0,,2,50,/myso1987/birdclef2022-pytorch-starter-only-21-classes,BirdCLEF 2022
6447,94337223,72.0,,3,15,/tc0000/melspectrogram-calc-speed,BirdCLEF 2022
6448,93882296,305.0,,0,0,/kuaileqingwa/eda-for-birdclef-2022,BirdCLEF 2022
6449,89472361,89.0,0.5228046213892787,1,15,/ulrich07/a-dummy-cnn-inference-tf,BirdCLEF 2022
6450,96116943,90.0,,0,2,/blankaf/birdclef-audio-to-numpy-h,BirdCLEF 2022
6451,89298395,65.0,,0,4,/lucasdmr/the-jiripoca-will-pew-pew-00-eda,BirdCLEF 2022
6452,95762046,138.0,,0,32,/lunapandachan/birdclef-eda-v4,BirdCLEF 2022
6453,88197420,348.0,,1,13,/ravishah1/birdclef-2022-audio-feature-engineering-eda,BirdCLEF 2022
6454,95782219,56.0,,3,24,/marchworks/birdclef2022-ssast,BirdCLEF 2022
6455,88097585,365.0,,1,4,/shuheiakahane/birdclef-eda-augumentation,BirdCLEF 2022
6456,88272640,219.0,,0,4,/rhythmcam/audio-basic-librosa-usage,BirdCLEF 2022
6457,93778073,244.0,,0,1,/jingwora1/birdclef2022-united,BirdCLEF 2022
6458,88558566,207.0,,0,8,/foolishboi/birdclef2022-analysis-time,BirdCLEF 2022
6459,94456705,350.0,0.5147570506596623,1,9,/krist0phersmith/birdclef-random-guess-baseline,BirdCLEF 2022
6460,95034252,415.0,,1,10,/lobrien/species-co-occurrence-from-ebird-checklists,BirdCLEF 2022
6461,95889183,441.0,,0,2,/alexklyu/birdclef-2022-sounds-like-a-image-classification,BirdCLEF 2022
6462,88180220,442.0,,0,13,/julian3833/audio-101-1-audio-manipulation-musical-notes,BirdCLEF 2022
6463,96503865,448.0,,0,17,/m1y7k8/birdclef-2022-eda,BirdCLEF 2022
6464,89722990,417.0,,8,28,/venkatkumar001/audiostarter2-end-end-preprocess-lstm-cnn,BirdCLEF 2022
6465,99174350,485.0,,29,102,/usharengaraju/tensorflow-maskedautoencoders-w-b,BirdCLEF 2022
6466,96339760,496.0,0.5858516037386672,1,1,/jamesbarthelemy/non-semantic-representation-of-speech,BirdCLEF 2022
6467,89013232,573.0,0.5150096050534966,3,27,/ambrusattila/basic-submission-without-scoring-error,BirdCLEF 2022
6468,95833366,507.0,,10,41,/jirkaborovec/birdclef-eda-baseline-flash-efficientnet,BirdCLEF 2022
6469,93001660,604.0,0.503627486929632,0,1,/huyidao/infer-exp001-b0-5s,BirdCLEF 2022
6470,95543239,571.0,,1,3,/robbynevels/birdclef-2022-dataset-explorations,BirdCLEF 2022
6471,94830116,520.0,0.4897501036619484,0,2,/waley22/notebook63a1c6dd38,BirdCLEF 2022
6472,93544683,591.0,0.5510795718731333,1,6,/ermak9/simple-classification-using-pytorch,BirdCLEF 2022
6473,94149830,551.0,,0,2,/teacody/birdclef2022-simple-starter-code-error-analysis,BirdCLEF 2022
6474,94811319,549.0,,0,0,/leabsnd/aqsoneleasubmission,BirdCLEF 2022
6475,95265754,705.0,0.5363350624873878,0,2,/bartmiki/birds-book-eda,BirdCLEF 2022
6476,88252734,595.0,,2,15,/atamazian/birdclef-2022-melspectrogram-compute,BirdCLEF 2022
6477,103854770,577.0,,0,0,/azereldukali/ensemble,BirdCLEF 2022
6478,89465744,614.0,,1,15,/duythanhng/birdclef-2022-keras-simple-tutorial,BirdCLEF 2022
6479,95095906,758.0,0.5155169852116644,0,2,/talmanr/unsupervised-simclr-learning-using-all-birds,BirdCLEF 2022
6480,93513722,762.0,,0,5,/riadalmadani/pytorch-base-model-fold0-epoch10,BirdCLEF 2022
6481,88412308,666.0,,1,45,/drcapa/birdclef-2022-starter,BirdCLEF 2022
6482,88114038,763.0,0.5150096050534966,2,17,/sytuannguyen/birdclef-2022-fast-eda,BirdCLEF 2022
6483,87983015,768.0,0.5150096050534966,1,18,/chiranjeevbit/birdclef-2022-eda-and-identifiaction-of-bird-calls,BirdCLEF 2022
6484,88960361,748.0,,0,10,/sagnik1511/birdclef-2022-introduction,BirdCLEF 2022
6485,90244292,791.0,0.5150096050534966,0,2,/ajzensar/birdcliff-basic-eda-v6,BirdCLEF 2022
6486,88860260,656.0,,0,2,/a1248654/notebook43adc7d2ac,BirdCLEF 2022
6487,93721194,642.0,0.4877159878961279,4,11,/jinttt/birdclef-tensorflow,BirdCLEF 2022
6488,95827198,639.0,,0,1,/viktorcikojevic/baseline-dataset-time-integral-over-spectrogram,BirdCLEF 2022
6489,88318862,760.0,0.4944420725186451,0,10,/palash97/birdclef22-pytorch-starter-cnn,BirdCLEF 2022
6490,93225315,643.0,,0,1,/johnnytorres/p08-ann-300,BirdCLEF 2022
6491,91356531,681.0,,1,8,/bowaka/birdclef22-eda-and-signals-identifications,BirdCLEF 2022
6492,96498702,687.0,0.4849962678001869,0,0,/hkonly/birdclef,BirdCLEF 2022
6493,88117689,667.0,,2,11,/alexteboul/birdclef-2022-all-false-naive-lb-0-48,BirdCLEF 2022
6494,90282570,676.0,,0,5,/xxxccc333/train-bird-pytorch-baseline,BirdCLEF 2022
6495,91701660,684.0,,5,29,/kartushovdanil/bird-eda-dark-charts,BirdCLEF 2022
6496,87957319,696.0,,6,45,/robikscube/bird-2022-eda-twitch-live-stream,BirdCLEF 2022
6497,94591128,646.0,,0,0,/rumman18/submission-notebook,BirdCLEF 2022
6546,88634637,3.0,0.9920833333333332,0,5,,Dog vs Cat classification
6547,93079632,2.0,,0,8,/haqishen/simulate-background,UltraMNIST Classification Challenge
6548,93050758,3.0,0.9895714285714284,0,4,/namtran1118/ultramnist-3rd-solution,UltraMNIST Classification Challenge
6549,93081111,6.0,,1,25,/vecxoz/tricks-for-large-images,UltraMNIST Classification Challenge
6550,90254424,22.0,,3,13,/miwojc/ultra-mnist-fastai-starter,UltraMNIST Classification Challenge
6551,90348040,34.0,,0,3,/zuraiz/worst-accuracy-using-random-ultra-mnist,UltraMNIST Classification Challenge
6552,91036554,49.0,0.1527142857142857,0,3,/mohammadkashifunique/umnist-tez-5-folds,UltraMNIST Classification Challenge
6553,91176496,46.0,,4,2,/phanttan/keras-resnet-umnist-training,UltraMNIST Classification Challenge
6554,90195968,52.0,,1,20,/konradb/fast-image-resizing,UltraMNIST Classification Challenge
6555,92161090,72.0,,0,1,/aninda/ultramnist-simple-baseline-fastai,UltraMNIST Classification Challenge
6556,90683710,78.0,,0,2,/praveeniitd/beginner-ultra-mnist-xception-finetuning-no-cv,UltraMNIST Classification Challenge
6557,91424245,81.0,,0,0,/harshraj22/ultramnist,UltraMNIST Classification Challenge
6558,90198749,86.0,,11,30,/odins0n/updated-ultramnist-image-resizer-512x512,UltraMNIST Classification Challenge
6559,90034908,96.0,,0,3,/stpeteishii/ultramnist-bitwise-not,UltraMNIST Classification Challenge
6560,92344337,12.0,,0,7,/jellyfiy/chinese-word-division,CSU-AI-InClass-NLP
6561,90111085,1.0,0.4822355289421157,20,28,/dienhoa/fastai-pogchamp-music-genre-classification,Music Classification
6562,90265789,18.0,,0,0,/harshul23/churn-prediction,Telecom Churn Case Study Hackathon
6563,91052548,1.0,,1,1,/letmeknow/top1-sol,[AI TEMPO RUN] Retrieval of Song Lyrics
6564,91557205,19.0,,0,5,/bobfromjapan/sorghum-keras-dataloader-with-albumentation,Sorghum -100 Cultivar Identification - FGVC 9
6565,92856797,54.0,0.6325408240967934,4,6,/erdican/effnet-gpu,Sorghum -100 Cultivar Identification - FGVC 9
6566,92450517,92.0,0.7799306201878331,11,43,/pegasos/sorghum-pytorch-lightning-starter-training,Sorghum -100 Cultivar Identification - FGVC 9
6567,98335196,91.0,,0,0,/changnico/notebookbce1650859,Sorghum -100 Cultivar Identification - FGVC 9
6568,91369112,89.0,,5,12,/nayakroshan/swin-transformer-focal-loss-0-526,Sorghum -100 Cultivar Identification - FGVC 9
6569,93028138,106.0,,1,3,/laurentpoyet/sorghum-100-preprocessing-and-training,Sorghum -100 Cultivar Identification - FGVC 9
6570,90402192,152.0,0.0740333361536509,2,7,/lonnieqin/sorghum-100-cultivar-identification-with-cnn,Sorghum -100 Cultivar Identification - FGVC 9
6571,92297522,157.0,,2,3,/aquibalikhan/sorghum-100-cultivar-identification-eda,Sorghum -100 Cultivar Identification - FGVC 9
6572,92929337,162.0,,2,4,/waynewhying/sorghum-transferlearning-efficientnet,Sorghum -100 Cultivar Identification - FGVC 9
6573,91304322,165.0,,0,3,/prashanthacsq/fgvc9-statistics,Sorghum -100 Cultivar Identification - FGVC 9
6574,95785078,174.0,,0,1,/arminatc/sorghum-fastai,Sorghum -100 Cultivar Identification - FGVC 9
6575,91268865,186.0,0.4936119807090278,2,12,/tchaye59/efficientnet-tensorflow-baseline-tpu,Sorghum -100 Cultivar Identification - FGVC 9
6576,96379400,193.0,0.435739064218631,13,13,/aayushdeswal/95-sorghum-efficientnetb2-by-beginner,Sorghum -100 Cultivar Identification - FGVC 9
6577,90601546,194.0,,0,7,/ayuraj/images-to-tfrecord,Sorghum -100 Cultivar Identification - FGVC 9
6578,91061004,195.0,,1,9,/ibombonato/vit-transformers-sorghum-100-starter-0-491,Sorghum -100 Cultivar Identification - FGVC 9
6579,96100744,197.0,0.4680599035451391,0,2,/pksx01/sorghum-cultivar-prediction-baseline,Sorghum -100 Cultivar Identification - FGVC 9
6580,96319697,202.0,,0,2,/aroonima12/eda-sorghum-image-classification,Sorghum -100 Cultivar Identification - FGVC 9
6581,90394909,216.0,,1,9,/motloch/sorghum-pytorch-starter,Sorghum -100 Cultivar Identification - FGVC 9
6582,113539054,219.0,,0,1,/ivanmaksimov21/sorghum-challenge-final-project-ds,Sorghum -100 Cultivar Identification - FGVC 9
6583,92370053,226.0,,1,3,/girinchutia01/sorghum-100-training-pipeline,Sorghum -100 Cultivar Identification - FGVC 9
6584,90259743,242.0,0.0115068956764531,2,18,/meetnagadia/sorghum-100-cultivar-baseline,Sorghum -100 Cultivar Identification - FGVC 9
6585,90303005,236.0,,2,7,/gauravduttakiit/sorghum-cultivar-identification-class-dataset,Sorghum -100 Cultivar Identification - FGVC 9
6586,92461113,251.0,,0,0,/myncoder0908/sorghum-fgvc9-transfer-learning-via-fine-tuning,Sorghum -100 Cultivar Identification - FGVC 9
6587,90865275,1.0,1.5631273045412093,11,23,/cabaxiom/rdc-22-data-leakage-and-starter-notebook,2022 Regression Data Challenge
6588,90553977,45.0,,2,10,/docxian/2022-regression-data-challenge-eda,2022 Regression Data Challenge
6589,90626949,17.0,8.004504592540384,0,0,/omarvivas/torchrdc,2022 Regression Data Challenge
6590,91912023,20.0,1.5371796732845449,2,10,/akmalmir/no-machine-learning-just-interpolate,2022 Regression Data Challenge
6591,112597526,62.0,,0,4,/ayanotemitope/medical-condition-scoring-system,2022 Regression Data Challenge
6592,93141714,73.0,2.984386733533772,0,3,/abhishek123maurya/medical-score-predictor,2022 Regression Data Challenge
6593,125519670,64.0,,0,2,/pradeepsapparapu/prediction-medical-condition,2022 Regression Data Challenge
6594,91124593,86.0,3.719854545001849,1,7,/alexryzhkov/rdc-22-lightautoml-baseline,2022 Regression Data Challenge
6595,91581686,105.0,,0,6,/shubhamsoni07/2022-regression-data-challenge,2022 Regression Data Challenge
6596,103234103,95.0,0.98000768935025,0,4,/archietram/subm-for-multi-target-road-to-the-top-part-4,Paddy Doctor: Paddy Disease Classification
6597,98743415,8.0,0.8738946559015763,45,604,/jhoward/first-steps-road-to-the-top-part-1,Paddy Doctor: Paddy Disease Classification
6598,100516682,134.0,0.9807766243752404,3,14,/fmussari/fast-resnet34-with-fastai,Paddy Doctor: Paddy Disease Classification
6599,102169607,113.0,0.9796232218377549,1,9,/imbikramsaha/00-pushing-limits-on-paddy-doctor-fastai,Paddy Doctor: Paddy Disease Classification
6600,99869445,164.0,,4,17,/konradszafer/paddy-disease-pytorch-acc-98-0,Paddy Doctor: Paddy Disease Classification
6601,102709341,135.0,,2,12,/iamravi1/paddy,Paddy Doctor: Paddy Disease Classification
6602,98967247,129.0,0.9842368319876972,2,12,/alexanderyyy/paddydoctor-fastai2,Paddy Doctor: Paddy Disease Classification
6603,104392827,74.0,,0,0,/bencoman/rttt4-multi-target-variety-age,Paddy Doctor: Paddy Disease Classification
6604,104419987,171.0,,1,13,/asheniranga/paddy-doctor-training,Paddy Doctor: Paddy Disease Classification
6605,104266234,47.0,0.9815455594002308,3,10,/mohamedazizchabchoub/fastai-ensembling-stratified-cross-validation,Paddy Doctor: Paddy Disease Classification
6606,99120784,148.0,0.9269511726259132,0,6,/santhoshkumarv/visualize-paddy-disease-efficientnet-b0,Paddy Doctor: Paddy Disease Classification
6607,97915480,161.0,,2,24,/gman123/fastai-out-of-the-box,Paddy Doctor: Paddy Disease Classification
6608,98355377,279.0,,4,8,/amanbahuguna/vgg16-paddy-disease-classify-92-81-acc,Paddy Doctor: Paddy Disease Classification
6609,101913890,194.0,0.9765474817377932,0,8,/miquel0/paddy-doctor-resnet34-pytorch-w-b,Paddy Doctor: Paddy Disease Classification
6610,101613794,137.0,0.9753940792003076,1,0,/ritheshsreenivasan/paddydiseaseclassificationv2,Paddy Doctor: Paddy Disease Classification
6611,102663946,305.0,0.9823144944252212,0,1,/peterpetrov826/saving-paddy-with-fastai-0-982-on-lb,Paddy Doctor: Paddy Disease Classification
6612,98235526,226.0,,0,10,/duylamlee/simple-pytorch-transfer-learning-code,Paddy Doctor: Paddy Disease Classification
6613,101008506,207.0,0.978085351787774,0,1,/whoishoo/hooai-paddy-disease,Paddy Doctor: Paddy Disease Classification
6614,103218837,210.0,,0,1,/maunilshah/paddy-disease-classification,Paddy Doctor: Paddy Disease Classification
6615,97878645,318.0,,2,5,/akashsdevbanshi/cnn-tranfer-learning-fine-tuning-90-valid-acc,Paddy Doctor: Paddy Disease Classification
6616,98104534,335.0,0.9700115340253748,0,2,/koushikcon/efficientnet-b4-sampler,Paddy Doctor: Paddy Disease Classification
6617,104403050,287.0,0.9700115340253748,1,5,/canonicalized/paddy-disease-classification-autogluon,Paddy Doctor: Paddy Disease Classification
6618,104509217,372.0,0.8204536716647444,0,1,/tharunreddy/pytorch-baseline,Paddy Doctor: Paddy Disease Classification
6619,140802277,379.0,,0,15,/maifeeulasad/paddy-doctor-paddy-disease-classification,Paddy Doctor: Paddy Disease Classification
6620,99961466,380.0,,0,5,/kugatsunekawa/paddy-disease-multi-head-vgg16,Paddy Doctor: Paddy Disease Classification
6621,96358583,359.0,,0,2,/bernhardertel/exploration-histograms-label-per-variety,Paddy Doctor: Paddy Disease Classification
6622,96441894,384.0,,2,8,/nitibbgg/simple-cnn-paddy-disease-classifaction-acc-0-88,Paddy Doctor: Paddy Disease Classification
6623,103038479,396.0,,0,3,/aleksandrmogilevskiy/k-fold-stratified,Paddy Doctor: Paddy Disease Classification
6624,100724976,369.0,0.9500192233756248,0,1,/chtalhaanwar/huggingface-model,Paddy Doctor: Paddy Disease Classification
6625,93857571,393.0,0.9319492502883506,15,26,/abhishek123maurya/mobilenetv2-paddy-disease-classifier,Paddy Doctor: Paddy Disease Classification
6626,98398736,392.0,0.942714340638216,0,2,/huilili/paddy-doctor,Paddy Doctor: Paddy Disease Classification
6627,97409830,389.0,,0,3,/nivu07/paddy-disease-classification-cnn-tensorflow-hub,Paddy Doctor: Paddy Disease Classification
6628,97104093,405.0,,0,0,/liyihua/paddy-cnn,Paddy Doctor: Paddy Disease Classification
6629,102236255,413.0,0.946559015763168,0,1,/ikinglopez/paddy-doctor-entry,Paddy Doctor: Paddy Disease Classification
6630,101908481,400.0,0.7277970011534025,0,1,/moajjem04/paddy-doctor-convnext-v3,Paddy Doctor: Paddy Disease Classification
6631,96641497,399.0,0.9419454056132256,2,7,/aayushdeswal/90-paddy-classification-efficientnetb2,Paddy Doctor: Paddy Disease Classification
6632,109917676,416.0,0.9104190695886196,16,55,/tejasurya/paddy-disease-quickstart-resnet-in-keras,Paddy Doctor: Paddy Disease Classification
6633,99513910,428.0,0.9331026528258364,0,3,/wittmannf/simple-benchmark-with-deepfeatx-and-sklearn,Paddy Doctor: Paddy Disease Classification
6634,101184134,442.0,,1,12,/ltrahul/finally-became-paddy-doctor,Paddy Doctor: Paddy Disease Classification
6635,97551938,467.0,,0,10,/muki2003/paddy-disease-classifier-tensorflow-keras,Paddy Doctor: Paddy Disease Classification
6636,95755133,466.0,,0,1,/sartajbirsingh/paddy-disease-classification,Paddy Doctor: Paddy Disease Classification
6637,103434423,444.0,,0,3,/ugorjiir/ricepaddy,Paddy Doctor: Paddy Disease Classification
6638,98451724,469.0,,0,0,/koushikcs/paddy-disease,Paddy Doctor: Paddy Disease Classification
6639,101269914,471.0,,0,2,/mohdsarfarazali/paddy-disease-inception-resnet-v2,Paddy Doctor: Paddy Disease Classification
6640,96686346,485.0,0.7443291041906959,0,3,/youneskhandouch/paddy-disease-classification-with-cnn,Paddy Doctor: Paddy Disease Classification
6641,119157331,528.0,,0,2,/cheremgena/classification-paddy-desease,Paddy Doctor: Paddy Disease Classification
6642,104446028,523.0,,1,2,/victorbahlangene/first-steps-road-to-the-top-part-1-tutorial,Paddy Doctor: Paddy Disease Classification
6643,91633494,512.0,,0,12,/samy101/paddy-disease-classification-starter-code-cnn,Paddy Doctor: Paddy Disease Classification
6644,101340387,518.0,,0,11,/faresabbasai2022/paddy-disease-classification,Paddy Doctor: Paddy Disease Classification
6645,103850054,533.0,,0,3,/rama3282/fastai-first-steps-road-to-the-top-part-1,Paddy Doctor: Paddy Disease Classification
6646,101762632,550.0,,0,0,/swapnilpote/paddy-doctor-paddy-disease-classification,Paddy Doctor: Paddy Disease Classification
6647,103412151,578.0,0.7620146097654749,0,8,/jiaowoguanren/paddy-doctor-paddy-disease-classification-tf,Paddy Doctor: Paddy Disease Classification
6648,93186125,589.0,0.6116878123798539,0,4,/gopalgoyal612002/paddy-disease-classification,Paddy Doctor: Paddy Disease Classification
6649,94234743,614.0,,0,7,/aliphya/exploring-paddy-data,Paddy Doctor: Paddy Disease Classification
6650,97138497,633.0,,0,3,/hassanelgafif/paddy-disease-classification-using-cnn,Paddy Doctor: Paddy Disease Classification
6651,96255612,644.0,,2,8,/mukeshrajm/paddy-disease-classification-fast-ai,Paddy Doctor: Paddy Disease Classification
6652,98791167,649.0,0.0,0,0,/kushalkapoor/rice-paddy-classifier,Paddy Doctor: Paddy Disease Classification
6653,91147000,8.0,,0,1,/michaln/hotel-id-image-preprocessing-256x256,Hotel-ID to Combat Human Trafficking 2022 - FGVC9
6654,99181139,1.0,0.8612166616315974,3,20,/goldenlock/usp-base,U.S. Patent Phrase to Phrase Matching
6655,95162420,11.0,,0,3,/quincyqiang/pppm-deberta-v3-large-baseline-5cv-cls,U.S. Patent Phrase to Phrase Matching
6656,90973432,26.0,,21,204,/remekkinas/eda-and-feature-engineering,U.S. Patent Phrase to Phrase Matching
6657,97675347,125.0,0.8433010293976183,11,32,/gaozhao/share-a-normal-5fold-model,U.S. Patent Phrase to Phrase Matching
6658,95662805,205.0,0.7794101495782895,4,12,/yangranran/offline-version-for-submission,U.S. Patent Phrase to Phrase Matching
6659,95899293,147.0,,8,17,/don9wankim/us-patent-eda-for-kokr,U.S. Patent Phrase to Phrase Matching
6660,98843857,31.0,0.8504249815713183,0,8,/atharvaingle/uspppm-inference-ensemble-hill-climbing,U.S. Patent Phrase to Phrase Matching
6661,90887549,178.0,,0,11,/nbroad/cross-encoder-baseline,U.S. Patent Phrase to Phrase Matching
6662,98689596,99.0,,2,10,/nischaydnk/stacking-v0-w-electra,U.S. Patent Phrase to Phrase Matching
6663,91914452,83.0,,41,140,/ksork6s4/uspppm-bert-for-patents-baseline-train,U.S. Patent Phrase to Phrase Matching
6664,93310001,162.0,,0,0,/yuutahasegawa/uspppm-eda,U.S. Patent Phrase to Phrase Matching
6665,98142260,215.0,,10,40,/mohamadmerchant/us-phrase-matching-tf-keras-train-tpu,U.S. Patent Phrase to Phrase Matching
6666,98939048,57.0,0.828384736750154,0,0,/hutch1221/uspppm-inference,U.S. Patent Phrase to Phrase Matching
6667,96750400,285.0,0.839530143451599,10,53,/renokan/pppm-deberta-v3-large-additional-fold-s,U.S. Patent Phrase to Phrase Matching
6668,93314971,223.0,,0,0,/nagashimakeisuke/eda-and-feature-engineering,U.S. Patent Phrase to Phrase Matching
6669,93051584,122.0,,12,58,/ohmeow/iterate-like-a-grandmaster-blurrified,U.S. Patent Phrase to Phrase Matching
6670,98757789,226.0,0.8109069231531867,3,3,/afiaibnath/deberta-v3-small-wkpooling-inference,U.S. Patent Phrase to Phrase Matching
6671,97769390,232.0,0.839558700644111,0,0,/perfectqing/model-without-custom-from-huggingface,U.S. Patent Phrase to Phrase Matching
6672,93177187,322.0,0.8200441102736277,0,4,/niallm/iterate-like-a-grandmaster-submission-misc,U.S. Patent Phrase to Phrase Matching
6673,98189007,548.0,0.8383354502776521,1,2,/yichuwang123/deberta-v3-large-baseline-inference,U.S. Patent Phrase to Phrase Matching
6674,98855163,297.0,,0,0,/aleron751/stack-blend-train,U.S. Patent Phrase to Phrase Matching
6675,98119029,529.0,,6,55,/luaubrey/uspppm-inference,U.S. Patent Phrase to Phrase Matching
6676,97709313,527.0,,0,1,/kosukewakita/getting-started-with-nlp-for-absolute-beginners-jp,U.S. Patent Phrase to Phrase Matching
6677,98902270,379.0,,0,1,/fritzcremer/patent-ptpm-leaderboard-shakeup,U.S. Patent Phrase to Phrase Matching
6678,91827288,366.0,,1,7,/bibhabasumohapatra/train-us-patent-part-1-simple-pytorch,U.S. Patent Phrase to Phrase Matching
6679,98952835,404.0,,0,1,/ssoyoooung/usppm-data-eda-tutorial-1,U.S. Patent Phrase to Phrase Matching
6680,99120412,407.0,,0,2,/anhongbi/usppm-train-tutorial-2,U.S. Patent Phrase to Phrase Matching
6681,94214988,419.0,0.3951649065636136,0,0,/arjunjanamatti/notebook8f847456aa,U.S. Patent Phrase to Phrase Matching
6682,93784994,421.0,,1,10,/foolishboi/phrase-to-phrase-eda,U.S. Patent Phrase to Phrase Matching
6683,98738416,432.0,,4,4,/deadprstkrish/us-patents-k-folds-deberta-v3,U.S. Patent Phrase to Phrase Matching
6684,94318486,447.0,,3,7,/tensorchoko/u-s-patent-phrase-eda-en-jp,U.S. Patent Phrase to Phrase Matching
6685,94663413,468.0,,6,35,/gpreda/us-patent-phrase-to-phrase-matching-eda,U.S. Patent Phrase to Phrase Matching
6686,96934131,384.0,0.5779172361985885,0,0,/jaloeffe92/advanced-feature-engineering-with-deberta,U.S. Patent Phrase to Phrase Matching
6687,96122210,376.0,,0,1,/bkanupam/us-pppm-maskedlm-pretrain-deberta-v3-small,U.S. Patent Phrase to Phrase Matching
6688,95428902,551.0,0.8272316858716532,0,0,/maxverstappen/pppm-deberta-v3-large-baseline-max-inference,U.S. Patent Phrase to Phrase Matching
6689,93582182,190.0,,2,5,/arvinddevarkonda/semantic-similarity-creating-similarity-features,U.S. Patent Phrase to Phrase Matching
6690,96556279,300.0,,4,6,/snnclsr/bert-for-patents-baseline-pseudolabelling-train,U.S. Patent Phrase to Phrase Matching
6691,97947540,372.0,,20,99,/alincijov/nlp-starter-continuous-bag-of-words-cbow,U.S. Patent Phrase to Phrase Matching
6692,97845169,367.0,,0,5,/kotikkonstantin/length-sort-batch-sampler-w-1st-max-length-batch,U.S. Patent Phrase to Phrase Matching
6693,94080063,689.0,,0,0,/abdelrahmanhassanein/ptp-matching-eda,U.S. Patent Phrase to Phrase Matching
6694,96706155,795.0,,0,1,/nelumbolutea/eda-solve-problem-as-multiclass-classification,U.S. Patent Phrase to Phrase Matching
6695,96850745,586.0,,8,26,/venkatkumar001/u-s-p-p-baseline-eda-dataprep,U.S. Patent Phrase to Phrase Matching
6696,96191534,609.0,0.8392967760915481,3,40,/surilee/inference-bert-for-uspatents-deepshare,U.S. Patent Phrase to Phrase Matching
6697,96670186,614.0,,0,6,/mikhaildonskoy/eda-u-s-patent-phrase-for-beginners,U.S. Patent Phrase to Phrase Matching
6698,97339029,359.0,0.7993323451102995,0,0,/kutuz4/uspppm-bert-for-patents-baseline-inference,U.S. Patent Phrase to Phrase Matching
6699,95967707,484.0,,1,5,/ceshine/sentence-t5-base-baseline-no-training,U.S. Patent Phrase to Phrase Matching
6700,96027125,541.0,,3,15,/narendra/simple-eda,U.S. Patent Phrase to Phrase Matching
6701,97076717,1154.0,0.8066630726780137,0,2,/yudelune6101068/pppm-deberta-v3-large-baseline-inference,U.S. Patent Phrase to Phrase Matching
6702,95370447,718.0,0.8002455835867258,0,0,/ainurbl/fine-tuning-bert-simple-and-straightforward,U.S. Patent Phrase to Phrase Matching
6703,91940314,715.0,,1,6,/ldevyataykina/baseline-metric-choice,U.S. Patent Phrase to Phrase Matching
6704,98972840,672.0,,0,1,/datakite/phrase-matching-using-keras-and-transformers,U.S. Patent Phrase to Phrase Matching
6705,90879320,908.0,,3,12,/damianpanek/first-look-into-data,U.S. Patent Phrase to Phrase Matching
6706,96183616,980.0,0.3989542163182101,2,7,/lonnieqin/u-s-patent-phrase-to-phrase-matching-with-tfhub,U.S. Patent Phrase to Phrase Matching
6707,93952769,990.0,,0,0,/jiabll/patent-c,U.S. Patent Phrase to Phrase Matching
6708,90953092,904.0,,21,59,/hasanbasriakcay/patent-phrase-matching-eda-fe-baseline,U.S. Patent Phrase to Phrase Matching
6709,95951164,711.0,,0,25,/lunapandachan/uspppm-eda-v3,U.S. Patent Phrase to Phrase Matching
6710,95204160,1121.0,,0,0,/guanghan/train-us-patent-deepshare,U.S. Patent Phrase to Phrase Matching
6711,93454351,794.0,,0,2,/okanzkaya/deberta-mini-st5k,U.S. Patent Phrase to Phrase Matching
6712,91739576,1042.0,,0,5,/bharathbn1998/us-patient-phrase-phrase-matching,U.S. Patent Phrase to Phrase Matching
6713,90894463,1044.0,,1,13,/tc0000/uspppm-huggingface-train-inference-by-patent-bert,U.S. Patent Phrase to Phrase Matching
6714,102160205,1092.0,,0,2,/fanbyprinciple/from-jeremy-s-iterate-like-a-grandmaster,U.S. Patent Phrase to Phrase Matching
6715,90951513,1035.0,,11,89,/abhishek/tez-training-phrase-matching,U.S. Patent Phrase to Phrase Matching
6716,93345820,1100.0,0.8018832441135285,0,0,/rkoirala129/finetuning-using-roberta-for-uppm,U.S. Patent Phrase to Phrase Matching
6717,95011750,1262.0,,0,0,/aruthart/eda-and-baseline,U.S. Patent Phrase to Phrase Matching
6718,92359274,1233.0,,0,2,/pranay1990/basic-eda-and-data-preprocessing,U.S. Patent Phrase to Phrase Matching
6719,93153468,1227.0,0.8218203506811539,0,3,/ahsr0x76/tho-submission,U.S. Patent Phrase to Phrase Matching
6720,96588740,1244.0,,0,9,/bhavesjain/train-baseline-bert-w-o-context,U.S. Patent Phrase to Phrase Matching
6721,92687064,1265.0,0.3528790449046246,1,16,/nayakroshan/beginner-bert-for-patents-svr,U.S. Patent Phrase to Phrase Matching
6722,90881714,1151.0,,6,36,/tanlikesmath/u-s-patent-phrase-to-phrase-matching-simple-eda,U.S. Patent Phrase to Phrase Matching
6723,99978342,1142.0,,1,2,/takeshisuzuki/patent-train-0614,U.S. Patent Phrase to Phrase Matching
6724,94523214,1255.0,,0,9,/leekh7411/uspppm-deberta-v3-small-kor-ver,U.S. Patent Phrase to Phrase Matching
6725,93253988,1326.0,,0,1,/vietnhat/patent-phrase-matching,U.S. Patent Phrase to Phrase Matching
6726,96023628,1353.0,0.2335971494401177,1,0,/honghong11/ldaprocessing,U.S. Patent Phrase to Phrase Matching
6727,96067008,1355.0,,1,1,/terovaleriya/my-patent-phrase,U.S. Patent Phrase to Phrase Matching
6728,98034052,1308.0,,2,2,/irinamaslowski/u-s-patent-phrase-basic-eda,U.S. Patent Phrase to Phrase Matching
6729,95288708,1396.0,0.8067202203636079,0,2,/znu808/uspppm-bertforpatent-keras-prediction,U.S. Patent Phrase to Phrase Matching
6730,94136217,1392.0,0.2523351624764302,4,5,/himanshubag/patent-matching-glove-embedding-lstm,U.S. Patent Phrase to Phrase Matching
6731,95565101,1411.0,0.8083508197047776,1,0,/aalexl/getting-started-with-nlp-offline-version,U.S. Patent Phrase to Phrase Matching
6732,94414047,1352.0,,0,3,/ishansharma13/eda-usppm,U.S. Patent Phrase to Phrase Matching
6733,95913024,1419.0,0.6312095968248116,0,1,/hongheee/patentsberta-baseline,U.S. Patent Phrase to Phrase Matching
6734,90959858,1333.0,,0,7,/dschettler8845/us-pp2pm-tfidf-baseline-rapids,U.S. Patent Phrase to Phrase Matching
6735,99145345,1431.0,0.8010967564508047,0,0,/cenzop/uspppm-predictions,U.S. Patent Phrase to Phrase Matching
6736,95990068,1436.0,,3,8,/mattrosinski/nlp-with-transformers-and-deberta-v3-small,U.S. Patent Phrase to Phrase Matching
6737,91676344,1378.0,0.4180016397449779,11,41,/legorreta/traditional-approach-levenshtein,U.S. Patent Phrase to Phrase Matching
6738,96024984,1351.0,0.8019367166051902,0,0,/tanyapridonyants/u-s-patent-phrase-to-phrase-matching,U.S. Patent Phrase to Phrase Matching
6739,97244664,1317.0,,3,16,/bharadwajvedula/pppm-tpu-high-speed-bert-training,U.S. Patent Phrase to Phrase Matching
6740,98902320,1347.0,,0,1,/alishaangdembe/phrasematching-nlp,U.S. Patent Phrase to Phrase Matching
6741,93055377,1455.0,,0,0,/shivarama/simple-sentence-similarity-matching,U.S. Patent Phrase to Phrase Matching
6742,94576139,1435.0,0.7981499480423849,0,1,/bmhjhu/deberta-v3-w-early-stopping,U.S. Patent Phrase to Phrase Matching
6743,97450722,1442.0,0.7979697447082851,0,1,/christiandeantana/pptpm,U.S. Patent Phrase to Phrase Matching
6744,94390985,1484.0,,3,3,/nanditab35/patent-phrase-matching-eda,U.S. Patent Phrase to Phrase Matching
6745,96016844,1459.0,,12,52,/miwojc/getting-started-with-nlp-offline-version,U.S. Patent Phrase to Phrase Matching
6746,95504902,1429.0,0.5921048747576396,0,0,/ddtarski/pppm-sentence-bert-v0-1,U.S. Patent Phrase to Phrase Matching
6747,95733133,1469.0,0.2978540841722129,2,4,/himanshutripathi/uspppm-baseline-glove-vectors,U.S. Patent Phrase to Phrase Matching
6748,90926355,1505.0,0.7840905445737175,3,23,/danofer/uspppm-huggingface-patent-bert,U.S. Patent Phrase to Phrase Matching
6749,96956109,1488.0,,0,0,/sampathweb/patents-train,U.S. Patent Phrase to Phrase Matching
6750,97951842,1506.0,0.7668696509130426,0,0,/rosemaryzheng/roberta-albert,U.S. Patent Phrase to Phrase Matching
6751,91849355,1534.0,,10,61,/junjitakeshima/uspppm-simple-roberta-starter-eng,U.S. Patent Phrase to Phrase Matching
6752,90891412,1525.0,0.7425669915206383,4,45,/phantivia/uspppm-huggingface-train-inference-baseline,U.S. Patent Phrase to Phrase Matching
6753,90903716,1541.0,0.757349818293245,1,4,/shigeeeru/uspppm-eda-submission,U.S. Patent Phrase to Phrase Matching
6754,96029827,1545.0,0.7552934460918223,1,1,/vladislavem/roberta-em,U.S. Patent Phrase to Phrase Matching
6755,91556647,1536.0,0.7551643988739606,0,1,/koalaswelcome/simple-roberta,U.S. Patent Phrase to Phrase Matching
6756,95331998,1559.0,0.7279239642204488,2,4,/krsna540/tensorflow-nlp-semantic-textual-similarities,U.S. Patent Phrase to Phrase Matching
6757,95331998,1559.0,0.7167442030742421,2,4,/krsna540/tensorflow-nlp-semantic-textual-similarities,U.S. Patent Phrase to Phrase Matching
6758,90962647,1537.0,,7,7,/sohailshaik272/detailed-eda-for-patent-phrase,U.S. Patent Phrase to Phrase Matching
6759,96685799,1573.0,,0,0,/witoldszejgis/notebook8da6703f16,U.S. Patent Phrase to Phrase Matching
6760,91682233,1574.0,0.4465826382263591,0,2,/krdatascientist/notebookd2fe6b33ce,U.S. Patent Phrase to Phrase Matching
6761,92196228,1564.0,0.7222288031128348,0,8,/gopalgoyal612002/u-s-patent-phrase-to-phrase-matching-robert-base,U.S. Patent Phrase to Phrase Matching
6762,95162408,1561.0,0.7278544417401326,0,0,/rajeshradhakrishnan/r003-gryffindor-nimbus-2000,U.S. Patent Phrase to Phrase Matching
6763,94393550,1594.0,0.7187343366106277,2,0,/codefluence/finetuning-sentence-embeddings-with-sbert,U.S. Patent Phrase to Phrase Matching
6764,101678172,1595.0,,5,10,/skiplik/first-nlp-project-w-tf-keras-roberta,U.S. Patent Phrase to Phrase Matching
6765,95789715,1602.0,0.6868086966001945,0,10,/nilaychauhan/uspppm-starter-notebook-using-jax,U.S. Patent Phrase to Phrase Matching
6766,95942749,1608.0,,0,0,/pilsungdev/us-patent-phrase-matching-using-sbert,U.S. Patent Phrase to Phrase Matching
6767,97247290,1626.0,,0,0,/norellel/all-distilroberta-v1-train,U.S. Patent Phrase to Phrase Matching
6768,95632379,1627.0,,1,3,/apocarus/uspppm-bert-for-patents-various-models,U.S. Patent Phrase to Phrase Matching
6769,96020839,1629.0,0.3799856632467629,1,1,/jamesnakano/patent-work-notebook,U.S. Patent Phrase to Phrase Matching
6770,92739556,1644.0,0.5368688791515916,0,0,/chuka19952/nlp-patent-phrase-to-phrase-matching,U.S. Patent Phrase to Phrase Matching
6771,93007766,1641.0,,2,3,/brunogianesi/patent-phrase-to-phrase-matching-baseline,U.S. Patent Phrase to Phrase Matching
6772,96776671,1654.0,,0,0,/sunnyal/patent-phrase-to-phrase-matching-eda-catboost,U.S. Patent Phrase to Phrase Matching
6773,98561450,1661.0,,14,34,/tanyadayanand/sentence-transformer-cosine-similaritybeginner,U.S. Patent Phrase to Phrase Matching
6774,99807056,1653.0,,1,2,/abdo96/modeling-u-s-patent,U.S. Patent Phrase to Phrase Matching
6775,96900840,1679.0,,0,0,/saurabhmishra98/train-baseline-bert-w-o-context,U.S. Patent Phrase to Phrase Matching
6776,98084900,1684.0,0.4465826370687954,0,3,/tracyporter/patent-phrase-similarity-spacy,U.S. Patent Phrase to Phrase Matching
6777,94983877,1686.0,,0,3,/sunilkrishnan/cpc-titles-usage,U.S. Patent Phrase to Phrase Matching
6778,96261645,1682.0,0.4296579469291744,0,4,/ashishkattel/u-s-patent-phrase-to-phrase-matching-tfidf,U.S. Patent Phrase to Phrase Matching
6779,92146207,1669.0,0.4247752334406652,0,0,/rafaeldd/patent-randomforest,U.S. Patent Phrase to Phrase Matching
6780,90965497,1727.0,0.4200833990812236,0,2,/rajankumar/baseline-semantical-similarity-using-spacy,U.S. Patent Phrase to Phrase Matching
6781,91296945,1692.0,0.4151969204137779,0,5,/shilpagopal/basic-string-matchers-hamming-levenshtein-jaro,U.S. Patent Phrase to Phrase Matching
6782,91187558,1694.0,0.4147850196835516,29,32,/vickeytomer/eda-modeling-beginner-friendly,U.S. Patent Phrase to Phrase Matching
6783,99033812,1745.0,,0,0,/cyprienricque/deberta-fine-tuned,U.S. Patent Phrase to Phrase Matching
6784,97388475,1752.0,0.2343050700631559,0,0,/yil1ii/patent-similarity,U.S. Patent Phrase to Phrase Matching
6785,97937144,1771.0,0.2924542727265677,0,0,/falreis/falreis-notebook-tf-idf,U.S. Patent Phrase to Phrase Matching
6786,96416526,1759.0,0.27755924261271,0,1,/jaeahjoah/ldaprocessing,U.S. Patent Phrase to Phrase Matching
6787,95815548,1764.0,,0,3,/akshatpathak/us-patents,U.S. Patent Phrase to Phrase Matching
6788,94140732,1791.0,0.2119050262210681,0,0,/amosditto/model-v2,U.S. Patent Phrase to Phrase Matching
6789,95915106,1849.0,,1,3,/ravin235/beginner-approach-targets-scores-eda-wordcloud,U.S. Patent Phrase to Phrase Matching
6790,95815020,1850.0,2.215507801146427e-17,0,1,/dkdkdkdkw/competition-practice,U.S. Patent Phrase to Phrase Matching
6791,93507261,1864.0,-0.0341189141780004,0,0,/mrlmarquez/us-phrase-matching-tf-keras-inference,U.S. Patent Phrase to Phrase Matching
6792,97045778,1886.0,,0,1,/soumochatterjee/phrase-to-phrase-match-exploratory-data-analysis,U.S. Patent Phrase to Phrase Matching
6793,97727593,1889.0,,1,0,/toya18/nlp-for-beginners2,U.S. Patent Phrase to Phrase Matching
6794,92515915,1.0,0.9661503054353904,3,12,/davidedwards1/tab-april22-pytorch-lstm-starter-v2,Tabular Playground Series - Apr 2022
6795,94459308,3.0,0.9902380700579312,1,10,/group16/tps-april-3-solution-the-final-blend,Tabular Playground Series - Apr 2022
6796,91998892,5.0,,0,6,/cabaxiom/tps-apr-22-in-depth-eda,Tabular Playground Series - Apr 2022
6797,94471665,2.0,,0,4,/azzamradman/2nd-place-final-stacking,Tabular Playground Series - Apr 2022
6798,92214896,15.0,0.9766004931954804,12,43,/dmitryuarov/tps-sensors-2xlstm-xgb-auc-0-976,Tabular Playground Series - Apr 2022
6799,93607104,41.0,,21,69,/hasanbasriakcay/tpsapr22-eda-fe-baseline,Tabular Playground Series - Apr 2022
6800,93712954,23.0,,2,6,/prathwishmestha/notebook4c9fbf27bf,Tabular Playground Series - Apr 2022
6801,93396253,31.0,,0,0,/wangqijing/xgboost-dnn-ensemble-lb-0-980,Tabular Playground Series - Apr 2022
6802,93466862,20.0,,0,3,/slythe/exploring-tps-april-22-with-baseline-nn,Tabular Playground Series - Apr 2022
6803,93876724,40.0,0.9809600189354832,3,10,/dlaststark/tps-apr22-tfv1,Tabular Playground Series - Apr 2022
6804,91868237,24.0,0.9403607813908516,6,10,/cristianminas/baseline-tps-april,Tabular Playground Series - Apr 2022
6805,92537503,54.0,,0,1,/mirenaborisova/tabular-playground-april-2022-01,Tabular Playground Series - Apr 2022
6806,98379092,49.0,,8,12,/asdkarma/bilstm-april-tabular,Tabular Playground Series - Apr 2022
6807,92151129,48.0,,2,8,/raviista/tps-april-2022-autogluon-93-2auc,Tabular Playground Series - Apr 2022
6808,92537357,77.0,,7,26,/devsubhash/tps-april-eda-lstm,Tabular Playground Series - Apr 2022
6809,93017640,76.0,,35,65,/abdulravoofshaik/important-features-and-insights,Tabular Playground Series - Apr 2022
6810,93777811,92.0,,20,94,/tyrionlannisterlzy/xgboost-dnn-ensemble-lb-0-980,Tabular Playground Series - Apr 2022
6811,93945497,296.0,,32,100,/khashayarrahimi94/lgbm-using-summary-statistics-tps,Tabular Playground Series - Apr 2022
6812,92746247,84.0,0.9677144132937836,2,11,/huseyincot/tps-apr-pytorch-lightning-single-model-0-971,Tabular Playground Series - Apr 2022
6813,94375827,100.0,0.8326725638610928,1,1,/nnjjpp/tps-april-2022-xgb-with-feature-selection,Tabular Playground Series - Apr 2022
6814,97905860,120.0,0.9450545738089364,13,13,/mustafakeser4/tps-april-with-keras-lstm-cnn,Tabular Playground Series - Apr 2022
6815,94104651,154.0,0.954277438405122,6,11,/matthewszhang/lstm-with-pytorch-and-groupkfold,Tabular Playground Series - Apr 2022
6816,93280940,162.0,,4,15,/siukeitin/tps042022-fe-2500-features-with-tsfresh-catch22,Tabular Playground Series - Apr 2022
6817,92737646,147.0,,15,29,/aboriginal3153/tps-apr-22-lstm-using-pytorch,Tabular Playground Series - Apr 2022
6818,92361008,143.0,0.9716765121108196,37,87,/hamzaghanmi/tps-april-tensorflow-bi-lstm,Tabular Playground Series - Apr 2022
6819,91818765,134.0,0.4931994671877281,2,13,/jagofc/r-submission-template-04-22,Tabular Playground Series - Apr 2022
6820,92197697,199.0,,28,137,/ambrosm/tpsapr22-eda-which-makes-sense,Tabular Playground Series - Apr 2022
6821,94381895,183.0,0.9681676562471148,0,0,/leo45890/tps-april-2022-keras-inception-resnet,Tabular Playground Series - Apr 2022
6822,91961393,168.0,0.9651124630061424,0,0,/rizkykiky/i-just-want-to-guess,Tabular Playground Series - Apr 2022
6823,91961393,168.0,0.9670635060524722,0,0,/rizkykiky/i-just-want-to-guess,Tabular Playground Series - Apr 2022
6824,93146460,223.0,,6,8,/zhixx018/eda-fe-catboost-pipeline,Tabular Playground Series - Apr 2022
6825,92109708,172.0,,2,10,/rnepal2/tps-dnn-augmentation-bandpass-shift-etc,Tabular Playground Series - Apr 2022
6826,107828649,190.0,,66,68,/landfallmotto/tps-apr-lstms-attention,Tabular Playground Series - Apr 2022
6827,92471231,197.0,,2,11,/shimjongsoo/tps-apr-22-study-gru,Tabular Playground Series - Apr 2022
6828,91936891,175.0,,16,82,/kartushovdanil/top-1-tps-apr-22-eda-lstm,Tabular Playground Series - Apr 2022
6829,99415860,181.0,0.964337333622066,24,25,/sanjaylalwani/tps-april-22-lstm,Tabular Playground Series - Apr 2022
6830,93038173,174.0,,2,6,/nahumsa/eda-fe-models,Tabular Playground Series - Apr 2022
6831,91802628,195.0,0.9358438796253864,7,49,/ryanbarretto/lstm-baseline,Tabular Playground Series - Apr 2022
6832,93688125,185.0,0.953450060180592,8,16,/packinman/tps-apr-2022-neural-network-for-beginners,Tabular Playground Series - Apr 2022
6833,91980811,211.0,0.8870518560298939,5,23,/shoooono/lightgbm-baseline-with-simple-feature,Tabular Playground Series - Apr 2022
6834,93751456,251.0,0.9590583122239624,3,12,/samu2505/eda-lstm,Tabular Playground Series - Apr 2022
6835,91985770,204.0,,2,19,/ted0071/tps-apr-2022-keras-lstm-model,Tabular Playground Series - Apr 2022
6836,92880751,277.0,,0,2,/thefringthing/xgboost-with-fft-aggregate-statistics-etc,Tabular Playground Series - Apr 2022
6837,93466364,288.0,0.9570598465352934,5,13,/delai50/gramian-angular-field-imaging-cnn2d-0-957-plb,Tabular Playground Series - Apr 2022
6838,94357187,247.0,0.9508638474954968,21,30,/ahmetcelik158/tps-apr-22-lstm-with-pytorch,Tabular Playground Series - Apr 2022
6839,95773211,215.0,,10,38,/jiwonkng/tabular-playground-apr-22,Tabular Playground Series - Apr 2022
6840,93843984,283.0,0.9443270769018998,0,7,/m1y7k8/tps-apr-2022-tsfresh,Tabular Playground Series - Apr 2022
6841,94507481,330.0,,0,0,/girolamanotarangelo/classification-states-tps-april-2022,Tabular Playground Series - Apr 2022
6842,91878796,265.0,0.9448881748913476,0,7,/paulomarquies/tps-apr-22-keras,Tabular Playground Series - Apr 2022
6843,93717908,333.0,0.9477020582266114,14,22,/satoshiss/tps-apr-sneak-peek-xgb,Tabular Playground Series - Apr 2022
6844,92230071,272.0,0.9412697853139212,0,4,/requiem33/tps-apr-2022-lstm,Tabular Playground Series - Apr 2022
6845,92415095,293.0,,1,8,/wonjinkim1010/tabular-april-using-lstm,Tabular Playground Series - Apr 2022
6846,92035278,258.0,0.9257990925068867,45,64,/cv13j0/tps-apr-2022-xgboost-model,Tabular Playground Series - Apr 2022
6847,92204805,307.0,,0,9,/robertturro/eda-and-feature-selection,Tabular Playground Series - Apr 2022
6848,93274012,298.0,0.9379225021696908,2,5,/gopalgoyal612002/tps-apr-2022-lstm-model,Tabular Playground Series - Apr 2022
6849,93106239,337.0,,0,8,/gunjanpaul/complete-eda-data-analysis,Tabular Playground Series - Apr 2022
6850,93877047,309.0,0.9249299571769344,13,47,/sytuannguyen/tps-april-2022-eda-model,Tabular Playground Series - Apr 2022
6851,94118305,371.0,0.9364062366230378,0,3,/sleetet/tabular-playground-apr-22-lstm,Tabular Playground Series - Apr 2022
6852,92626222,365.0,0.934507652251862,10,26,/matanivanov/lgbm-with-fourier-transform,Tabular Playground Series - Apr 2022
6853,93388829,375.0,0.9286079398093358,3,9,/sfktrkl/tps-apr-2022,Tabular Playground Series - Apr 2022
6854,93088265,350.0,0.9284060788273428,31,52,/ohseokkim/tps-apr-let-s-go-over-the-wall-inceptiontime,Tabular Playground Series - Apr 2022
6855,93901560,373.0,,1,7,/gauravduttakiit/tps-042022-autoviz,Tabular Playground Series - Apr 2022
6856,91831563,347.0,0.9258188169687448,6,9,/karthikbhandary2/tbpg-apr-with-nn,Tabular Playground Series - Apr 2022
6857,92393952,352.0,0.9185656707072436,74,114,/lordozvlad/tps-apr-pytorch-bidirectional-lstm,Tabular Playground Series - Apr 2022
6858,93550136,402.0,0.9125161362884774,1,0,/dompero/fcn-for-time-series-classification,Tabular Playground Series - Apr 2022
6859,94009895,410.0,0.9204789435074624,0,1,/anshupriyadarshi/solution1,Tabular Playground Series - Apr 2022
6860,93374121,412.0,0.9195720379313992,6,19,/docxian/tpg-2022-apr-r-starter-eda-model-transparency,Tabular Playground Series - Apr 2022
6861,93378536,361.0,0.917386609524481,1,8,/thomashopkins32/simple-bidirectional-lstm-in-pytorch,Tabular Playground Series - Apr 2022
6862,101567629,372.0,0.9199770189035884,0,0,/leesstephanie/tps-apr2022-lgbm,Tabular Playground Series - Apr 2022
6863,93915828,384.0,,5,8,/boshili/transformer-pratice-for-apr22,Tabular Playground Series - Apr 2022
6864,92527351,398.0,0.8752339656911872,9,23,/himanshunayal/lstm-pytorch,Tabular Playground Series - Apr 2022
6865,92736045,422.0,,1,1,/chenyubang/tps-apr-2022-with-lightgbm,Tabular Playground Series - Apr 2022
6866,91856925,430.0,,3,7,/catadanna/tab-folds-april-2022,Tabular Playground Series - Apr 2022
6867,92363118,452.0,0.8880771083771049,2,12,/naotokitajima/lighgbm-with-some-simple-features,Tabular Playground Series - Apr 2022
6868,91878287,447.0,0.8850525510024223,4,18,,Tabular Playground Series - Apr 2022
6869,92929395,460.0,0.8820510754448077,15,17,/naveenkonam1985/tps-apr-22-eda-lgbmc-optuna,Tabular Playground Series - Apr 2022
6870,92464051,420.0,,1,16,/jeonghyunha/tps-apr-2022-simple-eda-lstm,Tabular Playground Series - Apr 2022
6871,92146658,466.0,,1,7,/desitancheva/stats-xgboost-score-83,Tabular Playground Series - Apr 2022
6872,92793789,470.0,0.8243503097999519,9,20,/hikarumoriya/simple-eda-and-predict-with-lightgbm,Tabular Playground Series - Apr 2022
6873,94489866,472.0,,2,9,/jiprud/tps-apr22-rookie-eda-submission,Tabular Playground Series - Apr 2022
6874,92621120,483.0,,4,7,/imnaho/tps22-apr-searching-good-feature,Tabular Playground Series - Apr 2022
6875,106081184,459.0,,11,27,/vineethakkinapalli/tpsapril2022-tf-lstm-feature-importance,Tabular Playground Series - Apr 2022
6876,94154201,509.0,,0,2,/dcrowd/tablular-playground-apr,Tabular Playground Series - Apr 2022
6877,92386865,478.0,,0,1,/raghulraj422/tps-apr-2022-eda-on-sensor-data-lstm,Tabular Playground Series - Apr 2022
6878,92132320,518.0,0.8409119332154902,0,2,/sophieb/eda-baseline-tps-april-2022,Tabular Playground Series - Apr 2022
6879,92225403,514.0,0.8100400028873255,0,4,/aniskhan25/playground-apr-2022-conv1d,Tabular Playground Series - Apr 2022
6880,92533386,523.0,,2,5,/wasshoiwasshoi/tps-apr-2022-visualization-of-sensor-signal,Tabular Playground Series - Apr 2022
6881,92633914,558.0,0.8217288448851533,1,5,/bcruise/tps-apr-2022-eda-and-baseline,Tabular Playground Series - Apr 2022
6882,92931164,572.0,0.8044554621651248,0,10,/adwaitkesharwani/prediction-with-catboost-classifier,Tabular Playground Series - Apr 2022
6883,95160205,562.0,,0,0,/bvarkoly/tabular-playground-2022-april,Tabular Playground Series - Apr 2022
6884,92187598,586.0,0.7820180474629306,0,4,/stpeteishii/tps0422-simple-lgbm,Tabular Playground Series - Apr 2022
6885,92655448,585.0,0.7132254195435004,4,13,/rafburzy/tp-april-data-exploration-and-prediction-in-r,Tabular Playground Series - Apr 2022
6886,93057856,583.0,0.795564556065314,0,5,/naokisugimura/tps-apr-2022-ensamble-catboost-and-lstm,Tabular Playground Series - Apr 2022
6887,94140350,599.0,0.7846317484938066,0,0,/silviopodhraski/eda-tsfresh-xgboost,Tabular Playground Series - Apr 2022
6888,92002746,610.0,,2,14,/reymaster/apr-2022-tps-simple-time-series-analysis-xgboost,Tabular Playground Series - Apr 2022
6889,92998713,637.0,,7,14,/vishnukarthiklu/tps-4-let-s-speed-up,Tabular Playground Series - Apr 2022
6890,93575686,653.0,0.7502459262691222,1,4,/kartikeychauhan/tabular-playground-series-apr-2022,Tabular Playground Series - Apr 2022
6891,92670193,683.0,0.7543381226005402,1,12,/akioonodera/tps-apr2022-lgbm-binary-classification,Tabular Playground Series - Apr 2022
6892,93986202,745.0,,1,4,/peressim/tps-apr-2022-eda,Tabular Playground Series - Apr 2022
6893,93323029,677.0,0.6562609638631072,1,0,/chethanbr86/tabular-playground-april2022-v3,Tabular Playground Series - Apr 2022
6894,93621426,702.0,0.6919108303243037,0,5,/rajnishkumar546/tps-apr,Tabular Playground Series - Apr 2022
6895,94403667,736.0,,0,3,/hykhhijk/base-tree-model,Tabular Playground Series - Apr 2022
6896,92964975,748.0,,0,5,/bluegnome/simple-data-exploration-and-lag-feature-regression,Tabular Playground Series - Apr 2022
6897,92833702,770.0,,0,0,/sivachandran123/april-22,Tabular Playground Series - Apr 2022
6898,91848527,771.0,,0,4,/tracyporter/april-22-tabular,Tabular Playground Series - Apr 2022
6899,92140417,769.0,,0,1,/jakkojukranti/logistic-regression-with-fast-fourier-transform,Tabular Playground Series - Apr 2022
6900,94174831,763.0,0.5051965563607612,0,1,/omarsamy99/state-prediction,Tabular Playground Series - Apr 2022
6901,94312646,784.0,,0,0,/helenor/wip-april-2022-tabular-playground-series,Tabular Playground Series - Apr 2022
6902,93093090,804.0,0.5,0,2,/akritisood175/tsa-bidirectional-lstm,Tabular Playground Series - Apr 2022
6903,99790406,5.0,,0,3,/konstantinakalimeri/kalimeri-konstantina-solution,Company Bankruptcy Prediction
6904,98273728,33.0,0.9270482603815936,0,10,/alexanderyyy/xraybodyparts-fastai,UNIFESP X-ray Body Part Classifier Competition
6905,101194054,52.0,0.9079685746352412,2,4,/amss10/x-ray-classifier-1,UNIFESP X-ray Body Part Classifier Competition
6906,101489458,28.0,,0,8,/asheniranga/unifesp-x-ray-body-part-classifier-dataset,UNIFESP X-ray Body Part Classifier Competition
6907,101374180,49.0,,3,11,/gbalachandhiran/preparation-of-data-and-training,UNIFESP X-ray Body Part Classifier Competition
6908,94921573,63.0,,0,7,/waynewhying/unifesp-x-ray-body-transferlearning-efficientnet,UNIFESP X-ray Body Part Classifier Competition
6909,117723607,81.0,,15,69,/usamabalochhh/x-ray-bodypart-prediction-eda-cnn,UNIFESP X-ray Body Part Classifier Competition
6910,101010044,96.0,,0,2,/thomasdubail/x-ray-body-part-dataset,UNIFESP X-ray Body Part Classifier Competition
6911,97600660,6.0,0.8098484848484848,10,31,/igorlashkov/imc-2022-baseline-quadtreeattention-0-812-0-817,Image Matching Challenge 2022
6912,97447255,7.0,,1,10,/fakebird/0-848-image-warping-and-crop-with-loftr-dkm,Image Matching Challenge 2022
6913,97713177,14.0,,0,8,/yamash73/imc2022-14th-place-solution-private-lb-0-839,Image Matching Challenge 2022
6914,92109407,12.0,,16,115,/remekkinas/detector-free-local-feature-matching-w-transformer,Image Matching Challenge 2022
6915,97411589,10.0,,0,5,/tmyok1984/imc2022-validation-csv,Image Matching Challenge 2022
6916,92537369,30.0,0.5819264069264068,10,35,/ammarali32/image-matching-challenge-2022-baseline-kornia,Image Matching Challenge 2022
6917,92829303,32.0,,6,43,/losveria/superglue-baseline,Image Matching Challenge 2022
6918,95625792,37.0,0.3080519480519481,0,39,/rsmits/sold-inference,Image Matching Challenge 2022
6919,96228833,49.0,,0,2,/motono0223/imc2022-preprocessing-histogrammatching,Image Matching Challenge 2022
6920,95670446,41.0,,0,0,/iiyamaiiyama/img2022-glrmodel-check-distance-networkx,Image Matching Challenge 2022
6921,97492672,50.0,,0,2,/anonymousyuxiang/imc-2022-example-cross-validation-pipeline,Image Matching Challenge 2022
6922,97317441,63.0,0.7955844155844157,0,0,/tlthegreatestone/kornia-loftr-dkm-pdc,Image Matching Challenge 2022
6923,94976078,66.0,,0,4,/iru538/imc2022-loftr-validation-score,Image Matching Challenge 2022
6924,96309391,92.0,0.6967965367965369,0,9,/calvchen/kornia-loftr-seg,Image Matching Challenge 2022
6925,96242955,93.0,,0,7,/bobfromjapan/segmentation-immovable-object,Image Matching Challenge 2022
6926,97364834,100.0,0.7477922077922077,0,4,/akihirok/loftr-ds-ot-w-o-any-training-imc2022,Image Matching Challenge 2022
6927,92993501,287.0,0.5833982683982685,13,33,/cbeaud/image-matching-challenge-2022,Image Matching Challenge 2022
6928,96148704,316.0,,1,7,/ilyaryabov/google-image-parser,Image Matching Challenge 2022
6929,164348515,135.0,,2,14,/mkosik/image-matching-attempt-with-delf,Image Matching Challenge 2022
6930,96826316,290.0,0.0001298701298701,5,13,/natnitarach/imc-2022-0-0-dkm-loftr,Image Matching Challenge 2022
6931,92581182,196.0,,5,16,/nguyenhung1903/imc-baseline-submission-basic,Image Matching Challenge 2022
6932,96496291,426.0,,0,5,/alexanderdamen/keypoint-selection-by-custom-loss-homography,Image Matching Challenge 2022
6933,92136929,274.0,,0,6,/dinowun/imc2022-baseline-submission-disk,Image Matching Challenge 2022
6934,95762371,198.0,,1,15,/pixyz0130/imc2022-eda,Image Matching Challenge 2022
6935,94308701,376.0,,2,14,/jesperandersson/visualize-superglue-sfm-reconstruction,Image Matching Challenge 2022
6936,96754266,317.0,,4,10,/sanjaylalwani/imc-22-kornia,Image Matching Challenge 2022
6937,93678503,359.0,,4,7,/kentoyamasaki/imc2022-training-data-first-time-at-kaggle,Image Matching Challenge 2022
6938,92837053,559.0,0.533095238095238,4,25,/namgalielei/loftr-kornia,Image Matching Challenge 2022
6939,92465608,605.0,,1,14,/zzy990106/compute-f-using-krt,Image Matching Challenge 2022
6940,93669039,627.0,,0,2,/jenyadatapower/notebook17d7159799,Image Matching Challenge 2022
6941,94800238,628.0,,0,4,/mattmenzi/cv-final-project,Image Matching Challenge 2022
6942,93720597,642.0,,0,2,/devasenak/devasena-harisudhan,Image Matching Challenge 2022
6943,108721466,1.0,,6,37,/shokisakai/jpx-regression,JPX Tokyo Stock Exchange Prediction
6944,110576672,2.0,0.0040259418839354,6,37,/uioiuioi/2nd-place-solution,JPX Tokyo Stock Exchange Prediction
6945,100052889,4.0,0.3478707262260235,0,17,/flat831/4th-place-model,JPX Tokyo Stock Exchange Prediction
6946,108053933,5.0,,6,15,/jonnydossantos/jpx-5th-place-0-339,JPX Tokyo Stock Exchange Prediction
6947,110432535,6.0,,0,1,/kento217/jpx-simple-lightgbm-model,JPX Tokyo Stock Exchange Prediction
6948,95953054,7.0,,0,4,/swiftpredator/xgboost-optuna-short,JPX Tokyo Stock Exchange Prediction
6949,94177073,33.0,,0,1,/ericlepouchard/jpx-target-calc,JPX Tokyo Stock Exchange Prediction
6950,95873218,39.0,,1,10,/periklisdrakousis/notebook92966581ad,JPX Tokyo Stock Exchange Prediction
6951,92391028,44.0,,3,11,/kevinmontes/using-adjustment-factors,JPX Tokyo Stock Exchange Prediction
6952,94620447,55.0,,7,37,/aboriginal3153/ver-jpx-tokyo-simple-way-by-lstm,JPX Tokyo Stock Exchange Prediction
6953,130970823,74.0,,0,0,/vikalptripathi/jpxtokyo,JPX Tokyo Stock Exchange Prediction
6954,96365176,111.0,,8,35,/akshaypawar7/jpx-stock-market-2021-dec-03,JPX Tokyo Stock Exchange Prediction
6955,98135707,147.0,,0,0,/rahilsidiqqui/rahil-siddiqui,JPX Tokyo Stock Exchange Prediction
6956,100100564,229.0,0.0298787267297157,0,0,/abhisekdash37/jpx-lgbm,JPX Tokyo Stock Exchange Prediction
6957,97923696,250.0,,0,2,/yisyuanlee/ds-final-pipeline,JPX Tokyo Stock Exchange Prediction
6958,98200036,253.0,,0,3,/yamashita0240/jpx-fractional-difference-fracdiff,JPX Tokyo Stock Exchange Prediction
6959,92285365,273.0,0.1209403051109289,2,9,/lonnieqin/tokyo-stock-exchange-prediction-with-catboost,JPX Tokyo Stock Exchange Prediction
6960,92285365,273.0,0.1209403051109289,2,9,/lonnieqin/tokyo-stock-exchange-prediction-with-catboost,JPX Tokyo Stock Exchange Prediction
6961,95221980,287.0,0.1114616683183979,0,0,/xingzlee/jpx-lstm-simple,JPX Tokyo Stock Exchange Prediction
6962,98623315,318.0,,1,1,/ozoozo/jpx-eda-time-intervals-in-the-files,JPX Tokyo Stock Exchange Prediction
6963,92384736,350.0,,1,3,/pappukrjha/submission-test,JPX Tokyo Stock Exchange Prediction
6964,96026437,394.0,,0,2,/kavishgoyal/jpx-tokyo-stock-exchange-prediction-by-kv,JPX Tokyo Stock Exchange Prediction
6965,97463530,421.0,,2,17,/hechtjp/jpx-eda-with-cudf-key-events-japan-market,JPX Tokyo Stock Exchange Prediction
6966,97580576,439.0,,0,3,/huayao0728/lstm-small-size-scored-rebuild,JPX Tokyo Stock Exchange Prediction
6967,92219079,487.0,,1,3,/ympaik/tokyo-stock-exchange-prediction-with-xgboost,JPX Tokyo Stock Exchange Prediction
6968,97529751,494.0,,18,40,/nataliasz/quick-lgbm-no-leak,JPX Tokyo Stock Exchange Prediction
6969,94529452,521.0,,7,91,/tensorchoko/jpx-eda-model-jp-en,JPX Tokyo Stock Exchange Prediction
6970,93196394,556.0,,9,23,/celiker/abusing-leakages-for-fun,JPX Tokyo Stock Exchange Prediction
6971,96989000,585.0,,0,12,/dingyan/jpx-gru-tensorflow-baseline-no-leak,JPX Tokyo Stock Exchange Prediction
6972,93189087,592.0,,17,80,/ravishah1/jpx-dnn-lgbm-with-cross-validation,JPX Tokyo Stock Exchange Prediction
6973,95101616,596.0,,0,12,/franciscofeng/no-leakage-dnn-prediction-feature-engineering,JPX Tokyo Stock Exchange Prediction
6974,97417349,611.0,,0,10,/kevinbird15/fastai-starter-notebook,JPX Tokyo Stock Exchange Prediction
6975,106533666,627.0,,0,1,/xxxxyyyy80008/jpx-data-processing-csv2parquet,JPX Tokyo Stock Exchange Prediction
6976,93613640,644.0,,7,30,/daosword/jpx-neural-network-starter-keras,JPX Tokyo Stock Exchange Prediction
6977,94628210,682.0,,0,2,/ericchu630/jpx-baseline-efficient-frontier,JPX Tokyo Stock Exchange Prediction
6978,99628297,691.0,,17,46,/ricopue/jpx-tokyo-securities-filter-no-leak,JPX Tokyo Stock Exchange Prediction
6979,95603851,719.0,,0,1,/pirsqrd/eda-tokyo-sep,JPX Tokyo Stock Exchange Prediction
6980,100167695,745.0,,9,62,/unokensuke/eng-eda-prediction-evaluation,JPX Tokyo Stock Exchange Prediction
6981,107464700,758.0,,0,4,/kaito510/41st-place-w-minor-error-flipped-rolling,JPX Tokyo Stock Exchange Prediction
6982,97535279,789.0,,0,1,/kuxtu72/notebooka70d9a4062,JPX Tokyo Stock Exchange Prediction
6983,99565376,792.0,,1,14,/notabene/jpx-feat-util,JPX Tokyo Stock Exchange Prediction
6984,97692149,795.0,,0,1,/yangonjr/lightgbm,JPX Tokyo Stock Exchange Prediction
6985,94452266,797.0,,1,4,/aemulcahy/jpx-tse-minimal-catboost-baseline,JPX Tokyo Stock Exchange Prediction
6986,99825864,808.0,,2,11,/peterkeszthelyi/jpx-tokyo-ar-arma-arima-models-on-log-returns,JPX Tokyo Stock Exchange Prediction
6987,100020902,847.0,-0.1031732034321197,0,3,/carls2rt/neuralprophet-model,JPX Tokyo Stock Exchange Prediction
6988,95141231,860.0,,0,12,/itachicom615/jpx-competition,JPX Tokyo Stock Exchange Prediction
6989,97988839,866.0,-0.1431824456817104,0,4,/melmurphy/stocks-notebook,JPX Tokyo Stock Exchange Prediction
6990,93370956,872.0,,1,4,/kakys1111/abusing-leakages-for-fun-2,JPX Tokyo Stock Exchange Prediction
6991,95624284,891.0,,0,3,/bond005/jpx-extratrees,JPX Tokyo Stock Exchange Prediction
6992,92568707,905.0,,26,54,/bturan19/lightgbm-ranker-introduction,JPX Tokyo Stock Exchange Prediction
6993,92551800,908.0,,5,84,/ikeppyo/jpx-lightgbm-demo,JPX Tokyo Stock Exchange Prediction
6994,95846743,922.0,,13,53,/avijitduttta/xgboost-try2,JPX Tokyo Stock Exchange Prediction
6995,93788262,990.0,-0.2052705217993266,1,5,/solvar/simple-rolling-linear-regression-no-leakage,JPX Tokyo Stock Exchange Prediction
6996,94266586,1000.0,,1,4,/bisman/jpx-submission,JPX Tokyo Stock Exchange Prediction
6997,96109036,1021.0,,0,2,/marcogorelli/target-discrepancies,JPX Tokyo Stock Exchange Prediction
6998,93879685,1035.0,,3,12,/genbufuthark/jpx-datafile-description-in-japanese,JPX Tokyo Stock Exchange Prediction
7016,100351909,4.0,,0,8,/vincentschuler/fsq-group-category-and-fill-missing-categories,Foursquare - Location Matching
7017,98666033,13.0,,1,28,/tubotubo/tips-measure-exact-execution-time,Foursquare - Location Matching
7018,100539534,17.0,,0,10,/currypurin/memory-usage-and-measure-the-elapsed-time,Foursquare - Location Matching
7019,94422937,21.0,,2,13,/locbaop/foursquare-xgboost-custom-inference-baseline,Foursquare - Location Matching
7020,102747790,23.0,,0,3,/joulazas/latitude-and-longitude-encoding-for-arcmargin,Foursquare - Location Matching
7021,99990388,43.0,,0,3,/shkanda/pylcs-super-fast-library-to-calculate-lcs,Foursquare - Location Matching
7022,100311730,51.0,,2,5,/dongkyunkim/simple-silver-solution-foursquare-inference,Foursquare - Location Matching
7023,97143995,55.0,0.8360353708267212,6,39,/nlztrk/public-0-836-catboost-fast-fe-22-features,Foursquare - Location Matching
7024,93093506,60.0,0.6868383884429932,10,38,/hengzheng/distance-and-category-hard-match-baseline,Foursquare - Location Matching
7025,97558282,64.0,,1,4,/tarique7/foursq-binary-lgb-baseline-0-85,Foursquare - Location Matching
7026,97010536,95.0,,1,13,/mviola/foursquare-location-matching-eda-with-rapids,Foursquare - Location Matching
7027,93942573,106.0,,2,7,/sgreiner/foursquare-kdtree-editdistance,Foursquare - Location Matching
7028,99966794,104.0,,0,1,/tsurakitani/embed-use-ttani-test,Foursquare - Location Matching
7029,99221755,108.0,,0,10,/felipefonte99/foursquare-training-set-in-a-nutshell,Foursquare - Location Matching
7030,93448618,114.0,,0,2,/sorkun/flm-create-samples,Foursquare - Location Matching
7031,99479032,117.0,,1,7,/motono0223/install-pykakasi-wo-internet,Foursquare - Location Matching
7032,99140898,116.0,,2,32,/negoto/fsq-name-variants-and-other-languages,Foursquare - Location Matching
7033,96155295,131.0,,7,37,/roniheka/convert-japanese-texts-into-alphabet-precisely,Foursquare - Location Matching
7034,93325770,150.0,0.746337354183197,7,21,/cbeaud/spatial-neighbours-benchmark-name-and-category,Foursquare - Location Matching
7035,93083649,133.0,,0,8,/foolishboi/foursquare-simple-eda,Foursquare - Location Matching
7036,93334598,168.0,,6,23,/lennarthaupts/spatial-neighbours-benchmark,Foursquare - Location Matching
7037,99336267,197.0,,10,19,/sskknt/eng-eda-it-s-never-too-late-to-do-eda,Foursquare - Location Matching
7038,95786720,206.0,0.6548956632614136,1,13,/frankmollard/rapids-dbscan,Foursquare - Location Matching
7039,95325615,212.0,,0,20,/tensorchoko/foursquare-eda-en-jp,Foursquare - Location Matching
7040,93631617,231.0,,0,10,/tcarloscn/unify-city-names-and-fill-nan,Foursquare - Location Matching
7041,93489329,262.0,,3,4,/omarvivas/model-4square-haversian-v1,Foursquare - Location Matching
7042,98215940,268.0,,3,8,/dinowun/eda-simplified-foursquare-location-matching,Foursquare - Location Matching
7043,101744199,276.0,,0,2,/taos2000/foursquare-train-data-generation,Foursquare - Location Matching
7044,93652358,431.0,0.8209200501441956,68,322,/ryotayoshinobu/foursquare-lightgbm-baseline,Foursquare - Location Matching
7045,93652358,431.0,0.8209200501441956,68,322,/ryotayoshinobu/foursquare-lightgbm-baseline,Foursquare - Location Matching
7046,97847974,433.0,0.8587470054626465,20,54,/zakopur0/foursquare-catboost-baseline,Foursquare - Location Matching
7047,95818384,443.0,0.8340013027191162,6,109,/guoyonfan/binary-lgb-baseline-0-834,Foursquare - Location Matching
7048,97840788,454.0,,1,15,/markwijkhuizen/foursquare-use-mpnet-name-embeddings,Foursquare - Location Matching
7049,97227263,459.0,,0,6,/cenzop/fuzzy-matcher-r-notebook,Foursquare - Location Matching
7050,98763402,457.0,,3,32,/chack3/fastlcs,Foursquare - Location Matching
7051,95363837,462.0,0.8313501477241516,17,129,/ragnar123/flm-xlmroberta-inference-baseline,Foursquare - Location Matching
7052,95567392,519.0,,0,45,/thedrcat/foursquare-questions-about-data,Foursquare - Location Matching
7053,94712416,555.0,,0,4,/takafumitakizawa/make-train-data-knn-and-cross-validation-iou,Foursquare - Location Matching
7054,93317361,584.0,,10,35,/andypenrose/spatial-neighbours-benchmark-name-and-category,Foursquare - Location Matching
7055,96202097,625.0,,1,33,/lunapandachan/foursquare-eda-sentence-bert,Foursquare - Location Matching
7056,96042515,657.0,,0,1,/victorasso/fork-of-foursquare-location-matches-hex-68fccf,Foursquare - Location Matching
7057,93680745,671.0,,1,54,/robikscube/foursquare-location-matching-eda-twitch-stream,Foursquare - Location Matching
7058,93059081,672.0,0.6389968395233154,2,22,/pjmathematician/matching-based-on-nearest-location,Foursquare - Location Matching
7059,93781239,682.0,,1,5,/david26694/flm-additional-match-and-non-match-pairs-data,Foursquare - Location Matching
7060,97922504,720.0,,1,8,/sanjaylalwani/haversine-distance-pairs-data-foursquare,Foursquare - Location Matching
7061,94755515,776.0,,4,58,/hidehisaarai1213/foursquare-eda-distance-distribution-variation,Foursquare - Location Matching
7062,96038268,787.0,,0,5,/gabrielbchacon/fork-of-foursquare-location-matches-hex-lda,Foursquare - Location Matching
7063,93439023,836.0,0.7610356211662292,4,88,/aerdem4/foursquare-rapids-xgb-inference,Foursquare - Location Matching
7064,98834499,848.0,,0,16,/junjitakeshima/fsq-tfidf-and-name-similarity-eng,Foursquare - Location Matching
7065,96063534,864.0,,1,3,/plarmuseau/poi-distribution-error,Foursquare - Location Matching
7066,96587852,877.0,0.526787281036377,0,5,/zenone/foursquare,Foursquare - Location Matching
7067,96005490,879.0,0.743073582649231,0,0,/lzx932001/2022-s1-cos20083-assignment2-group11,Foursquare - Location Matching
7068,94262388,914.0,,0,3,/santoshkumar/1-eda-for-foursquare-location-matching,Foursquare - Location Matching
7069,99822914,919.0,0.6993996500968933,0,1,/sumamallapragada/foursquare-gd-analysis,Foursquare - Location Matching
7070,95176037,920.0,,11,37,/ananduk1993/foursquare-detailed-eda-analysis,Foursquare - Location Matching
7071,98499163,933.0,,1,4,/harukiyasui/eda-japanese,Foursquare - Location Matching
7072,96650362,936.0,,2,5,/jimkaihuang/location-matching-siamese-network,Foursquare - Location Matching
7073,93090788,950.0,0.6491747498512268,0,7,/shashimo/foursquare-eda-and-submit,Foursquare - Location Matching
7074,98891389,970.0,0.6491854190826416,1,0,/ahmedali058/foursquare-location-matching,Foursquare - Location Matching
7075,98891389,970.0,0.6491854190826416,1,0,/ahmedali058/foursquare-location-matching,Foursquare - Location Matching
7076,94518886,978.0,,2,3,/utkarshshukla2912/foursquare-rf-with-string-features-with-haversine,Foursquare - Location Matching
7077,94578765,987.0,,0,3,/b11gden/location-matching,Foursquare - Location Matching
7078,95015688,992.0,0.6491747498512268,0,35,/ttahara/fsq-lm-self-match-only-baseline,Foursquare - Location Matching
7079,95197091,997.0,0.6491747498512268,1,10,/samyukthamobile/find-matching-location-5-mins,Foursquare - Location Matching
7080,95197091,997.0,0.6491747498512268,1,10,/samyukthamobile/find-matching-location-5-mins,Foursquare - Location Matching
7081,96751504,1012.0,0.6491747498512268,0,1,/carywei958/2022-5-18,Foursquare - Location Matching
7082,93589877,1.0,,2,27,/carnozhao/tract-competiton-metrics,UW-Madison GI Tract Image Segmentation
7083,99191395,32.0,,0,7,/yingpengchen/uwmgit-nnunet-3d-training,UW-Madison GI Tract Image Segmentation
7084,95566931,27.0,,4,9,/p4rallax/uwmgit-mmsegmentation-inference,UW-Madison GI Tract Image Segmentation
7085,93883465,86.0,,6,58,/yiheng/50-times-faster-way-get-hausdorff-with-monai,UW-Madison GI Tract Image Segmentation
7086,100788228,84.0,0.881078014133108,0,0,/phamthaihoangtung/uwm-3d-monai-mmseg-v2-infer,UW-Madison GI Tract Image Segmentation
7087,100846004,149.0,0.8811728496741117,1,1,/ddcddmm/end-to-end-submission,UW-Madison GI Tract Image Segmentation
7088,94775811,133.0,,0,7,/purplejester/fast-ai-02-histogram-equalization,UW-Madison GI Tract Image Segmentation
7089,93069792,123.0,,5,29,/fabiendaniel/image-with-masks-quick-overview,UW-Madison GI Tract Image Segmentation
7090,100873242,43.0,,6,23,/atmguille/uw-madison-43rd-cv-strategy-77-in-private,UW-Madison GI Tract Image Segmentation
7091,95987159,507.0,,0,1,/romamartyanov/uwmgi-2-5d-stride-2-data-step-2-0-2,UW-Madison GI Tract Image Segmentation
7092,98574054,102.0,,4,9,/tt195361/uwmgi-image-segmentation-eda,UW-Madison GI Tract Image Segmentation
7093,98406931,98.0,,0,1,/yoshoo/wrong-annotation,UW-Madison GI Tract Image Segmentation
7094,100865377,83.0,0.8770200322602708,0,4,/hideyukizushi/uw-inf-single-3-0d-a600-infx384,UW-Madison GI Tract Image Segmentation
7095,95854357,106.0,0.8554033137205369,0,1,/takeajioka/unetr-inference-submission-3-labels-raw-size,UW-Madison GI Tract Image Segmentation
7096,93204308,140.0,,1,6,/vexxingbanana/gi-tract-2d-approach-coco-dataset,UW-Madison GI Tract Image Segmentation
7097,95162051,201.0,,4,8,/jsxyhelu2019/uwmgit-datapreparation-pytorch-fastai,UW-Madison GI Tract Image Segmentation
7098,98646456,659.0,,3,17,/zekaili/eda-and-helper-functions,UW-Madison GI Tract Image Segmentation
7099,100842059,194.0,0.8717155978290402,0,6,/rm1000/improved-monai-ensemble-weights,UW-Madison GI Tract Image Segmentation
7100,98228182,192.0,,3,10,/caomaobin/uw-madison-data-incorrect-in-case7day0,UW-Madison GI Tract Image Segmentation
7101,97505351,289.0,,0,3,/hatokgl/submit-uuwmgi,UW-Madison GI Tract Image Segmentation
7102,94830084,284.0,,2,17,/ammarnassanalhajali/uwmgi-detectron2-training,UW-Madison GI Tract Image Segmentation
7103,100301115,231.0,0.8717512387055074,0,0,/yixuliu/3d-solution-with-monai-ensemble-weights,UW-Madison GI Tract Image Segmentation
7104,107759690,267.0,,0,0,/jitensharma597/uwmgi-transunet-keras-train,UW-Madison GI Tract Image Segmentation
7105,98921971,228.0,,3,13,/dinowun/eda-simplified-uwm-gi-tract-segmentation-w-w-b,UW-Madison GI Tract Image Segmentation
7106,98493031,272.0,,7,27,/utm529fg/eda-umwgi-mask,UW-Madison GI Tract Image Segmentation
7107,93097096,363.0,,5,28,/gunesevitan/uw-madison-gi-tract-image-segmentation-eda,UW-Madison GI Tract Image Segmentation
7108,93114398,421.0,,9,21,/mohammaddehghan/pytorch-dataloader-and-visualize,UW-Madison GI Tract Image Segmentation
7109,93445742,736.0,0.804547894153186,9,21,/salmanahmedtamu/pytorch-unet-efficientnet-b1,UW-Madison GI Tract Image Segmentation
7110,98601517,717.0,0.8591347166127244,0,1,,UW-Madison GI Tract Image Segmentation
7111,98601517,717.0,0.8591347166127251,0,1,,UW-Madison GI Tract Image Segmentation
7112,98601517,717.0,0.8591347166127248,0,1,,UW-Madison GI Tract Image Segmentation
7113,96872106,725.0,,0,0,/lezilv/2d-solution-with-monai,UW-Madison GI Tract Image Segmentation
7114,96298254,746.0,,5,32,/priyanagda/getting-started-understanding-data,UW-Madison GI Tract Image Segmentation
7115,105985647,597.0,0.851113369298745,0,0,/kailathan/3d-solution-with-monai-ensemble-weights,UW-Madison GI Tract Image Segmentation
7116,98497554,565.0,,0,3,/sinamhd9/making-3d-volumes-and-save-as-npy,UW-Madison GI Tract Image Segmentation
7117,98656781,555.0,,1,10,/zxj2323/3d-solution-with-monai-infer,UW-Madison GI Tract Image Segmentation
7118,94851951,680.0,,2,12,/clemchris/gi-seg-prepare-numpy-masks,UW-Madison GI Tract Image Segmentation
7119,97203750,812.0,,0,1,/dragonslayer01/transformation-v1,UW-Madison GI Tract Image Segmentation
7120,95787730,1110.0,,0,0,/pranavjadhav/infer,UW-Madison GI Tract Image Segmentation
7121,97751698,841.0,,2,106,/awsaf49/uwmgi-mask-data,UW-Madison GI Tract Image Segmentation
7122,97090826,698.0,0.4365998630169531,0,6,/lvgang623/2d-solution-with-monai,UW-Madison GI Tract Image Segmentation
7123,95950261,933.0,,1,17,/lunapandachan/uwm-eda,UW-Madison GI Tract Image Segmentation
7124,99360969,1015.0,0.0,0,3,/dmitry999/uw-competition-new,UW-Madison GI Tract Image Segmentation
7125,97316621,1112.0,0.8514609040713109,0,1,/huyidao/uwmgi-infer-exp010-7,UW-Madison GI Tract Image Segmentation
7126,95191251,1167.0,,2,2,/gtownfoster/uwmgi-yolov5-train,UW-Madison GI Tract Image Segmentation
7127,93568518,1310.0,0.523385571529462,3,3,/sadivamadaan/basic-submission,UW-Madison GI Tract Image Segmentation
7128,99915382,1350.0,0.8296723607195678,0,1,/shrutimurarka/uw-infer-keras,UW-Madison GI Tract Image Segmentation
7129,94085166,1345.0,,0,2,/bhavesh0124/uwmgi-processing-and-visualization,UW-Madison GI Tract Image Segmentation
7130,98811581,1355.0,0.6536620913340789,0,2,/zhangqing123/tract-segm-baseline-flash-unet-albumentation,UW-Madison GI Tract Image Segmentation
7131,96570705,1367.0,0.8085395027336614,0,3,/dalalmanish/madi-v2,UW-Madison GI Tract Image Segmentation
7132,93165958,1404.0,,0,3,/sumitjha19/eda-image-mask-with-video-from-stack-of-slices,UW-Madison GI Tract Image Segmentation
7133,96012843,1425.0,,0,15,/gbalachandhiran/demystify-image-segmentation-from-scratch,UW-Madison GI Tract Image Segmentation
7134,95519067,1452.0,,4,15,/israrahmed919/simple-preprocessingtraincsv,UW-Madison GI Tract Image Segmentation
7135,97512820,1470.0,0.5935940868046573,0,0,/abose550/unet-resnetbackbone-inference,UW-Madison GI Tract Image Segmentation
7136,98142915,1476.0,0.501161084399386,0,1,/muratter/uw-madison-01,UW-Madison GI Tract Image Segmentation
7137,94180275,1482.0,,0,9,/rbhadra/annotations-with-motion-using-mri-slices,UW-Madison GI Tract Image Segmentation
7138,101842014,1503.0,0.802121037894278,0,9,/maryiaznak/mri-scans-segmentation-keras-unet,UW-Madison GI Tract Image Segmentation
7139,96335849,1508.0,,7,10,/rerere/wip-uwmgit-eda,UW-Madison GI Tract Image Segmentation
7140,93747205,1535.0,,1,7,/mohanrobotics/cocoformat-dataset-creation-instance-segmentation,UW-Madison GI Tract Image Segmentation
7141,108812551,5.0,0.6630459226098644,15,52,/abhishek/goodreads-autotrain,Goodreads Books Reviews
7142,113650081,13.0,,0,3,/adegladius/goodreads-books-bert-base-cased-0-45337,Goodreads Books Reviews
7143,116056436,15.0,,33,66,/serkanp/goodread-books-reviews-analysis,Goodreads Books Reviews
7144,104333976,26.0,,0,1,/jeremyadamsfisher/goodreads-x-huggingface-trainer,Goodreads Books Reviews
7145,101969608,32.0,,0,11,/mikhailutrobin/book-review-rating-with-pytorch-lightning,Goodreads Books Reviews
7146,121299278,47.0,0.5760094763431357,1,4,/pawebiegun/books-reviews,Goodreads Books Reviews
7147,120196708,67.0,,5,5,/alessandrozanette/goodreads-books-reviews-eda-cleaning-nn,Goodreads Books Reviews
7148,126544267,68.0,,0,0,/shadowhat/exercise-goodread-reviews-rating-nlp,Goodreads Books Reviews
7149,134296113,70.0,,0,3,/abdallahragab223/roberta,Goodreads Books Reviews
7150,156113922,75.0,,4,14,/maryiaznak/goodreads-reviews-eda-roberta-tf-tpu-vm-v3-8,Goodreads Books Reviews
7151,123454660,74.0,,0,6,/justinsiow/goodreads-distilbert-automodel-tensorflow,Goodreads Books Reviews
7152,96502606,80.0,,0,0,/qsuire/goodreads-books-reviews-parquet-files,Goodreads Books Reviews
7153,118677565,93.0,0.5814955050127345,2,5,/klyushnik/reviews-with,Goodreads Books Reviews
7154,108592600,96.0,,0,3,/gabrielikaro/goodreads-data-processing-for-sentiment-analysis,Goodreads Books Reviews
7155,109422142,112.0,0.5415531370775,0,8,/priyanagda/tf-idf-lr,Goodreads Books Reviews
7156,106166741,113.0,,0,2,/ricxavtoragu/goodreads-books-reviews-eda-rxta,Goodreads Books Reviews
7157,109639691,120.0,0.5453970179851788,4,13,/belsonraja/good-reads-book-review-analysis-notebook,Goodreads Books Reviews
7158,109512069,118.0,,0,6,/bouyakhsainekhadija/goodreads-data-processin,Goodreads Books Reviews
7159,97981262,136.0,0.3454655279714245,0,0,/polaternez/books-recommendation-surprice,Goodreads Books Reviews
7160,116488872,135.0,,0,9,/liqiang2022/books-rate-prediction,Goodreads Books Reviews
7161,123625181,142.0,0.527814531438762,0,0,/mohamedaminesahraoui/book-review,Goodreads Books Reviews
7162,123625181,142.0,0.527814531438762,0,0,/mohamedaminesahraoui/book-review,Goodreads Books Reviews
7163,118194487,145.0,,2,6,/pathompongmuangthong/my-very-dumb-logistic-regression-sklearn,Goodreads Books Reviews
7164,115223747,162.0,,4,10,/datarohitingole/simple-eda-and-interactive-plots,Goodreads Books Reviews
7165,97412122,173.0,,0,6,/mayerantoine/eda-nlp-goodreads-books-reviews,Goodreads Books Reviews
7166,93093185,207.0,,1,7,/danofer/goodreads-data-munge,Goodreads Books Reviews
7167,104210542,215.0,0.3422466045718649,1,4,/vickytau/basic-eda-and-mean-prediction,Goodreads Books Reviews
7168,106347629,225.0,,0,3,/elahehosseini/notebook6e440ed027,Goodreads Books Reviews
7169,117938266,242.0,,0,1,/ashokkumargarain/notebookdd6e4057fc,Goodreads Books Reviews
7170,95455826,247.0,,2,2,/vijaysiyer/goodreads-reviews,Goodreads Books Reviews
7171,124075070,261.0,0.0,0,9,/gauridargar/gd-bookreview,Goodreads Books Reviews
7172,95164514,29.0,,23,61,/balabaskar/autism-prediction-eda-auc-0-853-score,Autism Prediction
7173,94357097,32.0,0.8439903317952099,23,32,/mahsazamanifard/autism-diagnosis,Autism Prediction
7174,95961004,10.0,0.8580531751263458,4,8,/ezzzio/autism-prediction-0-85805-score,Autism Prediction
7175,98485469,1.0,,20,29,/himanshunayal/autism-prediction-1-solution,Autism Prediction
7176,97958796,47.0,0.8571742474181498,0,6,/raselmeya/asd-predictions-with-8-different-models-85-7,Autism Prediction
7177,93480708,46.0,0.7780707536805098,4,13,/francuzovd/autism-prediction-77-8-feature-engineering,Autism Prediction
7178,94430063,5.0,,2,5,/arnavr10880/asd-prediction-eda-baseline,Autism Prediction
7179,95006385,9.0,0.7834541858932103,4,7,/abhishek123maurya/no-ml-baseline-solution-using-eda,Autism Prediction
7180,95454858,23.0,0.8483849703361899,1,12,/alexryzhkov/autism-lightautoml,Autism Prediction
7181,95002178,18.0,0.8360799824214459,12,25,/sanjaylalwani/autism-diagnosis-with-flaml,Autism Prediction
7182,97356362,15.0,,2,7,/naveenkonam1985/autism-prediction-with-catboost,Autism Prediction
7183,93411317,22.0,0.7486266754559437,0,3,/skylord/fastai-tabular-version-0-pb-0-74,Autism Prediction
7184,96426578,14.0,0.7079762689518787,4,7,/raushan9jnv/austim-data-ml,Autism Prediction
7185,93874307,33.0,0.7902658756317293,3,10,/jawahar96/autism-eda-prediction-score-79-5,Autism Prediction
7186,96046241,49.0,,2,3,/musicbanerjee/autism-eda-and-prediction-score,Autism Prediction
7187,97340351,34.0,0.6930344979125467,1,2,/jiyakelawala/high-accuracy-using-basic-models,Autism Prediction
7188,124720579,89.0,,6,20,/bcruise/autism-prediction-eda-baseline,Autism Prediction
7189,98563891,104.0,0.8508020215337289,0,5,/kristoffhernan/autism-prediction-in-adults,Autism Prediction
7190,94751179,58.0,0.6728191606240387,1,2,/purvapr/autism-prediction-analysis,Autism Prediction
7191,94403078,645.0,,0,3,/ananyachauhan/notebookbdde5f16f3,UCS654 - Lab-2 Exam (Kaggle Hack)
7192,94983237,10.0,,0,12,/sharrish/draw-color-landmarks,VKCV_2022_Contest_01: Facial Landmarks
7193,95877003,1.0,0.9983456378179132,2,22,/pourchot/tpsmay22-keras-test-tuned,Tabular Playground Series - May 2022
7194,95143994,7.0,0.9948187277667888,0,12,/foolishboi/tps-may22-xgb-baseline,Tabular Playground Series - May 2022
7195,110741929,9.0,0.9982535585947552,1,6,/deepernet/9th-place-solution-in-tpsmay22,Tabular Playground Series - May 2022
7196,96435001,10.0,0.998270339430084,4,28,/mehrankazeminia/tpsmay22-auc-ensembling,Tabular Playground Series - May 2022
7197,94696641,16.0,0.9839401108399158,2,2,/ehekatlact/tps2205-pycaret,Tabular Playground Series - May 2022
7198,94696641,16.0,0.9839401108399158,2,2,/ehekatlact/tps2205-pycaret,Tabular Playground Series - May 2022
7199,95685717,26.0,0.9980693541118552,0,1,/jitensharma597/tsp2022-tabnet,Tabular Playground Series - May 2022
7200,96148676,17.0,,12,54,/cabaxiom/tps-may-22-eda-lgbm-model,Tabular Playground Series - May 2022
7201,94781516,19.0,0.9905795664065716,11,15,/cbeaud/tps-may-2022-lgbm-fe-optuna,Tabular Playground Series - May 2022
7202,95761213,25.0,,1,31,/kotrying/tps22-05,Tabular Playground Series - May 2022
7203,94912039,62.0,0.9936964510703205,1,12,/delai50/tpsmay22-gbdts-quickstart-useful-interactions,Tabular Playground Series - May 2022
7204,94912039,62.0,0.9936964510703205,1,12,/delai50/tpsmay22-gbdts-quickstart-useful-interactions,Tabular Playground Series - May 2022
7205,94461748,36.0,,0,6,/dlaststark/tps-may22-eda-insights,Tabular Playground Series - May 2022
7206,94531579,43.0,,1,14,/nnjjpp/eda-may-2022-exploring-the-string-feature-f-27,Tabular Playground Series - May 2022
7207,94788139,72.0,,1,1,/paulomarquies/tps-may-22-xgboost,Tabular Playground Series - May 2022
7208,95237806,78.0,0.9938249686501696,0,0,/mirenaborisova/tps-may-2022-eda-lgbm-lb-0-99382,Tabular Playground Series - May 2022
7209,94460949,82.0,,8,31,/harshitkmr/tps22-may-lgbm-beginners,Tabular Playground Series - May 2022
7210,94456410,86.0,,1,5,/uthamkanth/tpsmay2022-basic-eda-with-data-visualization,Tabular Playground Series - May 2022
7211,94507905,97.0,0.9397231189032098,1,5,/shravankoninti/baseline-xgboost-prediction,Tabular Playground Series - May 2022
7212,95610515,75.0,0.9982498273796476,1,5,/nadhiarpradana/simple-tps-may-2022-0-99824,Tabular Playground Series - May 2022
7213,94808135,102.0,,2,10,/slythe/tps-may-super-eda-base-model,Tabular Playground Series - May 2022
7214,95622650,109.0,0.9968495527148382,0,5,/mustafakeser4/tps-may-keras-cnn-2d-1d,Tabular Playground Series - May 2022
7215,94888161,108.0,,34,109,/hasanbasriakcay/tpsmay22-insightful-eda-fe-baseline,Tabular Playground Series - May 2022
7216,96241115,139.0,0.9958738771187606,6,37,/cv13j0/tps-may22-eda-gbdt,Tabular Playground Series - May 2022
7217,96142102,113.0,0.9859219839370994,1,11,/docxian/tps-2022-may-visual-baseline,Tabular Playground Series - May 2022
7218,94593384,132.0,,0,4,/davidhguerrero/eda-of-data-tps-may22,Tabular Playground Series - May 2022
7219,95763054,129.0,,38,47,/naoshermustakim/comprehensive-eda-tps-may,Tabular Playground Series - May 2022
7220,94834469,126.0,0.9927661103507858,12,38,/devsubhash/tps-may-lightautoml-0-992,Tabular Playground Series - May 2022
7221,97248016,141.0,,0,0,/eduus710/tps-may-22-feature-interaction-boundaries,Tabular Playground Series - May 2022
7222,96016709,146.0,,4,12,/matthewszhang/tps-may-eda-and-feature-enigneering-learning-notes,Tabular Playground Series - May 2022
7223,96068544,155.0,0.998146545003612,10,65,/alexryzhkov/tps-may-22-lightautoml-here-again,Tabular Playground Series - May 2022
7224,97116988,164.0,0.9980891047071812,2,7,/mukaseevru/tps-may-22-fe-lama-lightautoml,Tabular Playground Series - May 2022
7225,94776991,175.0,0.9364853121956028,1,6,/casati8/kaggle-tps2022-may-fastai-baseline,Tabular Playground Series - May 2022
7226,94655056,188.0,0.9852431952199288,0,6,/rhythmcam/tps-may-22-xgboost-simple-baseline,Tabular Playground Series - May 2022
7227,94655056,188.0,0.9852431952199288,0,6,/rhythmcam/tps-may-22-xgboost-simple-baseline,Tabular Playground Series - May 2022
7228,95067859,194.0,,19,67,/calebreigada/getting-started-eda-preprocessing,Tabular Playground Series - May 2022
7229,97049905,205.0,0.9978896391967071,0,2,/kottoz/tps-may22-pytorch,Tabular Playground Series - May 2022
7230,96575397,214.0,,0,0,/guptadikshant/tps-may-2022,Tabular Playground Series - May 2022
7231,95982419,222.0,,2,1,/alfamame/tps-may-2022-ann,Tabular Playground Series - May 2022
7232,97046802,224.0,0.996398890134056,0,0,/nickmhnk/tps-may-2022-bilstm-overkill-experiment,Tabular Playground Series - May 2022
7233,96337071,235.0,,4,8,/arnavr10880/tps-may-22-tensorflow-decision-forests,Tabular Playground Series - May 2022
7234,94489899,238.0,,2,11,/raviista/tpsmay22-art-of-eda,Tabular Playground Series - May 2022
7235,97122299,241.0,0.9967174812107704,0,0,/bvarkoly/tabular-playground-2022-may,Tabular Playground Series - May 2022
7236,95516573,242.0,,0,11,/prashantpathak244/basic-xgboost-implementation,Tabular Playground Series - May 2022
7237,96144240,246.0,,0,0,/rohitmohite/my-first-edition-tabular-playground,Tabular Playground Series - May 2022
7238,96145054,249.0,0.9730021498036976,1,7,/davidhammond/may-tp-xgboost-parameter-search,Tabular Playground Series - May 2022
7239,96760679,261.0,,6,26,/raj401/simple-clean-eda-tps-may,Tabular Playground Series - May 2022
7240,94640623,257.0,0.9925966472324956,9,23,/abhishek123maurya/tps-may-decoding-f-27,Tabular Playground Series - May 2022
7241,96436518,274.0,,22,18,/aryanml007/tps-may-2022-xgb-nn,Tabular Playground Series - May 2022
7242,97063100,269.0,0.997108187946075,22,47,/akioonodera/tps-may2022-lgbm-binary,Tabular Playground Series - May 2022
7243,95248610,277.0,0.9966801149667092,0,1,/njhzzz/nn-6-minutes-0-99689,Tabular Playground Series - May 2022
7244,96070128,281.0,,0,3,/robertturro/tps-may-2022-eda-feature-selection,Tabular Playground Series - May 2022
7245,94491719,278.0,,1,4,/waldemar/pca-and-mi,Tabular Playground Series - May 2022
7246,96008466,287.0,0.9968996431204864,0,1,/werus23/tps-may2022,Tabular Playground Series - May 2022
7247,94782494,303.0,0.9968713447824736,3,28,/sfktrkl/tps-may-2022-nn,Tabular Playground Series - May 2022
7248,94845299,300.0,0.996857340903926,0,3,/mohammg/tabular-playground-series-may-2022-firststep,Tabular Playground Series - May 2022
7249,94978923,301.0,,0,6,/rsarten/may22-graphs-and-correlations,Tabular Playground Series - May 2022
7250,96810774,308.0,,4,26,/shagkala/eda-detailed-feature-interactions-shap,Tabular Playground Series - May 2022
7251,95796999,326.0,0.9966227443756718,3,7,/guillermofantoni/tabular-playground-series-binary-classification,Tabular Playground Series - May 2022
7252,97096678,320.0,0.9965663867396052,2,7,/x1akshay/tabular-playground-eda-binary-n-network,Tabular Playground Series - May 2022
7253,95639547,312.0,0.9782310288188808,0,2,/hosseinbehjat/tps-may-22-lgbm-optuna,Tabular Playground Series - May 2022
7254,97169265,315.0,,2,7,/palsouradip/tableplaygroundmay22-xgb-lgbm-fastai-nn,Tabular Playground Series - May 2022
7255,97080350,317.0,0.9900342548104792,0,6,/m1y7k8/tps-may-2022-eda-dtc-rfc-lgb-xgb,Tabular Playground Series - May 2022
7256,95156625,330.0,0.9936506000335974,1,4,/nguu0123/beginner-s-eda-fe-lgbm,Tabular Playground Series - May 2022
7257,98621386,335.0,,3,1,/soanmo/tpseries-may-2022-best-score,Tabular Playground Series - May 2022
7258,97092006,331.0,0.9962897574088876,2,8,/neerajkaroshi/tpsmay22,Tabular Playground Series - May 2022
7259,117157644,347.0,,3,15,/ritzig/feature-interaction-tutorial-pdp-shap-ensemble-mod,Tabular Playground Series - May 2022
7260,95307952,357.0,0.944232499300037,2,5,/rajnishkumar546/tps-may,Tabular Playground Series - May 2022
7261,95226074,359.0,0.9956629918833042,1,16,/lovroselic/may2022-ls,Tabular Playground Series - May 2022
7262,95226074,359.0,0.9956629918833042,1,16,/lovroselic/may2022-ls,Tabular Playground Series - May 2022
7263,94812735,356.0,0.9070339551060111,3,7,/harshul23/tps-may-22-eda-interactions-catboost,Tabular Playground Series - May 2022
7264,94786876,364.0,,0,4,/bhavesh0124/basic-eda-with-insights-beginner,Tabular Playground Series - May 2022
7265,96366338,363.0,0.9954464152750496,1,4,/motchan/lightgbm-kfold-optuna-tuning,Tabular Playground Series - May 2022
7266,97073734,399.0,0.9933591321610452,6,19,/cid007/tpmay,Tabular Playground Series - May 2022
7267,97128447,408.0,0.9925151697342752,4,20,/ninamaamary/neural-network-tps-05-2022,Tabular Playground Series - May 2022
7268,97143027,414.0,0.9924608807921504,3,3,/yasseinmahmoud/eda-feature-engineering-nn-prediction-may-2022,Tabular Playground Series - May 2022
7269,97143027,414.0,0.9924608807921504,3,3,/yasseinmahmoud/eda-feature-engineering-nn-prediction-may-2022,Tabular Playground Series - May 2022
7270,95082844,424.0,0.975023802512788,2,4,/jagofc/tps-may-2022-lgbm-baseline-in-r,Tabular Playground Series - May 2022
7271,135566154,436.0,,0,5,/anirudhg15/single-model-tps-may-2022-w-xgb-w-b,Tabular Playground Series - May 2022
7272,97100503,442.0,0.9914003187388342,0,3,/leesstephanie/tps-may-22-many-models-almost-same-results,Tabular Playground Series - May 2022
7273,95595702,460.0,,0,2,/welkin10/tpsmay22-lgbm-tuned-solution,Tabular Playground Series - May 2022
7274,96242604,446.0,0.9909635698149026,0,0,/shivanisinghal/tps-may22-tf-decision-forest,Tabular Playground Series - May 2022
7275,95546964,449.0,,8,45,/paultimothymooney/getting-started-with-tensorflow-decision-forests,Tabular Playground Series - May 2022
7276,96045115,466.0,0.9905743662741509,0,0,/chantom/fi-f-27-fe-optuna-lgbm,Tabular Playground Series - May 2022
7277,96346487,476.0,0.9899455482675096,0,3,/jiprud/tps-may22-xgb-classsifier,Tabular Playground Series - May 2022
7278,97142916,495.0,0.9880742026538756,9,11,/une510/tps-may-2022-lgbm-targetencoder-optuna,Tabular Playground Series - May 2022
7279,95775309,494.0,,0,0,/reenarajendraprasad/tabularbinaryclass-may,Tabular Playground Series - May 2022
7280,99292353,499.0,,0,4,/fajerbolt/tps-may-2022-final-summary-notebook,Tabular Playground Series - May 2022
7281,95026185,502.0,0.9848073242436814,0,0,/kaaveland/tps202205-quick-and-dirty-eda,Tabular Playground Series - May 2022
7282,96294728,507.0,0.985370181933235,1,7,/vvekparmar/tabular-playground-series-may2022,Tabular Playground Series - May 2022
7283,97366411,506.0,,1,1,/juanromera/tabular-playground-series-may-2022,Tabular Playground Series - May 2022
7284,95109439,513.0,0.9859027203287702,0,3,/ashokkumargarain/notebook457bf07179,Tabular Playground Series - May 2022
7285,97250612,524.0,,0,1,/janamejay97/tps-may-22,Tabular Playground Series - May 2022
7286,94757802,531.0,,0,3,/jhotor/eda-of-dataset,Tabular Playground Series - May 2022
7287,96824152,530.0,,0,6,/sawsanshakir/notebook-playground,Tabular Playground Series - May 2022
7288,94847546,532.0,,13,32,/sathyakrishnan12/kaggle-tps-may-22,Tabular Playground Series - May 2022
7289,96104157,538.0,0.9807227513312092,3,13,/sv7productions/tabular-playground-series-may-2022,Tabular Playground Series - May 2022
7290,96810873,540.0,0.980289764346801,0,0,/floopybits/lgbm-optuna,Tabular Playground Series - May 2022
7291,95100670,542.0,,1,8,/ted0071/tps-may-2022-eda-catboost,Tabular Playground Series - May 2022
7292,97141862,541.0,,0,4,/jamesmcguigan/tps-may-2022-lightgbm-regression,Tabular Playground Series - May 2022
7293,119757465,545.0,,20,44,/ninjaac/tpsmay22-logestic-reg-all-you-need-to-know,Tabular Playground Series - May 2022
7294,97134798,559.0,0.9733493599733212,0,7,/jbm1966/h2o-gbm-test,Tabular Playground Series - May 2022
7295,95179689,569.0,0.8256726217989679,3,5,/utkarshshukla2912/random-forest-baseline-classification,Tabular Playground Series - May 2022
7296,96269195,580.0,,0,0,/yamachan/tps22may-lgbmprac,Tabular Playground Series - May 2022
7297,95410719,582.0,,32,30,/yuyougnchan/numeric-variable-end-with-this,Tabular Playground Series - May 2022
7298,97099785,587.0,0.9707781506447196,6,11,/mukeshrajm/tps-may-2022-neuralnets-fastai-hgboost-r-forest,Tabular Playground Series - May 2022
7299,96486714,595.0,0.9677846513323608,0,0,/samuelsaintomer/notebook54062b4623,Tabular Playground Series - May 2022
7300,94549122,599.0,,0,6,/leo45890/tps-may-2022-eda-baseline-model,Tabular Playground Series - May 2022
7301,95270659,607.0,0.9628890474629704,1,8,/muki2003/may-2022-tabular-playground-deep-learning,Tabular Playground Series - May 2022
7302,95241845,611.0,,0,0,/ijcrook/tps-may-22-eda-and-catboost-model,Tabular Playground Series - May 2022
7303,97128547,622.0,0.959015197206757,15,17,/imnaho/eda-predict-with-lgbmclassifier,Tabular Playground Series - May 2022
7304,97189793,625.0,,1,4,/izainab/tps22-may-keras,Tabular Playground Series - May 2022
7305,95745994,629.0,,10,9,/akanshakhandelwal08/may-tps-22-xgboost-gridsearchcv,Tabular Playground Series - May 2022
7306,96222971,637.0,,0,2,/peressim/tps-may-2022-eda,Tabular Playground Series - May 2022
7307,96962483,654.0,0.9464228762402414,0,0,/hastingssibanda/tpsmay2022-hs2,Tabular Playground Series - May 2022
7308,96091640,656.0,0.945602348286287,1,10,/ayushjain001/tabular-playground-may2022,Tabular Playground Series - May 2022
7309,94744837,674.0,,0,6,/wasshoiwasshoi/tps-2022-may-with-automl-pycaret1,Tabular Playground Series - May 2022
7310,94564185,679.0,0.8598917477205007,0,5,/gavisr/let-s-get-started-with-the-lgbm-classifier,Tabular Playground Series - May 2022
7311,94467021,681.0,0.93831112112232,2,14,/saurabhshahane/baseline-with-h2o-automl,Tabular Playground Series - May 2022
7312,96365311,688.0,,4,14,/sanjaylalwani/tps-may22,Tabular Playground Series - May 2022
7313,95891563,708.0,,0,0,/bumstern/eda-tps-may-2022,Tabular Playground Series - May 2022
7314,94530055,714.0,0.860827258998955,0,3,/goldchildbright/tabnet-baseline,Tabular Playground Series - May 2022
7315,95055978,719.0,0.9300469536359324,5,15,/kimchanyoung/tps-may-2022-baseline-with-automl,Tabular Playground Series - May 2022
7316,101281939,729.0,0.9952550506521576,0,2,/zhangcheche/tabular-202205-baseline,Tabular Playground Series - May 2022
7317,94891282,747.0,0.9204560621336776,0,6,/ranjeetshrivastav/tps-may-22-catboost,Tabular Playground Series - May 2022
7318,95033660,748.0,0.9199951084748218,1,9,/shimjongsoo/tps-may22-catboost-automl,Tabular Playground Series - May 2022
7319,95033660,748.0,0.9188310008363036,1,9,/shimjongsoo/tps-may22-catboost-automl,Tabular Playground Series - May 2022
7320,121451745,750.0,,4,27,/gregoryoliveira/tabular-playground-series-may-2022,Tabular Playground Series - May 2022
7321,94615034,770.0,0.8706305473879391,0,4,/amarloni/tps-may2022,Tabular Playground Series - May 2022
7322,94615034,770.0,0.8611219982712104,0,4,/amarloni/tps-may2022,Tabular Playground Series - May 2022
7323,95462353,773.0,,0,1,/itsabhijith/tabular-playground-series-may-2022,Tabular Playground Series - May 2022
7324,94486180,777.0,0.9114677982251692,0,7,/adwaitkesharwani/simple-prediction-using-xgboost,Tabular Playground Series - May 2022
7325,95055840,787.0,0.9072393133993388,1,10,/wonjinkim1010/tps-5-le-rf,Tabular Playground Series - May 2022
7326,97189183,794.0,,0,2,/aleespinosa/learning-pyspark-with-may22-tps,Tabular Playground Series - May 2022
7327,94708121,797.0,0.9050639098581368,1,2,/ceruttivini/tpsmay22-eda-random-forest-w-tuning,Tabular Playground Series - May 2022
7328,96026049,812.0,0.8584011985166725,0,8,/wajidhassanmoosa/tabular-playground-series-may-2022-xgb,Tabular Playground Series - May 2022
7329,114520700,815.0,,0,1,/kartikeychauhan/tabular-playground-series-may-2022,Tabular Playground Series - May 2022
7330,94623621,823.0,0.891941130398935,4,16,/venkatkumar001/fast-ai-1,Tabular Playground Series - May 2022
7331,94623621,823.0,0.891941130398935,4,16,/venkatkumar001/fast-ai-1,Tabular Playground Series - May 2022
7332,96089131,826.0,,2,5,/nikhilsharma24/tps-may-python-f-27-only,Tabular Playground Series - May 2022
7333,94495026,839.0,,1,8,/charlottetu/playground-may-eda-in-r,Tabular Playground Series - May 2022
7334,94458627,842.0,,0,6,/stpeteishii/tps0522-data-histplot,Tabular Playground Series - May 2022
7335,97149913,845.0,,2,10,/flaviocavalcante/tps-may-22-just-eda,Tabular Playground Series - May 2022
7336,95067070,848.0,,1,14,/jeonghyunha/tps-may-2022-simple-eda-automl,Tabular Playground Series - May 2022
7337,96545358,852.0,,0,3,/nitibbgg/simple-tutorial-for-beginner-gradientboosting,Tabular Playground Series - May 2022
7338,95208743,865.0,,0,0,/shashankkumar1234567/shashank-kumar,Tabular Playground Series - May 2022
7339,96931053,894.0,0.8537119628431555,0,1,/tariqchhussain/xgbclassifier-optuna-k-fold-tps-may-22,Tabular Playground Series - May 2022
7340,95094042,902.0,,0,0,/luckychitundu/tabular-playgrounds-3-models-in-1,Tabular Playground Series - May 2022
7341,95238581,910.0,,7,9,/zwartfreak/easiest-tps-analysis-prediction-85-initial-acc,Tabular Playground Series - May 2022
7342,96262100,914.0,,2,5,/ashishkattel/simple-approach-random-forest-logistic-regression,Tabular Playground Series - May 2022
7343,97119495,927.0,,7,13,/rcoletto/tps-may-2022-eda-logistic-regression-rf,Tabular Playground Series - May 2022
7344,96465755,942.0,,1,6,/btharunkumar/playround-series-may-2022,Tabular Playground Series - May 2022
7345,99625579,988.0,0.979714527720002,1,5,/ahmedtoba/xgb-rf-knn-lgbm,Tabular Playground Series - May 2022
7346,95374963,1020.0,,0,2,/hughwinston/naive-bayes-quick-baseline,Tabular Playground Series - May 2022
7347,96092309,1041.0,,1,11,/sarthak333/tabular-series-may,Tabular Playground Series - May 2022
7348,95361373,1042.0,,4,10,/dcrowd/tpa-may-binarysearch-eda-fe-preliminary-logistic,Tabular Playground Series - May 2022
7349,95331917,1058.0,0.6130401977434861,1,1,/tracyporter/may-22-binary-classification,Tabular Playground Series - May 2022
7350,99840020,1062.0,,2,11,/srivnaman/logistic-rf-lightgbm,Tabular Playground Series - May 2022
7351,96305625,1073.0,,6,21,/arunasivapragasam/tps-may-2022-easiest-xgboost,Tabular Playground Series - May 2022
7352,96645328,1082.0,0.544680980457294,0,1,/r0hn00/tps-may22,Tabular Playground Series - May 2022
7353,96782007,1114.0,0.5002530561476725,0,0,/bbrown44/tabular-playground-series-may-2022bb,Tabular Playground Series - May 2022
7354,94633586,5.0,,12,140,/saitodevel01/gsdc2-baseline-submission,Google Smartphone Decimeter Challenge 2022
7355,102223020,11.0,,1,8,/forcewithme/gsdc2022-get-the-score-on-training-set,Google Smartphone Decimeter Challenge 2022
7356,94627409,32.0,,1,10,/columbia2131/gsdc2-phones-mean-but-test-isn-t-improved,Google Smartphone Decimeter Challenge 2022
7357,94960256,39.0,4.376327434480694,1,63,/ravishah1/gsdc2-savgol-filter-outlier-removal-with-bo,Google Smartphone Decimeter Challenge 2022
7358,96654472,95.0,,2,4,/kthimuo/2022-reproducing-baseline-wls-on-one-measurement,Google Smartphone Decimeter Challenge 2022
7359,102091012,548.0,2.8873634231347967,0,7,/roniheka/it-is-better-to-average-isrbmeters,Google Smartphone Decimeter Challenge 2022
7360,102091012,548.0,2.8873634231347967,0,7,/roniheka/it-is-better-to-average-isrbmeters,Google Smartphone Decimeter Challenge 2022
7361,101232681,83.0,2.9974950398985314,1,20,/tanxxx/vote-coordinate-with-nearestneighbor-new,Google Smartphone Decimeter Challenge 2022
7362,99751101,89.0,,0,4,/tyonemoto/gsdc2-baseline-sub,Google Smartphone Decimeter Challenge 2022
7363,100935465,286.0,2.9986552904297947,3,48,/cbeaud/gsdc22-coordinate-with-nearestneighbors-v2,Google Smartphone Decimeter Challenge 2022
7364,100233125,414.0,3.0008608820575886,19,64,/mehrankazeminia/gsdc22-coordinate-with-nearestneighbors,Google Smartphone Decimeter Challenge 2022
7365,102052115,304.0,2.9951838729550206,1,5,/rm1000/improved-coordinate-with-nearestneighbor,Google Smartphone Decimeter Challenge 2022
7366,95237214,311.0,,3,22,/tensorchoko/google-smartphone-2022-eda-en-jp,Google Smartphone Decimeter Challenge 2022
7367,101209944,366.0,,0,7,/slowlearnermack/gsdc22-coordinate-with-nearestneighbors,Google Smartphone Decimeter Challenge 2022
7368,94738473,373.0,,0,16,/foolishboi/gsdc22-eda-mapping,Google Smartphone Decimeter Challenge 2022
7369,100172750,213.0,3.00484468670209,1,21,/mohammadnaif/gsdc22-coordinate-with-nearestneighbors,Google Smartphone Decimeter Challenge 2022
7370,94907665,236.0,,2,9,/ollibolli/simple-exploration-adapted-from-last-year,Google Smartphone Decimeter Challenge 2022
7371,95951526,295.0,,0,14,/lunapandachan/google-smartphone-eda,Google Smartphone Decimeter Challenge 2022
7372,96023379,254.0,,4,40,/junkoda/deriving-baseline-wls-positions-in-progress,Google Smartphone Decimeter Challenge 2022
7373,94598972,408.0,17445.208056964733,0,11,/rsobtt/simple-lightgbm,Google Smartphone Decimeter Challenge 2022
7374,99045194,452.0,,0,2,/itrieu/gsdc2-data-analysis,Google Smartphone Decimeter Challenge 2022
7375,94941504,456.0,,2,7,/ilyaryabov/pytorch-model-for-correcting-results-of-gsdc2,Google Smartphone Decimeter Challenge 2022
7376,95415756,476.0,4.581842059048976,1,28,/dienhoa/where-is-my-phone-kalman-filter-optuna,Google Smartphone Decimeter Challenge 2022
7377,95888603,571.0,4.870011132291731,2,35,/dehokanta/visualize-public-and-private-trips,Google Smartphone Decimeter Challenge 2022
7378,95669255,501.0,,0,1,/ruslanbredun/google-smartphone-decimeter-challenge-2022,Google Smartphone Decimeter Challenge 2022
7379,98657242,3.0,,3,31,/yufuin/ai4code-linearity-of-kendall-s-tau-english,Google AI4Code – Understand Code in Python Notebooks
7380,96173012,13.0,,32,84,/yuanzhezhou/ai4code-distilbert-inference-777,Google AI4Code – Understand Code in Python Notebooks
7381,101370104,14.0,,2,6,/leehann/stronger-baseline-with-code-cells-ds,Google AI4Code – Understand Code in Python Notebooks
7382,103016148,15.0,,1,28,/snaker/new-rank,Google AI4Code – Understand Code in Python Notebooks
7383,100623643,28.0,,0,0,/conan1024/ai4code-baseline,Google AI4Code – Understand Code in Python Notebooks
7384,101081766,41.0,0.8626541886821534,0,0,/dunglt/inference-pct-rank-model,Google AI4Code – Understand Code in Python Notebooks
7385,102577979,48.0,,0,0,/omargamal064/graphcodebert-parwise,Google AI4Code – Understand Code in Python Notebooks
7386,101188537,56.0,,10,26,/kojimar/ai4code-pytorch-graphcodebert,Google AI4Code – Understand Code in Python Notebooks
7387,101559178,66.0,,2,3,/ikaroskaggle/mbert-ai4code-tf-tpu-codebert-data-preparation,Google AI4Code – Understand Code in Python Notebooks
7388,95645831,80.0,,0,14,/leolu1998/ai4code-deberta-inference,Google AI4Code – Understand Code in Python Notebooks
7389,98937910,82.0,,0,3,/hwsson/notebook766960e148,Google AI4Code – Understand Code in Python Notebooks
7390,100986452,94.0,,2,3,/oscarrangel/pairwise-training,Google AI4Code – Understand Code in Python Notebooks
7391,104596254,96.0,,80,527,/vad13irt/optimization-approaches-for-transformers,Google AI4Code – Understand Code in Python Notebooks
7392,101028378,107.0,,1,3,/msinger007/ai4code-tf-tpu-distilbert-data-preparation,Google AI4Code – Understand Code in Python Notebooks
7393,104739487,109.0,,0,3,/kirderf/ai4code-with-languages-translation,Google AI4Code – Understand Code in Python Notebooks
7394,97492725,135.0,,1,4,/happycube/ai4code-training-data-pre-processor,Google AI4Code – Understand Code in Python Notebooks
7395,98134923,151.0,,6,21,/haithamaliryan/ai4code-extract-all-functions-variables-names,Google AI4Code – Understand Code in Python Notebooks
7396,117239390,214.0,,2,6,/nguynthhi/model-v5,Google AI4Code – Understand Code in Python Notebooks
7397,100705853,294.0,,1,6,/congduyvu2103/ai4code,Google AI4Code – Understand Code in Python Notebooks
7398,98044674,337.0,,1,1,/trex99/ai4code-create-features-v900-codebert,Google AI4Code – Understand Code in Python Notebooks
7399,100173321,376.0,,0,10,/mohammadnaif/ai4code-pairwise-bertsmall-inference,Google AI4Code – Understand Code in Python Notebooks
7400,100858476,393.0,0.8257502059060106,0,0,/pypiahmad/ai4code-pairwise-bertsmall-inference,Google AI4Code – Understand Code in Python Notebooks
7401,95593177,397.0,,3,15,/cocoshe/how-to-hf-a-mini-template-to-start-big-models,Google AI4Code – Understand Code in Python Notebooks
7402,95428117,423.0,,0,3,/jdoesv/flax-code-embeddings-usage,Google AI4Code – Understand Code in Python Notebooks
7403,98353633,427.0,,0,9,/vincentwang25/real-benchmark-shuffle-markdown-cell-only,Google AI4Code – Understand Code in Python Notebooks
7404,99505438,451.0,,0,0,/nguyentanvietk15hl/ai4code-pairwise-bertsmall-inference,Google AI4Code – Understand Code in Python Notebooks
7405,96521306,461.0,0.8385202895688737,22,135,/suicaokhoailang/stronger-baseline-with-code-cells,Google AI4Code – Understand Code in Python Notebooks
7406,95411997,511.0,,1,7,/ilyaryabov/eda-collecting-training-dataset,Google AI4Code – Understand Code in Python Notebooks
7407,97391784,538.0,,7,31,/swaralipibose/a-detailed-eda-position-analysis,Google AI4Code – Understand Code in Python Notebooks
7408,100844678,574.0,0.8257502059060106,0,22,/mohdmuttalib/ai4code-pairwise-bertsmall-inference,Google AI4Code – Understand Code in Python Notebooks
7409,101700890,587.0,,0,3,/thaihocmap123/competition-ai4code,Google AI4Code – Understand Code in Python Notebooks
7410,97971156,595.0,,19,47,/nickuzmenkov/ai4code-tensorflow-distilbert-baseline,Google AI4Code – Understand Code in Python Notebooks
7411,101306131,602.0,,4,4,/readoc/ai4code-deberta-v3-large-train-and-infer,Google AI4Code – Understand Code in Python Notebooks
7412,99780215,610.0,0.8184378886325433,1,3,/tadashi123/ai4code-tf-tpu-codebert-inference,Google AI4Code – Understand Code in Python Notebooks
7413,100032183,612.0,,0,6,/hechtjp/ai4code-eda-as-binary-classification,Google AI4Code – Understand Code in Python Notebooks
7414,101241110,639.0,,1,2,/johnip/ai4code-tf-tpu-codebert-data-preparation,Google AI4Code – Understand Code in Python Notebooks
7415,95442527,710.0,,16,188,/aerdem4/ai4code-pytorch-distilbert-baseline,Google AI4Code – Understand Code in Python Notebooks
7416,101426692,715.0,,4,17,/robertrebor/training-using-crossencoder-with-sbert,Google AI4Code – Understand Code in Python Notebooks
7417,96124326,771.0,,1,15,/maunish/ai4code-some-random-stats,Google AI4Code – Understand Code in Python Notebooks
7418,95761401,807.0,,1,8,/aroksak/ai4code-languages-distribution,Google AI4Code – Understand Code in Python Notebooks
7419,102356026,825.0,0.6646822496977637,2,28,/ryanmuscle/an-approach-without-ml-libraries,Google AI4Code – Understand Code in Python Notebooks
7420,100744978,844.0,,2,3,/claree007/ai4code-dataset-analysis,Google AI4Code – Understand Code in Python Notebooks
7421,102884740,859.0,0.5691128075946806,1,12,/jazivxt/code-theory,Google AI4Code – Understand Code in Python Notebooks
7422,99419458,862.0,,2,5,/arunamenon/ai4code-eda-modelling,Google AI4Code – Understand Code in Python Notebooks
7423,97535924,892.0,0.6012338755123567,2,5,/harshwalia/ai4code-v1-easy-explanation-all-data,Google AI4Code – Understand Code in Python Notebooks
7424,100912868,918.0,,2,10,/xodeum/google-al4code,Google AI4Code – Understand Code in Python Notebooks
7425,95400212,925.0,0.5910650181341784,0,6,/shilpagracev/notebooke207a94f5c,Google AI4Code – Understand Code in Python Notebooks
7426,99242471,956.0,0.5910650181341784,1,5,/santosh1974/ai4code-first,Google AI4Code – Understand Code in Python Notebooks
7427,103216158,972.0,,4,18,/corneliuskristianto/google-ai4code-reconstruct-the-order,Google AI4Code – Understand Code in Python Notebooks
7428,100703169,984.0,,0,1,/danieljeongkut/notebooka6b92f5e1e,Google AI4Code – Understand Code in Python Notebooks
7429,99670175,1002.0,0.5413131938791729,0,0,/kimnnm/roberta-base-inference,Google AI4Code – Understand Code in Python Notebooks
7430,97447783,1014.0,0.4203224945693795,0,0,/kayalvizhim/first-code,Google AI4Code – Understand Code in Python Notebooks
7431,104587959,1.0,,0,1,/patrick0302/lead-abnormal-viz,Large-scale Energy Anomaly Detection (LEAD)
7432,99491404,6.0,,25,131,/brandonhu0215/feedback-deberta-large-lb0-619,Feedback Prize - Predicting Effective Arguments
7433,97186446,14.0,0.6275962651955372,29,144,/abhishek/tez-for-feedback-v2-0,Feedback Prize - Predicting Effective Arguments
7434,103644405,22.0,,1,5,/nischaydnk/stacking-v1,Feedback Prize - Predicting Effective Arguments
7435,99137962,46.0,,0,1,/shreyasadhari123/deberta-data-512,Feedback Prize - Predicting Effective Arguments
7436,102745963,47.0,,0,27,/ducciow/feedbackprize-inference-for-token-classification,Feedback Prize - Predicting Effective Arguments
7437,100146669,71.0,,1,17,/mujrush/feedback2-word2vec-lightgbm,Feedback Prize - Predicting Effective Arguments
7438,98208707,70.0,,1,17,/arvissu/roberta-base-training-notebook-1-epoch,Feedback Prize - Predicting Effective Arguments
7439,103735074,72.0,0.6210301910845287,0,1,/ivesnx/inference-token-classification,Feedback Prize - Predicting Effective Arguments
7440,104031318,90.0,0.5972277826735398,1,5,/powercode/prompt-learning,Feedback Prize - Predicting Effective Arguments
7441,103657400,117.0,,2,1,/gwsuck/token-classification-approach-deberta-large,Feedback Prize - Predicting Effective Arguments
7442,103085266,144.0,,0,0,/jzjzjz123/baseline-with-huggingface-training-beginners,Feedback Prize - Predicting Effective Arguments
7443,104049029,170.0,0.6061155749848152,6,21,/mountpotatoq/autogluon-finetune-solutions,Feedback Prize - Predicting Effective Arguments
7444,101904535,146.0,0.6366276945170031,3,9,/chenghaozhe/notebookfa8a436bef,Feedback Prize - Predicting Effective Arguments
7445,104286355,147.0,,1,30,/yujikomi/feedbackprize2-train,Feedback Prize - Predicting Effective Arguments
7446,99148807,166.0,,4,11,/renokan/effectargs-checking-info-len-freq-count,Feedback Prize - Predicting Effective Arguments
7447,102555661,423.0,,0,2,/ryonryon8888/fbpe-deberta,Feedback Prize - Predicting Effective Arguments
7448,103287636,206.0,,10,49,/thedevastator/error-analysis-visualize-bert-s-attention,Feedback Prize - Predicting Effective Arguments
7449,96873172,222.0,0.7494688718410165,2,39,/imvision12/tensorflow-feedback-bert-baseline,Feedback Prize - Predicting Effective Arguments
7450,96873172,222.0,0.7387250573124421,2,39,/imvision12/tensorflow-feedback-bert-baseline,Feedback Prize - Predicting Effective Arguments
7451,98888790,450.0,,22,44,/manikanthgoud/feedback-prize-exploratory-data-analysis-eda,Feedback Prize - Predicting Effective Arguments
7452,98149110,471.0,,0,12,/murtadhayaseen/copetition1,Feedback Prize - Predicting Effective Arguments
7453,101360042,511.0,,5,9,/hugoya/pytorch-lightning-feedback-prediction,Feedback Prize - Predicting Effective Arguments
7454,103173494,497.0,0.7972726636941858,0,1,/kunduwang/bert-baseline,Feedback Prize - Predicting Effective Arguments
7455,103387880,412.0,0.7993838818631771,1,8,/legend507/baseline-classify-text-with-bert,Feedback Prize - Predicting Effective Arguments
7456,98815093,389.0,,1,1,/jitensharma597/feedback-prize-xlm-roberta,Feedback Prize - Predicting Effective Arguments
7457,101290317,589.0,,0,2,/nitsourish/distilbert-base-cased-baseline,Feedback Prize - Predicting Effective Arguments
7458,100664275,528.0,,0,6,/robber19/feedback-price-effectiveness-lgbm,Feedback Prize - Predicting Effective Arguments
7459,102419995,527.0,,0,12,/kosukeponi/data-augmentation,Feedback Prize - Predicting Effective Arguments
7460,102495770,604.0,,0,4,/corentinbonnefond/for-begginers,Feedback Prize - Predicting Effective Arguments
7461,101182981,663.0,,17,35,/morodertobias/feedback-prize-bert,Feedback Prize - Predicting Effective Arguments
7462,98719481,615.0,0.7897658685375721,4,18,/bhavesjain/train-logisticregression-fpe-sentencetransformer,Feedback Prize - Predicting Effective Arguments
7463,96694456,610.0,,2,6,/tegzes/predicting-effective-arguments-simple-eda,Feedback Prize - Predicting Effective Arguments
7464,101316421,669.0,,6,23,/elmetejon/starting-with-eda-logistic-model,Feedback Prize - Predicting Effective Arguments
7465,98167311,675.0,0.7168550568466833,1,3,/nkenyor/logisticregression-tfidf-5-folds-improved,Feedback Prize - Predicting Effective Arguments
7466,96582174,603.0,,1,7,/quincyqiang/fppea-exploratory-data-analysis,Feedback Prize - Predicting Effective Arguments
7467,101357980,653.0,,2,5,/bharadwajvedula/feedback-prize-tpu-roberta-training-fold-4,Feedback Prize - Predicting Effective Arguments
7468,100209525,792.0,0.7164457115510874,6,14,/ohmeow/deblurrta-a-baseline-using-fast-ai-and-blurr,Feedback Prize - Predicting Effective Arguments
7469,97858811,756.0,,3,15,/fanbyprinciple/baseline-bert-using-tensorflow,Feedback Prize - Predicting Effective Arguments
7470,100899561,798.0,0.7101549322238598,1,3,/lastofus111/fb-infer,Feedback Prize - Predicting Effective Arguments
7471,100991341,820.0,,0,0,/kaichixie/fpe-pytorch-train-deberta-v3-base,Feedback Prize - Predicting Effective Arguments
7472,109081502,836.0,,0,9,/raj26000/pytorch-feedback-siamese-deberta-base-training,Feedback Prize - Predicting Effective Arguments
7473,97247207,864.0,,2,6,/snnclsr/eda-feedback-prize-predicting-effect-arguments,Feedback Prize - Predicting Effective Arguments
7474,97212672,865.0,,15,145,/debarshichanda/pytorch-feedback-deberta-v3-baseline,Feedback Prize - Predicting Effective Arguments
7475,101976233,924.0,,8,25,/lau01b/feedback-prize-pretrained-training,Feedback Prize - Predicting Effective Arguments
7476,101245464,947.0,,1,8,/shaggy11/first-version-distilbert-training,Feedback Prize - Predicting Effective Arguments
7477,99400707,949.0,0.6831751358904703,0,0,/oliverlionado/infer-fpe2022-baseline,Feedback Prize - Predicting Effective Arguments
7478,96977150,976.0,,5,12,/tdh512194/simple-5-foldcv-deberta-baseline,Feedback Prize - Predicting Effective Arguments
7479,100634027,980.0,,2,29,/alvaroalbarrn/effective-arguments-eda,Feedback Prize - Predicting Effective Arguments
7480,103431781,1005.0,,1,4,/saansd2003/feedback-effeciveness-with-essay-text-using-ulmfit,Feedback Prize - Predicting Effective Arguments
7481,101604880,1034.0,0.707434869218055,0,3,/kuntalpal/feedback-prize-predicting-effective-arguments,Feedback Prize - Predicting Effective Arguments
7482,99881173,1057.0,,5,13,/muki2003/tpu-feedback-arugument-prediction-bert,Feedback Prize - Predicting Effective Arguments
7483,97758635,1071.0,0.7168550568466833,2,23,/kvsnoufal/logisticregression-tfidf-5-folds,Feedback Prize - Predicting Effective Arguments
7484,100109354,1076.0,0.7168550568466833,0,3,/santosh1974/feedback-price-effectiveness-first,Feedback Prize - Predicting Effective Arguments
7485,100109354,1076.0,0.7168550568466833,0,3,/santosh1974/feedback-price-effectiveness-first,Feedback Prize - Predicting Effective Arguments
7486,100109354,1076.0,0.7168550568466833,0,3,/santosh1974/feedback-price-effectiveness-first,Feedback Prize - Predicting Effective Arguments
7487,101958080,1098.0,,7,11,/inagana/simple-eda-and-insights-for-beginners-with-seaborn,Feedback Prize - Predicting Effective Arguments
7488,96513799,1089.0,0.7208578017591872,7,248,/tanlikesmath/feedback-prize-effectiveness-eda-deberta-baseline,Feedback Prize - Predicting Effective Arguments
7489,101831015,1105.0,,0,0,/tonylek/lingo-notebook2,Feedback Prize - Predicting Effective Arguments
7490,103305018,1096.0,0.7917955574574036,1,0,/abduygur/sklearn-randomforestclassifier,Feedback Prize - Predicting Effective Arguments
7491,101056283,1167.0,,3,8,/athews/effective-ineffective-or-adequate-a-study,Feedback Prize - Predicting Effective Arguments
7492,103556134,1097.0,0.963767934370258,2,2,/datakite/discourse-effectiveness-ratings-pred-using-keras,Feedback Prize - Predicting Effective Arguments
7493,100141104,1138.0,,22,39,/venkatkumar001/nlpstarter-3-simple-ml-baseline-algo-with-kfold,Feedback Prize - Predicting Effective Arguments
7494,97082777,1154.0,,6,10,/himanshutripathi/in-depth-eda-interactive-visualization,Feedback Prize - Predicting Effective Arguments
7495,102788094,1164.0,0.8250387385348993,0,2,/jellynexus/feedbackprize-nkh,Feedback Prize - Predicting Effective Arguments
7496,102952914,1215.0,1.1961445160890511,0,2,/chickenugget/predicting-effective-argument-using-lst-model,Feedback Prize - Predicting Effective Arguments
7497,101230993,1228.0,,0,4,/ravikumarmn/feedback-prize-effectiveness-tensorflow-hub,Feedback Prize - Predicting Effective Arguments
7498,97897872,1200.0,0.8358659878224918,0,6,/ajeetsingh17/ann-with-tensorflow-tokenizer,Feedback Prize - Predicting Effective Arguments
7499,99985590,1234.0,0.8023804772109489,0,3,/filippobuonco95/tfidf-neuralnet,Feedback Prize - Predicting Effective Arguments
7500,104408296,1239.0,,0,13,/fengqilong/replication-of-the-basics-of-top-1-solution,Feedback Prize - Predicting Effective Arguments
7501,97030203,1264.0,0.7931386213337973,1,6,/afajohn/no-text-baseline,Feedback Prize - Predicting Effective Arguments
7502,102107041,1273.0,0.7895599330610673,0,1,/avilaqba/firstdraft,Feedback Prize - Predicting Effective Arguments
7503,103269901,1261.0,0.7903603393243803,2,3,/lordxerxes/feedback-argument-competition,Feedback Prize - Predicting Effective Arguments
7504,103859564,1271.0,,0,1,/karlpetz/student-feedback-eda-nlp-model,Feedback Prize - Predicting Effective Arguments
7505,102463138,1257.0,0.7951106436597195,0,3,/sstanou/bert-case-dense-layer,Feedback Prize - Predicting Effective Arguments
7506,101421792,1290.0,0.8000268481037804,0,4,/krishnendudakshi02/transformer-from-scratch,Feedback Prize - Predicting Effective Arguments
7507,103167409,1297.0,1.084502161062325,1,3,/petergeorgebeidler/very-simple-tfidf-linreg,Feedback Prize - Predicting Effective Arguments
7508,100344405,1302.0,1.0112653911206182,1,5,/himanshubag/feedback-prize-simple-bert,Feedback Prize - Predicting Effective Arguments
7509,102785113,1321.0,,0,5,/aretma/fasttext,Feedback Prize - Predicting Effective Arguments
7510,100176043,1325.0,,0,2,/apoorvjha63/fork-of-feedbackclassification,Feedback Prize - Predicting Effective Arguments
7511,96668202,1342.0,0.9559010265698052,1,1,/psmart/very-simple-predictions-end-to-end,Feedback Prize - Predicting Effective Arguments
7512,100046729,1356.0,14.115386801165156,1,2,/afsahulsyed/knn-without-balance,Feedback Prize - Predicting Effective Arguments
7513,100960021,1355.0,,1,5,/ashokkumargarain/notebooka39e,Feedback Prize - Predicting Effective Arguments
7514,102415635,1354.0,0.8580860262258717,0,0,/shree321/bert-base-cased,Feedback Prize - Predicting Effective Arguments
7515,96502914,1366.0,,1,5,/ilyaryabov/fasttext-supervised-classifier,Feedback Prize - Predicting Effective Arguments
7516,103852868,1373.0,0.882976588735612,0,0,/kristantotanusdjaja/notebook6a193b350b,Feedback Prize - Predicting Effective Arguments
7517,100820044,1412.0,,3,7,/vithal2311/feedback-prize-keras-with-hyperparameter-tuning,Feedback Prize - Predicting Effective Arguments
7518,102405780,1415.0,,0,0,/albert13541031274/feedback-price-distilbert-tf,Feedback Prize - Predicting Effective Arguments
7519,96703259,1419.0,,8,31,/mpwolke/feedback-prize-effectiveness-remix,Feedback Prize - Predicting Effective Arguments
7520,102524705,1433.0,0.9971860234497744,0,0,/rhitwijmukherjee/prizepred,Feedback Prize - Predicting Effective Arguments
7521,102793182,1446.0,,0,3,/evgensuit/predicting-effective-arguments-submission,Feedback Prize - Predicting Effective Arguments
7522,103152256,1449.0,1.0977083179063367,0,2,/vibhorsharma111/predictive-modelling-using-tensorflow-99-6-acc-rdf,Feedback Prize - Predicting Effective Arguments
7523,102031890,1460.0,,2,3,/harukiyasui/feedback-prize-eda,Feedback Prize - Predicting Effective Arguments
7524,99553405,1471.0,1.65452319120404,0,1,/hs9000/feedback-prize,Feedback Prize - Predicting Effective Arguments
7525,102509271,1470.0,,2,7,/feezakhankhanzada/training-bert-for-prediction-beginner,Feedback Prize - Predicting Effective Arguments
7526,99351121,1486.0,,3,8,/uditsharma72/feedback-prize-predicting-effective-arguments,Feedback Prize - Predicting Effective Arguments
7527,101906678,1503.0,3.2925932492714907,1,6,/gauravahujaravenclaw/feedback,Feedback Prize - Predicting Effective Arguments
7528,99237968,1504.0,1.877791254294339,2,8,/mustafakeser4/feedback-eda,Feedback Prize - Predicting Effective Arguments
7529,99407032,1512.0,,2,7,/wajidhassanmoosa/feedback-prize-effectiveness-nnlm-128,Feedback Prize - Predicting Effective Arguments
7530,103048213,1509.0,3.124663386526642,2,9,/akashsdevbanshi/tensorflow-model-using-lstm-and-conv-layer-85-acc,Feedback Prize - Predicting Effective Arguments
7531,100811346,1515.0,2.092110475344697,5,21,/adrinhernndezs/feedback-price-effectiveness-logisticregression,Feedback Prize - Predicting Effective Arguments
7532,100470263,1532.0,3.2741090812689,1,10,/dhirendra73/starter-tfidf-xgboost-to-glove-bilstm,Feedback Prize - Predicting Effective Arguments
7533,98407998,1544.0,,1,2,/tracyporter/effective-argument-spacy,Feedback Prize - Predicting Effective Arguments
7534,112682663,1549.0,,34,94,/eisgandar/predicting-effective-arguments,Feedback Prize - Predicting Effective Arguments
7535,99798033,1552.0,13.517360546248655,0,4,/devanshu12122/feedback-prize-using-xg-boost,Feedback Prize - Predicting Effective Arguments
7536,106433805,1557.0,,2,14,/riteshsinha/tutorial-on-nlp-techniques-and-transformers,Feedback Prize - Predicting Effective Arguments
7537,97852657,5.0,,9,63,/zakopur0/adversarial-validation-private-vs-public,American Express - Default Prediction
7538,104136970,19.0,,2,20,/fritzcremer/amex-shakeup,American Express - Default Prediction
7539,97034822,14.0,,39,252,/cdeotte/tensorflow-gru-starter-0-790,American Express - Default Prediction
7540,97521140,133.0,,20,110,/gopidurgaprasad/amex-credit-score-model,American Express - Default Prediction
7541,96657840,10.0,,4,16,/jiweiliu/fast-eda-using-rapids-cudf,American Express - Default Prediction
7542,96745201,263.0,,0,7,/mohammadrahmati/understanding-the-evaluation-metric-g-and-d,American Express - Default Prediction
7543,98542463,24.0,,15,77,/pavelvod/amex-eda-revealing-time-patterns-of-features,American Express - Default Prediction
7544,96867344,173.0,0.7848847799878735,0,2,/werus23/amex-lightgbm-eda,American Express - Default Prediction
7545,103725323,105.0,,1,13,/pabuoro/amex-ultra-fast-adversarial-validation-shap,American Express - Default Prediction
7546,97329957,64.0,,49,538,/ambrosm/amex-eda-which-makes-sense,American Express - Default Prediction
7547,102438766,289.0,,0,0,/hideyukizushi/amex-train-rnn-gru-e10-changelr,American Express - Default Prediction
7548,103215519,102.0,,1,6,/viictte/xgboost-pyramid-test-predictions,American Express - Default Prediction
7549,102236136,132.0,,0,2,/leointeresting/amex-submission-correlation,American Express - Default Prediction
7550,98478185,211.0,,3,12,/hinepo/public-x-private-plots,American Express - Default Prediction
7551,97651978,109.0,0.7884572302183207,1,12,/mavillan/amex-lightgbm-baseline-1,American Express - Default Prediction
7552,101920054,227.0,,0,7,/shigeeeru/tensorflow-cnn-starter-0-785,American Express - Default Prediction
7553,101547375,195.0,0.7996754048966648,0,5,/skloveyyp/amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7554,101547375,195.0,0.7996754048966648,0,5,/skloveyyp/amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7555,101547375,195.0,0.7996754048966648,0,5,/skloveyyp/amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7556,101547375,195.0,0.7996754048966648,0,5,/skloveyyp/amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7557,101547375,195.0,0.7996754048966648,0,5,/skloveyyp/amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7558,101547375,195.0,0.7996754048966648,0,5,/skloveyyp/amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7559,101065410,574.0,,3,20,/mpware/amex-categorials,American Express - Default Prediction
7560,101326225,193.0,0.7924943932666497,2,25,/yekenot/catboost-as-feature-selector,American Express - Default Prediction
7561,100911803,283.0,0.7949313730705166,6,27,/sansmurk/xgb-lgbm-stacking-model-with-lr,American Express - Default Prediction
7562,102908447,840.0,,22,42,/neeharikar/amex-eda-prediction-new,American Express - Default Prediction
7563,101823300,375.0,,27,75,/jakelj/amex-cnn-starter-data-image-prediction,American Express - Default Prediction
7564,102019454,495.0,,5,21,/sercanyesiloz/american-express-default-prediction-eda,American Express - Default Prediction
7565,100289972,1342.0,,2,17,/abdellatifsassioui/create-pickeld-data-from-50-gb-to-6gb,American Express - Default Prediction
7566,103292324,1614.0,0.7640189698717992,0,5,/amant555/ensemble-xg-boost-catboost-lightgbm-credit-default,American Express - Default Prediction
7567,96640402,387.0,,0,6,/kingychiu/amex-woe-baseline-with-id-encoded-fp16-dataset,American Express - Default Prediction
7568,100455775,1231.0,,1,8,/ewu1233/rapids-cudf-feature-engineering-xgb-4684de,American Express - Default Prediction
7569,103397803,1980.0,,3,7,/sskknt/en-jp-lightgbm-feature-importance,American Express - Default Prediction
7570,99754267,192.0,,30,38,/gehallak/the-dark-side-of-the-moon,American Express - Default Prediction
7571,103157183,157.0,,0,2,/ivanblch/amex-ptls-baseline-supervised-neural-networ-8f6d4b,American Express - Default Prediction
7572,97657524,45.0,,2,11,/roberthatch/amex-s2-feature-engg,American Express - Default Prediction
7573,101045325,796.0,,2,13,/nlztrk/faster-get-difference-multi-processing,American Express - Default Prediction
7574,98578069,1489.0,,0,15,/onodera1/amex-eda-comparison-of-training-and-test-data,American Express - Default Prediction
7575,102407097,1397.0,,0,15,,American Express - Default Prediction
7576,101409723,622.0,,0,3,/lihuiliu2000/amex-lgbm-dart-cv-0-7963,American Express - Default Prediction
7577,103282307,351.0,0.7886618420470005,0,6,/vmuzhichenko/amex-tensorflow-lstm-cnn,American Express - Default Prediction
7578,99418170,472.0,,2,13,/finlay/faster-lgbm-dart-with-tunned-parameter,American Express - Default Prediction
7579,97132599,474.0,0.7947160731446,7,16,/apoorvbhardwaj/amex-early-ensemble,American Express - Default Prediction
7580,103359935,429.0,,7,81,/heyspaceturtle/beware-the-spaceturtles,American Express - Default Prediction
7581,103759492,802.0,,0,7,/wanko5452/catboost-md-10-gpu-0-795-lb,American Express - Default Prediction
7582,100346831,287.0,,9,34,/illidan7/amex-permutation-feature-importance,American Express - Default Prediction
7583,104087336,1524.0,0.7992146310340682,24,62,/swimmy/tuffline-amex-anotherfeaturelgbm,American Express - Default Prediction
7584,103271680,997.0,,0,3,/baekseungyun/error-analysis-with-lgbm-dart,American Express - Default Prediction
7585,103999891,415.0,,0,0,/mhill17/learning-the-kaggle-ensembling-guide,American Express - Default Prediction
7586,100179587,717.0,,1,11,/shanggangli/baseline-lgbm,American Express - Default Prediction
7587,103026597,1191.0,0.7994441110236208,2,18,/zhaoxinyu0121/amex-feature-ensemble,American Express - Default Prediction
7588,101593619,611.0,,11,29,/cv13j0/amex-default-prediction-keras-starter,American Express - Default Prediction
7589,104121457,27.0,0.7997647646202698,0,0,/tatsumicrub/27th-place-amex-rank-ensemble,American Express - Default Prediction
7590,104531331,729.0,,1,17,/pyagoubi/amex-eda-evolvement-of-numeric-features-over-time,American Express - Default Prediction
7591,104065499,538.0,0.7997688188031611,0,0,/carlmaxace/exponential-ensemble,American Express - Default Prediction
7592,101256132,1609.0,,7,23,/translucen7/amex-deep-dive-time-series-eda,American Express - Default Prediction
7593,98977766,321.0,,0,2,/viktorfairuschin/amex-reduce-memory-usage,American Express - Default Prediction
7594,100431948,581.0,,2,12,/shusky/amex-relation-b-w-number-of-statements-default,American Express - Default Prediction
7595,103219782,166.0,,7,26,/jpison/custom-lgbm-obj-weighted-logloss-function,American Express - Default Prediction
7596,98727163,1278.0,,10,22,/raj401/visualize-the-learningratescheduler,American Express - Default Prediction
7597,100186375,540.0,0.7977807195269013,15,177,/thedevastator/lag-features-are-all-you-need,American Express - Default Prediction
7598,100966288,372.0,,1,25,/youheitomio/gpu-version-amex-lgbm-by-youhei-tomio,American Express - Default Prediction
7599,100203871,1565.0,0.7972301526034069,5,32,/seraquevence/ensemble-weighted-average-iii-0-797,American Express - Default Prediction
7600,101582613,255.0,0.1710539702023899,1,7,/ravisinghiitbhu/amex-with-categorical,American Express - Default Prediction
7601,102951881,546.0,0.7991351074053883,2,14,/zb1373/blend-boosting-study,American Express - Default Prediction
7602,104441469,438.0,,2,21,/kalelpark/amex-top10-solution,American Express - Default Prediction
7603,97187967,1264.0,,3,23,/mikhaildonskoy/eda-for-beginners-correlations-and-plots,American Express - Default Prediction
7604,100693068,1409.0,,0,7,/deepkun1995/amex-make-feature,American Express - Default Prediction
7605,102820046,1169.0,0.7997682073840863,3,52,/rusinisiyara/tuffline-submitions-01,American Express - Default Prediction
7606,114235717,714.0,,16,222,/datark1/american-express-eda,American Express - Default Prediction
7607,97201708,1427.0,0.7962922167669775,8,47,/beezus666/ensemble-weighted-average,American Express - Default Prediction
7608,103263648,1309.0,,2,18,/rayanaay/pyspark-is-all-you-need-simple-decision-tree,American Express - Default Prediction
7609,98949310,2403.0,,3,42,/sietseschrder/xgboost-starter-0-793,American Express - Default Prediction
7610,99909749,1385.0,,0,0,/delight669/amex-feature-engg-for-calssifiers,American Express - Default Prediction
7611,102078476,2314.0,0.7927928336981469,2,5,/hongyishao/amex-model-tuning-version4-stackingstrategyc,American Express - Default Prediction
7612,100528415,1247.0,,47,130,/devsubhash/amex-eda-default-prediction,American Express - Default Prediction
7613,101322601,836.0,0.7997128181807347,13,45,/slowlearnermack/amex-lgbm-dart-cv-0-7963-improved,American Express - Default Prediction
7614,101636425,1236.0,,2,11,/anubhavde/amex-prediction,American Express - Default Prediction
7615,98706533,338.0,,1,9,/kgxiao/null-feature-importances,American Express - Default Prediction
7616,104121251,1596.0,0.799515885503394,0,7,/imbikramsaha/tuffline-amex-using-lgbmclassifier,American Express - Default Prediction
7617,96786087,1645.0,,1,3,/nimamanaf/read-customer-data-using-their-unique-ids,American Express - Default Prediction
7618,103431552,1631.0,,0,0,/prem134/notebook7d501712fc,American Express - Default Prediction
7619,104137348,2633.0,,0,3,/youneseloiarm/xgboost-starter-30-70,American Express - Default Prediction
7620,101565623,1445.0,,0,16,/mohammadnaif/amex-ensemble-several-notebook-outputs,American Express - Default Prediction
7621,101337098,380.0,,0,1,/maheshak04/amex-understand-categorical-variables,American Express - Default Prediction
7622,97232202,391.0,,10,102,/datafan07/amex-where-to-begin,American Express - Default Prediction
7623,96869430,571.0,,2,19,/dynamic24/h2o-ai-automl-explain-results,American Express - Default Prediction
7624,105725113,2253.0,,0,2,/juixv3937/amex-pytorch-ignite-gru,American Express - Default Prediction
7625,99434769,1518.0,,0,9,/tensorchoko/american-express-eda,American Express - Default Prediction
7626,98804686,858.0,0.7973540141077824,51,209,/ragnar123/amex-lgbm-dart-cv-0-7963,American Express - Default Prediction
7627,101948970,917.0,,9,20,/vijayendrad/supervised-learning-with-amex-data,American Express - Default Prediction
7628,96742013,960.0,,0,7,/foolishboi/amex-simple-eda,American Express - Default Prediction
7629,102805314,973.0,,0,0,/jiapingwen/follow-amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7630,103656165,976.0,0.7793533861933508,1,6,/shuntakinami/xgboost-catboost-and-lightgbm-ensemble-model,American Express - Default Prediction
7631,100045947,1781.0,,0,0,/pham0030/ibm-coursera-clf-final-amex-default-prediction,American Express - Default Prediction
7632,98771455,1038.0,,2,6,/naiborhujosua/eda-modelling-evaluation,American Express - Default Prediction
7633,99894900,1079.0,,4,15,/ozoozo/amex-eda-1-first-glance,American Express - Default Prediction
7634,106378994,1089.0,,0,0,/samedimanchelundi/fork-of-amex-lgbm-dart-cv-0-7977,American Express - Default Prediction
7635,101411879,328.0,,3,13,/valteresj/create-1k-features-with-datatable,American Express - Default Prediction
7636,104146102,288.0,,0,1,/kdafke123141/feature-engineering-using-last-3-month,American Express - Default Prediction
7637,100086760,1115.0,,2,7,/sarang210/american-express-correlations,American Express - Default Prediction
7638,103346268,1538.0,,6,34,/hikarutabata/exponential-ensemble,American Express - Default Prediction
7639,102933825,1570.0,,0,2,/stgkrtua/amex-howtopreprocess-onkaggle,American Express - Default Prediction
7640,101179947,1299.0,0.7965248363211046,7,62,/romaupgini/statement-dates-to-use-or-not-to-use,American Express - Default Prediction
7641,98580105,1302.0,0.776101943263457,0,3,/rodrigostallsikora/1st-attempt-at-american-express-challenge,American Express - Default Prediction
7642,98667758,327.0,,0,3,/yamaich/amex-nacounts-train-and-test,American Express - Default Prediction
7643,103127346,1891.0,,0,5,/roniheka/ensemble-coordinate-different-preds-one-by-one,American Express - Default Prediction
7644,96760082,2084.0,0.700138683038009,3,26,/lucasmorin/amex-woe-baseline,American Express - Default Prediction
7645,98976414,1840.0,,5,13,/indynavarrovidal/eda-amex-default-prediction,American Express - Default Prediction
7646,102940981,1843.0,,6,13,/jonbown/pyspark-memory-issues-decision-tree-submit,American Express - Default Prediction
7647,103371274,1852.0,0.7994441110236208,0,13,/adhithyasrinivasan/amex-feature-ensemble,American Express - Default Prediction
7648,103371274,1852.0,0.7994441110236208,0,13,/adhithyasrinivasan/amex-feature-ensemble,American Express - Default Prediction
7649,104794662,1566.0,,0,0,/aloychow/low-memory-lgbm-with-cv,American Express - Default Prediction
7650,97879359,1879.0,,2,9,/stautxie/amex-default-prediction-eda,American Express - Default Prediction
7651,101456245,1323.0,,4,18,/nanabi/amex-ks-csi-nnb,American Express - Default Prediction
7652,97378535,1881.0,,2,13,/songseungwon/de-identified-data-analysis-tutorial-ch-01,American Express - Default Prediction
7653,98336103,260.0,,0,5,/narendra/amex-high-level-analysis,American Express - Default Prediction
7654,99840025,2098.0,,0,4,/nishimoto/amex-1st-lgb,American Express - Default Prediction
7655,99924386,1988.0,,1,11,/tgwstr/baselinelgbm001,American Express - Default Prediction
7656,98335873,2083.0,,0,37,/radek1/xgboost-starter-with-nvtabular-0-794,American Express - Default Prediction
7657,103234270,1716.0,,0,8,/dmtrrr/nn-with-custom-transformer-layers,American Express - Default Prediction
7658,97450309,2575.0,0.7964495335459367,7,86,/jazivxt/expressions-of-gluttony,American Express - Default Prediction
7659,102305766,2165.0,,0,2,/larryliu31/amex-ccdp-lightgbm-series-1,American Express - Default Prediction
7660,97824847,2116.0,-0.0788935345130013,0,11,/bhavikardeshna/lightgbm-ensemble-learning,American Express - Default Prediction
7661,96829507,2089.0,0.7929459873035556,11,143,/huseyincot/amex-catboost-0-793,American Express - Default Prediction
7662,103756203,2272.0,,0,1,/stg44g3g36hk416hk417/amex-preprocessing-only-kaggle-gpu,American Express - Default Prediction
7663,100368660,2003.0,,11,58,/kartushovdanil/baseline-amex-catboost-blending-wandb,American Express - Default Prediction
7664,96849603,2360.0,0.7862539563166573,0,1,/basu369victor/amex-lightgbm-smote-quickstart,American Express - Default Prediction
7665,97564031,2379.0,0.795432830582177,0,4,/coolsidd14/weighted-average-of-ensemble,American Express - Default Prediction
7666,100871272,2164.0,,4,23,/kmmohsin/lgbm-with-optuna-for-tuning-on-c-gpu-lb-0-796,American Express - Default Prediction
7667,100899894,2026.0,,0,5,/canonicalized/amex-v2,American Express - Default Prediction
7668,100049202,2512.0,0.7855958287322948,0,1,/ryumdra/amex-from-good-refs,American Express - Default Prediction
7669,96899495,2462.0,,2,10,/datajmcn/converting-csv-to-parquet,American Express - Default Prediction
7670,100891591,2192.0,,2,3,/benjibb/hist-mining-concept-oriented-shared-information,American Express - Default Prediction
7671,101615120,2549.0,,0,1,/slashie/amex-data-eng-01,American Express - Default Prediction
7672,97640470,2443.0,0.7958790125488855,19,151,/alexryzhkov/amex-lightautoml-starter,American Express - Default Prediction
7673,104118196,2407.0,0.7951588239756191,0,4,/toddgardiner/amex-lgbm,American Express - Default Prediction
7674,103356845,2619.0,0.7956968559044137,2,7,/yulimjin/amex-data-analysis-in-english,American Express - Default Prediction
7675,100884315,2574.0,,2,8,/jafarbakhshaliyev/starter-lgbm-dart-with-optuna-score-0-794,American Express - Default Prediction
7676,101783642,2510.0,,0,4,/jjjj88/amex-feaure-generation,American Express - Default Prediction
7677,98455697,2455.0,,0,11,/leejunseok97/amex-default-eda-prediction,American Express - Default Prediction
7678,103129299,2517.0,,0,3,/hengjianshe/lightgbm-best-0-795,American Express - Default Prediction
7679,98281774,2464.0,,1,6,/konohayui/amex-topological-time-series-analysis,American Express - Default Prediction
7680,98307374,2285.0,,2,5,/carlosasdesouza/estudo-dask-leitura-de-dataframes,American Express - Default Prediction
7681,96941419,2694.0,,1,5,/guptadikshant/amex-default-prediction-basic-eda,American Express - Default Prediction
7682,96587208,2810.0,,2,22,/aninda/creating-smaller-train-test-data,American Express - Default Prediction
7683,103935749,2513.0,,0,1,/eteresh/amex-nn-proof-last-features-enough,American Express - Default Prediction
7684,96711701,2807.0,,1,30,/robikscube/amex-defaulters-delight-eda-twitch-stream,American Express - Default Prediction
7685,99635636,2737.0,0.794572953746919,5,17,/jonaswm/autogluon-automl,American Express - Default Prediction
7686,98519753,2697.0,,3,11,/paulojunqueira/brief-analysis-of-dataset-variables-amex,American Express - Default Prediction
7687,103256864,2648.0,0.7650453712403993,7,7,/otugrul/amex-caret-train-classification-with-r,American Express - Default Prediction
7688,99166884,2630.0,,0,2,/duanchenliu/data-exploring-dl,American Express - Default Prediction
7689,98237241,2534.0,,2,14,/bkaggler/amex-reduce-data-size-to-half,American Express - Default Prediction
7690,104536913,2986.0,,0,0,/erwanchesneau/notebook-exploration,American Express - Default Prediction
7691,97082788,2728.0,,0,1,/rriceice/amex-eda-which-makes-sense,American Express - Default Prediction
7692,96654736,3032.0,0.7832861962132613,2,38,/munumbutt/simple-lgbm-starter,American Express - Default Prediction
7693,97842951,2981.0,,5,20,/eduus710/amex-extremely-simple-xgboost-baseline,American Express - Default Prediction
7694,102279977,3089.0,,0,0,/vjagannath786/pytorch-lstm,American Express - Default Prediction
7695,100877362,3086.0,,9,31,/jsmithperera/amex-lightgbm,American Express - Default Prediction
7696,102472347,3182.0,,1,8,/eugenekoutiloff/amex-competition-data-prep-in-bq,American Express - Default Prediction
7697,98636705,2881.0,,7,33,/rakkaalhazimi/export-large-dataset-to-spark,American Express - Default Prediction
7698,102327609,2901.0,,2,8,/gilgarad/amex-metric-tester,American Express - Default Prediction
7699,102664670,2952.0,,0,0,/zeyjin/xgboost-starter,American Express - Default Prediction
7700,99685767,2953.0,,2,8,/rosicky1234/simple-logistic-regression,American Express - Default Prediction
7701,103248570,2963.0,0.7655467947983996,12,33,/vickeytomer/catboost-classifier,American Express - Default Prediction
7702,97845712,3150.0,,1,31,/karandora/xgboost-optuna-baseline,American Express - Default Prediction
7703,103400266,3027.0,,0,0,/tea0925ds/amex-2,American Express - Default Prediction
7704,102992818,3078.0,,0,5,/hiba007/using-lightgbm-0-792,American Express - Default Prediction
7705,97455218,3152.0,,0,5,/ishaan45/reduce-file-size-csv-to-parquet,American Express - Default Prediction
7706,102265913,3185.0,,2,4,/ivkireev/amex-ptls-data-preprocessing,American Express - Default Prediction
7707,99066424,3180.0,,0,9,/awaldeep/first-look-eda,American Express - Default Prediction
7708,102073209,3298.0,,1,3,/yajingirenezhang/fork-of-notebook2a797061f2,American Express - Default Prediction
7709,98126037,3878.0,0.7293038500416247,3,9,/craving1030/gpu-amex-keras-with-simple-selected-vars,American Express - Default Prediction
7710,103712823,3161.0,0.7889041208924266,19,33,/alvinleenh/amex-prediction-with-cat-boost,American Express - Default Prediction
7711,97945101,3153.0,,3,14,/medali1992/amex-data-engineering,American Express - Default Prediction
7712,98645523,3207.0,,2,5,/ahmedali058/amex-default-predection,American Express - Default Prediction
7713,96838617,3286.0,,4,5,/venkatkumar001/lets-try-fast-ai-amex,American Express - Default Prediction
7714,99319661,3196.0,,0,3,/ricafernandes/tensorflow-bilstms,American Express - Default Prediction
7715,102761765,3390.0,,2,14,/shahilap96/for-beginners-1-loading-and-preprocessing,American Express - Default Prediction
7716,96718923,3363.0,,7,21,/nikhilsharma24/custom-metric-r,American Express - Default Prediction
7717,97509183,3343.0,,1,9,/revathiprakash/amex-eda-beginner,American Express - Default Prediction
7718,99313616,3463.0,,24,49,/junjitakeshima/amex-simple-lgbm-starter-for-beginner-en,American Express - Default Prediction
7719,100192340,3477.0,,10,47,/mirfanazam/large-dataset-csv-dask-parquet,American Express - Default Prediction
7720,102820933,3436.0,,0,4,/drrajkulkarni/amex-cnn,American Express - Default Prediction
7721,98567467,3546.0,0.787203057711092,0,8,/nickimpark/amex-prediction,American Express - Default Prediction
7722,103636269,3578.0,,1,8,/itspavansatish/lgbclassifier-starter-0-57,American Express - Default Prediction
7723,108822255,3545.0,,0,0,/nethmirajapaksha/notebooka51a048bc9,American Express - Default Prediction
7724,98253098,3675.0,,1,13,/abhianalytic/amex-read-full-data-without-any-transformation,American Express - Default Prediction
7725,100849327,3772.0,0.7855641261596941,2,15,/lixinqi98/amex-lightgbm,American Express - Default Prediction
7726,103046725,3687.0,0.7854725483647004,0,5,/foocheechuan/amexdefaultprediction,American Express - Default Prediction
7727,99747665,3676.0,,2,7,/gauravduttakiit/reduce-training-data-by-88-16-5-gbs-to-2-gbs,American Express - Default Prediction
7728,101110246,3697.0,,1,12,/nandakishorejoshi/amex-pre-and-post-model-predictive-analysis,American Express - Default Prediction
7729,96798387,3744.0,,5,36,/yshiml/amex-simple-lgbm-baseline,American Express - Default Prediction
7730,99218586,3832.0,,1,10,/what5up/amex-lstm-pytorch-lightning-inf-0-717,American Express - Default Prediction
7731,99215784,3823.0,0.7833278859272613,4,18,/harshghadiya/amex-lgbm-prediction-boosting,American Express - Default Prediction
7732,103720803,3803.0,,0,0,/wordsforthewise/quick-and-dirty-first-ml-solution,American Express - Default Prediction
7733,103135320,3873.0,,0,0,/arsalaan7/americanoexpressopredictaro,American Express - Default Prediction
7734,97108971,3822.0,0.7827635415465544,9,27,/aliphya/who-would-default-next,American Express - Default Prediction
7735,104060828,3758.0,0.7824998767617357,0,0,/dianalaveena/american-express-xgboost,American Express - Default Prediction
7736,97456303,3848.0,,1,6,/karthisena/american-express-lightweight,American Express - Default Prediction
7737,102297197,3938.0,0.7790822909900136,3,19,/abee82/amex-using-fast-ai,American Express - Default Prediction
7738,97724299,3924.0,0.0208385099390065,1,8,/dkraynak/amex-test-dummy-submission,American Express - Default Prediction
7739,104125761,3921.0,0.7799573025671279,1,1,/sumit46656/02-amex-default-prediction,American Express - Default Prediction
7740,103835985,3954.0,,2,4,/ydvaakash/conversion-of-amex-dataset-csv-into-hdf5-format,American Express - Default Prediction
7741,98240495,3976.0,,4,7,/ransakaravihara/how-features-vary-from-statement-dates,American Express - Default Prediction
7742,104160252,3925.0,,0,1,/tavoglc/3d-convolution-for-tabular-data,American Express - Default Prediction
7743,166924096,3978.0,,1,16,/urbanmonk09/cat-boost-amex-solution-for-all,American Express - Default Prediction
7744,98060283,4008.0,,0,7,/hunsoojung/amex-default-prediction,American Express - Default Prediction
7745,97076420,4099.0,,4,5,/sravanneeli/convert-train-data-to-pckl-file,American Express - Default Prediction
7746,104744145,4035.0,,0,0,/chickenugget/random-forest-classifier,American Express - Default Prediction
7747,103520149,4058.0,0.7680407378424539,13,71,/limweixuan1994/xgboost-credit-prediction,American Express - Default Prediction
7748,96611357,4088.0,,1,5,/guillermolissa/amex-loaddataset2pyspark,American Express - Default Prediction
7749,101834024,4066.0,,1,4,/trevorfrench/amex-python-ml,American Express - Default Prediction
7750,96962795,4100.0,0.7659607137501834,0,3,/thebratattack/amex-ensemble-prediction-model,American Express - Default Prediction
7751,102336184,4097.0,0.7310146766371182,1,12,/sidharkal/amex-with-ml,American Express - Default Prediction
7752,102740950,4134.0,,4,9,/viktorcikojevic/amex-features-eda,American Express - Default Prediction
7753,102968475,4130.0,0.7567327703367625,0,1,/harshjadhav6301/amex-test02,American Express - Default Prediction
7754,106718717,4172.0,,0,1,/yairkabakovitch/default-prediction-gradient-boosting-bab60e,American Express - Default Prediction
7755,103052256,4159.0,,0,6,/sgreiner/amex-catboost-baseline,American Express - Default Prediction
7756,103131481,4218.0,0.7404950189683666,3,7,/arunkumar1809/amex-prediction,American Express - Default Prediction
7757,96598004,4291.0,0.595796925981092,2,23,/bgmello/the-platinum-solution,American Express - Default Prediction
7758,102986911,4348.0,,0,3,/joejoeshi/amex20220806,American Express - Default Prediction
7759,97152078,4357.0,,13,84,/ihelon/default-prediction-eda-and-modeling,American Express - Default Prediction
7760,102736576,4365.0,,2,6,/debarpanml/american-express-train-eda,American Express - Default Prediction
7761,100965934,4409.0,,4,12,/amineteffal/group-split-data-by-customer,American Express - Default Prediction
7762,103532400,4434.0,,0,3,/pirudayaraj/amex-mlt-free-soln1-score-0-585,American Express - Default Prediction
7763,102877708,4453.0,,4,12,/kobzetsu/top-25-most-important-features-using-gini-iv-woe,American Express - Default Prediction
7764,101763368,4512.0,,7,17,/kingsshah/easiest-way-to-reduce-from-190-to-36-columns,American Express - Default Prediction
7765,99790007,4541.0,,0,5,/madhuban17/amex-reading-data,American Express - Default Prediction
7766,100885584,4545.0,,0,8,/shinyatakaramoto/simple-logistic-regression-with-crossvalidataion,American Express - Default Prediction
7767,104686414,4542.0,,0,1,/anmolspace/instantly-estimate-rows-in-a-very-large-csv-file,American Express - Default Prediction
7768,99544474,4544.0,,10,17,/faseeh001/amex-data-analysis,American Express - Default Prediction
7769,100290717,4580.0,,0,7,/ricaxavier/competition-amex-prediction-eda,American Express - Default Prediction
7770,97946954,4592.0,0.496134982582787,10,32,/jirkaborovec/amex-eda-baseline-lightning-flash,American Express - Default Prediction
7771,99828692,4628.0,,0,5,/jagdmir/american-express-default-prediction-eda,American Express - Default Prediction
7772,108104501,4662.0,0.7110455565750884,0,1,/parthavjoshi/27-05-amex-v1,American Express - Default Prediction
7773,102877789,4667.0,,0,3,/pallavijagtap/american-express-default-prediction-9th-aug,American Express - Default Prediction
7774,103622918,4698.0,,0,6,/zhouhua2022/kaggle-2022-8-21-american-express-default-predicti,American Express - Default Prediction
7775,101008492,4710.0,0.0583475568863371,4,12,/cinciadedadoscomr/amex-decision-tree-for-categ-feature-selection,American Express - Default Prediction
7776,101982018,4757.0,0.0206775043509746,6,9,/kuldipgusani/amex-default-prediction-smote-lgb-and-xgb,American Express - Default Prediction
7777,96597228,4725.0,,10,40,/mpwolke/normalized-gini-amex-platinum,American Express - Default Prediction
7778,97741291,4774.0,0.0198056088447389,0,6,/kayalvizhim/amex-prediction,American Express - Default Prediction
7779,99654248,4716.0,0.0192286009876971,2,5,/ripcurl/ml-starter,American Express - Default Prediction
7780,99742250,1.0,,15,55,/sebastianvangerwen/1st-place-solution-tps-jun-denoising-ae,Tabular Playground Series - Jun 2022
7781,98553000,2.0,,0,1,/arturra/analysis-of-nans,Tabular Playground Series - Jun 2022
7782,107009174,4.0,,38,109,/ravi20076/tpsjun22-extensiveeda-groups13,Tabular Playground Series - Jun 2022
7783,99735778,8.0,0.9910241488241917,2,3,/daru191854/single-network-like-mlm,Tabular Playground Series - Jun 2022
7784,97235805,12.0,,1,8,/cabaxiom/tps-jun-22-eda,Tabular Playground Series - Jun 2022
7785,97928194,15.0,0.8597405287641854,8,23,/oxzplvifi/tps2206-gbm-resnet-imputation,Tabular Playground Series - Jun 2022
7786,98257059,20.0,0.8578756761604217,1,15,/mehrankazeminia/tps22jun-coordinate-one-by-one,Tabular Playground Series - Jun 2022
7787,98248743,17.0,,16,25,/nikhilkhetan/setting-up-a-validation-set,Tabular Playground Series - Jun 2022
7788,97290401,22.0,1.311885328081141,0,4,/foolishboi/tpsjun22-fancyimpute,Tabular Playground Series - Jun 2022
7789,99494658,19.0,1.0350990993463522,1,9,/nnjjpp/imputation-using-sgdregressor-tps-june-2022,Tabular Playground Series - Jun 2022
7790,97168811,47.0,0.9825023172010434,7,16,/akmalmir/missing-values-imputation-with-iterativeimputer,Tabular Playground Series - Jun 2022
7791,99481197,27.0,,2,13,/maxboxbox/tps-jun22-linear-keras-model,Tabular Playground Series - Jun 2022
7792,97557792,38.0,0.873939713167268,7,38,/shariful07/tps-jun2022-lgbmregressor,Tabular Playground Series - Jun 2022
7793,97291792,48.0,0.95233225296832,7,23,/vipin20/tsp-june22-handling-missing-value,Tabular Playground Series - Jun 2022
7794,97291792,48.0,1.022215450840377,7,23,/vipin20/tsp-june22-handling-missing-value,Tabular Playground Series - Jun 2022
7795,97424982,72.0,0.955068226824355,2,12,/cv13j0/tps-jun22-multivariate-feature-imputation,Tabular Playground Series - Jun 2022
7796,97375168,73.0,0.9295587457936528,4,10,/tharunnayak14/tps-june-22-imputation-techniques-beginner-to-adv,Tabular Playground Series - Jun 2022
7797,99042397,103.0,0.8874727300386164,13,60,/devsubhash/tps-june-eda-xgb-simpleimputer,Tabular Playground Series - Jun 2022
7798,99631504,104.0,0.8711220328334941,1,11,/btbpanda/py-boost-multioutput-models-for-imputation,Tabular Playground Series - Jun 2022
7799,98720029,106.0,,2,9,/eduus710/tps-jun2022-how-random-are-the-nans,Tabular Playground Series - Jun 2022
7800,98493303,108.0,,6,10,/pardeep19singh/tps-june-2022-understanding-data-distributions,Tabular Playground Series - Jun 2022
7801,97339433,109.0,0.8940246481306735,0,11,/ehekatlact/tps2206-convert-submission-to-data,Tabular Playground Series - Jun 2022
7802,98859747,107.0,0.9217681484002006,0,6,/abhishekrathi09/tubular-june-iterative-imputer-xgboost,Tabular Playground Series - Jun 2022
7803,97945304,112.0,0.8604224874562901,10,73,/alexryzhkov/tps-jun-22-lightautoml-imputer,Tabular Playground Series - Jun 2022
7804,97680406,120.0,0.8754033316176465,2,8,/mirenaborisova/tps-june-22-simpleimputer-lgbm-lb-0-87540,Tabular Playground Series - Jun 2022
7805,97369676,126.0,0.940819775047648,9,48,/hasanbasriakcay/tpsjun22-insightful-eda-baselines,Tabular Playground Series - Jun 2022
7806,98356983,127.0,0.861258893619065,30,69,/abdulravoofshaik/quick-eda-and-missing-values-tutorial,Tabular Playground Series - Jun 2022
7807,99432036,133.0,0.8633409492789405,1,18,/mehrdadsadeghi/tpsjun2022-missing-data-imputation-tensorflow-nn,Tabular Playground Series - Jun 2022
7808,98424354,139.0,0.9033761773795106,2,11,/minhtrthn/tps-jun-2022-validation-set-split,Tabular Playground Series - Jun 2022
7809,97772981,154.0,0.9595625732892517,0,5,/gopalgoyal612002/tps-june,Tabular Playground Series - Jun 2022
7810,97380777,153.0,,6,10,/martynovandrey/tps-jun-22-splitted-dataset-24x-faster,Tabular Playground Series - Jun 2022
7811,99472962,167.0,0.9109253504347112,6,20,/sfktrkl/tps-june-2022,Tabular Playground Series - Jun 2022
7812,98514540,174.0,,2,8,/bogdandoicin/improved-lgbm-and-mean,Tabular Playground Series - Jun 2022
7813,99442260,175.0,0.8753705973575602,2,7,/jadelsoufi/bayesian-optimization-xgboost-lgbm,Tabular Playground Series - Jun 2022
7814,97381733,176.0,0.924090639009562,6,30,/varunnagpalspyz/tps-june-2022-iterativeimputer-2x-baseline,Tabular Playground Series - Jun 2022
7815,98546624,177.0,,3,8,/vertigo42/tps-june22-imputation-regression-comparison,Tabular Playground Series - Jun 2022
7816,97449397,179.0,,0,3,/hosseinbehjat/simple-eda,Tabular Playground Series - Jun 2022
7817,98762811,199.0,0.9757030515455086,0,6,/andrewnuk/lightgbm,Tabular Playground Series - Jun 2022
7818,99636093,201.0,,7,16,/mohammadhossein77/june-tps-histgradientboostingregressor,Tabular Playground Series - Jun 2022
7819,99534909,207.0,,5,14,/ijcrook/tps-easy-to-use-imputation-techniques,Tabular Playground Series - Jun 2022
7820,99307971,212.0,,0,11,/asheniranga/tps-jun-imputer,Tabular Playground Series - Jun 2022
7821,97791526,213.0,,1,7,/slythe/exploration-for-imputation-tps-jun-22,Tabular Playground Series - Jun 2022
7822,99704470,214.0,0.8870024109554365,10,27,/imnaho/tps-jun22-eda-predict,Tabular Playground Series - Jun 2022
7823,97896572,221.0,,1,4,/hikarumoriya/imputation-of-mean-value,Tabular Playground Series - Jun 2022
7824,103115581,222.0,,1,13,/docxian/tps-2022-june-r-starter,Tabular Playground Series - Jun 2022
7825,99043206,226.0,,0,4,/marctris/msp-tab-playground,Tabular Playground Series - Jun 2022
7826,97227010,227.0,0.8940246481306735,4,21,/mukaseevru/tps-jun-22-lama-lightautoml-in-loop,Tabular Playground Series - Jun 2022
7827,98539934,237.0,,0,5,/ankitpathakzeal/imputation-tabular-playground-june-2022,Tabular Playground Series - Jun 2022
7828,98229495,245.0,0.9043074848466192,11,18,/wasshoiwasshoi/tps-2022-jun-using-lightgbm-for-now,Tabular Playground Series - Jun 2022
7829,99705850,246.0,0.8989435084903366,3,17,/swagician/june-r-forest-imputation-adjusting-hyperparams,Tabular Playground Series - Jun 2022
7830,99734305,247.0,0.9162445057691844,1,5,/rsesha/tps-june-featurewiz-score-0-899-in-10-lines,Tabular Playground Series - Jun 2022
7831,98013696,255.0,,1,10,/bannourchaker/crisp-dm-dataunderstanding-part1-auto-eda,Tabular Playground Series - Jun 2022
7832,99333117,263.0,0.9123679343368528,4,14,/athews/tpsjune22-eda-xgboost-nn-model,Tabular Playground Series - Jun 2022
7833,97733079,266.0,0.9063688715139018,6,12,/sanjaylalwani/tps-jun22-data-impute-lb-0-9,Tabular Playground Series - Jun 2022
7834,99651981,269.0,0.9118326019593268,0,0,/hirotokitamur/hk-tabular-playground-series-jun-2022,Tabular Playground Series - Jun 2022
7835,97404202,271.0,,3,14,/kotrying/tps0622-simple-imputation,Tabular Playground Series - Jun 2022
7836,98132572,272.0,,0,2,/mohamedmagdy11/tps-jun-22-eda-lightgbm-modeling,Tabular Playground Series - Jun 2022
7837,118425935,270.0,,1,8,/ltrahul/tabular-playground-jun-2022-simple-explanation,Tabular Playground Series - Jun 2022
7838,99339626,274.0,0.9141050628837076,1,10,/une510/tps-june-2022,Tabular Playground Series - Jun 2022
7839,99339626,274.0,0.9141050628837076,1,10,/une510/tps-june-2022,Tabular Playground Series - Jun 2022
7840,98431251,279.0,,3,9,/davidhguerrero/feature-importance-with-lgbmregressor-with-k-folds,Tabular Playground Series - Jun 2022
7841,117706187,284.0,,0,0,/sihyunlee/sihyun-imputation,Tabular Playground Series - Jun 2022
7842,99087135,304.0,0.9817950497460638,4,21,/akioonodera/tps-jun2022-lgbm-regression,Tabular Playground Series - Jun 2022
7843,98647880,291.0,0.9544144371652372,11,42,/desalegngeb/tps-june-22-quick-overview-modelling-using-xgb,Tabular Playground Series - Jun 2022
7844,99778755,299.0,0.9228817950120444,2,5,/harshul23/tps-june-2022-xgboost-with-correlation-0-92,Tabular Playground Series - Jun 2022
7845,97539235,309.0,0.9272475472110032,2,9,/mahendragundeti/eda-for-understanding,Tabular Playground Series - Jun 2022
7846,97810611,324.0,,4,10,/egemenuurdalg/tps-june-is-h2o-xgboost-is-faster,Tabular Playground Series - Jun 2022
7847,98731514,326.0,,0,3,/seungmoklee/55-xgboosts-with-mean-imputation,Tabular Playground Series - Jun 2022
7848,99221914,325.0,0.9739911476041512,3,11,/muki2003/june-2022-playground-deep-learning-regression,Tabular Playground Series - Jun 2022
7849,97806940,331.0,0.9478052680848652,1,12,/justinvanzyl/missxgb,Tabular Playground Series - Jun 2022
7850,97806940,331.0,0.9478052680848652,1,12,/justinvanzyl/missxgb,Tabular Playground Series - Jun 2022
7851,98010261,332.0,0.9357788390918662,2,7,/akanshakhandelwal08/tps-june-2022,Tabular Playground Series - Jun 2022
7852,99729807,346.0,,0,3,/hanselliott/tpsjun2022-xgb-missforest-knn,Tabular Playground Series - Jun 2022
7853,99676538,363.0,0.9493146862420644,0,20,/m1y7k8/tps-jun-2022-eda-imputation-interpolation,Tabular Playground Series - Jun 2022
7854,97919300,369.0,1.4175999876427674,1,3,/tracyporter/june-2022-imputation-tracy-s-code,Tabular Playground Series - Jun 2022
7855,97482924,371.0,0.966085980032139,3,7,/mustafakeser4/tps-jun-eda-sklearn-impute,Tabular Playground Series - Jun 2022
7856,97946007,373.0,,3,9,/robertturro/eda-feature-distributions-skewness-and-kurtosis,Tabular Playground Series - Jun 2022
7857,98086321,360.0,0.9667017280215532,0,8,/prashantpathak244/missing-value-eda-and-xgboost-imputing,Tabular Playground Series - Jun 2022
7858,99380591,387.0,,9,44,/dhirajkumar612/iterative-imputer-linear-regression,Tabular Playground Series - Jun 2022
7859,97168313,397.0,0.9825023172010434,0,2,/copypastebro/basic-iterative-imputation-benchmark,Tabular Playground Series - Jun 2022
7860,98123048,404.0,,7,12,/rizqyad/pandas-vs-cudf,Tabular Playground Series - Jun 2022
7861,99499004,409.0,1.390069560875984,0,0,/barbagrande007/bbg007-imputation,Tabular Playground Series - Jun 2022
7862,99088655,425.0,,3,11,/ginojp/out-of-bag-error,Tabular Playground Series - Jun 2022
7863,98230747,431.0,0.9824965871783576,7,19,/matthewszhang/tps-june-interactive-eda-sklearn-imputer,Tabular Playground Series - Jun 2022
7864,98948440,443.0,,0,1,/rohandawar/tabular-playground-jun-2022-experiment-2,Tabular Playground Series - Jun 2022
7865,97217640,482.0,1.0133045326313863,2,17,/pranjalverma08/tps-june-eda-imputer-starter,Tabular Playground Series - Jun 2022
7866,97184131,487.0,,7,10,/raviista/tpsjune22-art-of-eda,Tabular Playground Series - Jun 2022
7867,97586631,492.0,1.424425010385557,5,11,/maulberto3/tps-jun-2022-regression-based-imputer-w-pipeline,Tabular Playground Series - Jun 2022
7868,97456270,498.0,1.0243708352650889,1,6,/akritisood175/tps-missing-values,Tabular Playground Series - Jun 2022
7869,98892311,526.0,,0,8,/stautxie/june-2022-tabular-playground,Tabular Playground Series - Jun 2022
7870,98489169,527.0,1.071216531517181,3,8,/seongwonr/fast-imputation-with-handmade-class,Tabular Playground Series - Jun 2022
7871,99696251,529.0,,0,3,/junekitagawa/2022-june-tps,Tabular Playground Series - Jun 2022
7872,98923546,532.0,,0,7,/naiborhujosua/loading-your-data-faster,Tabular Playground Series - Jun 2022
7873,98314939,767.0,,2,6,/micajoumathematics/some-insights-into-missing-values,Tabular Playground Series - Jun 2022
7874,98095529,612.0,,2,10,/zhixx018/0611-eda-lgb,Tabular Playground Series - Jun 2022
7875,97589457,642.0,1.4232742726982437,0,1,/emansalah2000/play-ground-series,Tabular Playground Series - Jun 2022
7876,97810797,648.0,1.492068809110322,2,6,/ashishkattel/playground-series,Tabular Playground Series - Jun 2022
7877,97797424,668.0,,1,17,/ygorana/tps-june-2022-ultra-fast-submissions-50s,Tabular Playground Series - Jun 2022
7878,99550275,748.0,,2,8,/nourhadrich/for-loop-imputation-with-mean,Tabular Playground Series - Jun 2022
7879,99734994,773.0,1.5974031282326824,4,23,/youseefmoemen/generative-adversarial-imputation-network-gain,Tabular Playground Series - Jun 2022
7880,97173541,786.0,1.417080527161962,0,1,/gomohit/getting-started-with-median-imputation,Tabular Playground Series - Jun 2022
7881,97563273,801.0,1.426627187554924,3,8,/francescocolicino/tps-june-eda-r-with-data-table,Tabular Playground Series - Jun 2022
7882,99256690,835.0,,0,1,/peressim/tps-jun-2022-eda-fillna-interpolation,Tabular Playground Series - Jun 2022
7883,106276953,2.0,0.8411812233643181,0,21,/victorsd/2nd-place-inference,HuBMAP + HPA - Hacking the Human Body
7884,106283407,3.0,0.8398347267997165,0,9,/vladimirsydor/hubmap-2021-inference-v1,HuBMAP + HPA - Hacking the Human Body
7885,102645103,5.0,,3,22,/carnozhao/hpa-data-download,HuBMAP + HPA - Hacking the Human Body
7886,106973186,1.0,,0,10,/opusen/customize-mmseg,HuBMAP + HPA - Hacking the Human Body
7887,101655351,57.0,,40,45,/w3579628328/mmsegmentation-trainning,HuBMAP + HPA - Hacking the Human Body
7888,108021587,35.0,,0,0,/cheulkay/hubmap-inference,HuBMAP + HPA - Hacking the Human Body
7889,103362194,49.0,0.7138627130330837,2,3,/fuckvenkatraman/upernet-swin-submissions,HuBMAP + HPA - Hacking the Human Body
7890,104430878,41.0,0.7450450244864191,0,18,/tscheung/lb-0-74-tf-tpu-efficientnet-b8-640-640,HuBMAP + HPA - Hacking the Human Body
7891,106280950,53.0,0.8113196567189785,0,1,/snaker/hpainfer,HuBMAP + HPA - Hacking the Human Body
7892,100902347,59.0,,2,5,/vmuzhichenko/hubmap-hpa-tf-unet-train,HuBMAP + HPA - Hacking the Human Body
7893,101618475,62.0,,1,14,/soumya9977/hubmap-multiorgan-segmentation-1-3-data-prep,HuBMAP + HPA - Hacking the Human Body
7894,104248270,83.0,0.7182731331474345,0,0,/aruaru0/inference-segformer-oneshot,HuBMAP + HPA - Hacking the Human Body
7895,105115225,95.0,0.5326190575307891,0,0,/vladyslavsarnatskyi/coat-no-aspp-submission,HuBMAP + HPA - Hacking the Human Body
7896,99483224,80.0,,0,0,/bibhabasumohapatra/hubmap-train-part-1,HuBMAP + HPA - Hacking the Human Body
7897,104518560,118.0,,4,27,/e0xextazy/multiclass-dataset-768x768-with-stride-for-mmseg,HuBMAP + HPA - Hacking the Human Body
7898,99769670,123.0,,0,7,/aleksandrkruchinin/hubmap-hpa-images-tfrecords,HuBMAP + HPA - Hacking the Human Body
7899,102114231,147.0,,1,6,/pengbing/data-exploration,HuBMAP + HPA - Hacking the Human Body
7900,102344537,153.0,,0,8,/kleinliu/hubmap-with-early-stoping-trainning-test,HuBMAP + HPA - Hacking the Human Body
7901,105131195,176.0,,1,10,/shionhonda/hubmap-hpa-compare-masks-and-predictions,HuBMAP + HPA - Hacking the Human Body
7902,105693462,171.0,,11,55,/nghihuynh/hubmap-hpa-exploratory-data-analysis,HuBMAP + HPA - Hacking the Human Body
7903,101020965,343.0,,2,10,/quandapro/sliding-window-with-importance-map-inference,HuBMAP + HPA - Hacking the Human Body
7904,100963936,190.0,,4,34,/sungjunghwan/eda-organ-segmentation-eda,HuBMAP + HPA - Hacking the Human Body
7905,102793920,331.0,,3,7,/fortelean/create-coco-dataset-for-hacking-the-human-body,HuBMAP + HPA - Hacking the Human Body
7906,106534402,327.0,,0,1,/anubhavde/multi-organ-ftu-segmentation,HuBMAP + HPA - Hacking the Human Body
7907,104285983,267.0,,6,25,/ravishah1/measuring-functional-tissue-units,HuBMAP + HPA - Hacking the Human Body
7908,105208538,298.0,,0,22,/joydeep69/tf-tpu-efficientnet-0-74,HuBMAP + HPA - Hacking the Human Body
7909,103571427,233.0,,0,1,/konomuabe/view-with-gimp,HuBMAP + HPA - Hacking the Human Body
7910,103591216,289.0,,0,1,/tinvonguyenan/extract-5-type-to-csv-file-and-image-folder,HuBMAP + HPA - Hacking the Human Body
7911,104497709,258.0,,1,30,/utm529fg/eng-eda-hubmap-hpa-data,HuBMAP + HPA - Hacking the Human Body
7912,103674120,318.0,0.2239843717449926,0,2,/samundersingh/semetic-image,HuBMAP + HPA - Hacking the Human Body
7913,104882843,237.0,0.6667994486152722,0,7,/osmanf/hubmap-hpa-deep-learning-unet-cnn,HuBMAP + HPA - Hacking the Human Body
7914,103644681,415.0,,0,13,/yusaku5739/stain-normalized-dataset-768-768,HuBMAP + HPA - Hacking the Human Body
7915,106262058,380.0,,1,5,/huythach/hubmap-tile-patch-data,HuBMAP + HPA - Hacking the Human Body
7916,100803535,396.0,,2,10,/dinowun/eda-simplified-hubmap-hpa-organ-segmentation,HuBMAP + HPA - Hacking the Human Body
7917,103773048,404.0,,0,1,/aleksandrmogilevskiy/baseline,HuBMAP + HPA - Hacking the Human Body
7918,104829651,346.0,,0,0,/deltaechov/dataset-resize-hack-human-body,HuBMAP + HPA - Hacking the Human Body
7919,104119766,455.0,0.3136692581301911,8,21,/alexeyolkhovikov/segformer-inference-0-70-lb-simple-tta,HuBMAP + HPA - Hacking the Human Body
7920,100715382,445.0,,2,3,/tt195361/hubmap-hpa-walk-around-data,HuBMAP + HPA - Hacking the Human Body
7921,101449420,704.0,0.2765308060480664,0,2,/huyidao/infer1,HuBMAP + HPA - Hacking the Human Body
7922,99073075,440.0,,1,31,/thedevastator/hubmap-quick-eda,HuBMAP + HPA - Hacking the Human Body
7923,101795479,571.0,0.6486867655960892,0,0,/johnnyt2/unet-hubmap-resnet-submission,HuBMAP + HPA - Hacking the Human Body
7924,99097135,511.0,,4,12,/mohammaddehghan/hubmap-hpa-analyzing-exploratory-data,HuBMAP + HPA - Hacking the Human Body
7925,131002305,611.0,,0,1,/meenakshiramaswamy/creation-of-patches-using-monai,HuBMAP + HPA - Hacking the Human Body
7926,104245714,558.0,,0,0,/yuujin/notebookf855cc760a,HuBMAP + HPA - Hacking the Human Body
7927,103326635,620.0,,1,10,/maunilshah/hubmap-intro-to-segmentation,HuBMAP + HPA - Hacking the Human Body
7928,101480578,813.0,,5,29,/p4rallax/hubmap-hpa-pytorch-baseline-w-tiles-stratifiedkf,HuBMAP + HPA - Hacking the Human Body
7929,101231892,637.0,,1,6,/sunandwater/hubmap-data-visualization,HuBMAP + HPA - Hacking the Human Body
7930,105465992,694.0,,18,29,/yassinealouini/working-with-tiff-files,HuBMAP + HPA - Hacking the Human Body
7931,99165119,744.0,,37,268,/ishandutta/hubmap-complete-understanding-and-eda-w-b,HuBMAP + HPA - Hacking the Human Body
7932,104850211,700.0,,0,0,/danhoang/hubmap-eda-inference,HuBMAP + HPA - Hacking the Human Body
7933,109265962,683.0,,0,0,/adc28827810/mmseg-train-mit,HuBMAP + HPA - Hacking the Human Body
7934,100648304,607.0,,3,19,/clemchris/hubmap-pytorch-train,HuBMAP + HPA - Hacking the Human Body
7935,99504028,853.0,0.3585507070008205,0,8,/susnato/hubmap-hpa-fpn-starter-tf,HuBMAP + HPA - Hacking the Human Body
7936,101743198,846.0,,0,2,/arnavchakravarthy/fast-augmentations-multiprocessing-albumentations,HuBMAP + HPA - Hacking the Human Body
7937,102797537,883.0,,1,13,/b11gden/hubmap-hpa-simple-pytorch-baseline,HuBMAP + HPA - Hacking the Human Body
7938,99682200,884.0,0.3137378943259043,3,8,/seraphwedd18/hubseg-dnn-approach,HuBMAP + HPA - Hacking the Human Body
7939,106056938,950.0,,0,3,/olegbaryshnikov/hubmap-hpa-resized-tfrecords-512x512,HuBMAP + HPA - Hacking the Human Body
7940,124470057,1012.0,,0,3,/theo88/hubmap-hpa-1024x1024-png-generation,HuBMAP + HPA - Hacking the Human Body
7941,105683427,1031.0,,0,3,/bhavesjain/hubmap-hpa-data-prep,HuBMAP + HPA - Hacking the Human Body
7942,104804435,892.0,,1,9,/vincenttu/hubmap-hpa-comp-dataset-visualization,HuBMAP + HPA - Hacking the Human Body
7943,106777393,1071.0,0.2746087567783219,0,1,/tomp1121/mmsegmentation-inference,HuBMAP + HPA - Hacking the Human Body
7944,103167685,915.0,,1,46,/jirkaborovec/ftus-segm-eda-export-rle-mask,HuBMAP + HPA - Hacking the Human Body
7945,100202912,905.0,,21,166,/dschettler8845/eda-hubmap-hpa-organ-segmentation,HuBMAP + HPA - Hacking the Human Body
7946,104918226,912.0,0.0,0,2,/hubingqian2006/resnet50,HuBMAP + HPA - Hacking the Human Body
7947,99402355,1001.0,,4,19,/pedroprez/bbox-and-masks-visualisation,HuBMAP + HPA - Hacking the Human Body
7948,104354003,939.0,,0,0,/s0mes0me/for-analysis-data,HuBMAP + HPA - Hacking the Human Body
7949,106738639,1020.0,0.3422588063466429,2,2,/aahut90/hubmap-hpa,HuBMAP + HPA - Hacking the Human Body
7950,101053369,1047.0,,0,9,/ksooklall/hubmap-hpa-eda-and-preprocessing,HuBMAP + HPA - Hacking the Human Body
7951,101171495,1063.0,,0,4,/albertozorzetto/training-hubmap-dlv3-w-tiles,HuBMAP + HPA - Hacking the Human Body
7952,116084930,1101.0,,0,0,/hyunwoo2/training-with-thickness-and-staining-augmentation,HuBMAP + HPA - Hacking the Human Body
7953,103851442,1091.0,0.1778836783416999,0,2,/soymilkk/hubmap-unet,HuBMAP + HPA - Hacking the Human Body
7954,99745349,1106.0,,4,25,/temuujinerdene/augmentation-with-generated-artifacts,HuBMAP + HPA - Hacking the Human Body
7955,104667704,1131.0,,0,2,/florentgiaccherini/hubmap-hpa-exploratory-analysis,HuBMAP + HPA - Hacking the Human Body
7956,106842238,1135.0,,1,3,/bradhammond/hubmap-test-build-of-u-net-cnn,HuBMAP + HPA - Hacking the Human Body
7957,101565222,1.0,,0,2,/ymatioun/tps-722-integer-model,Tabular Playground Series - Jul 2022
7958,99905965,6.0,0.5173915953704633,6,39,/cabaxiom/tps-jul-22-gmm-baseline,Tabular Playground Series - Jul 2022
7959,101624987,46.0,0.6423322410626743,3,10,/mehrankazeminia/1-3-tps22jul-pseudo-supervised-clustering,Tabular Playground Series - Jul 2022
7960,108918413,4.0,,28,98,/ravi20076/tpsjul22-eda-baseline,Tabular Playground Series - Jul 2022
7961,102216877,2.0,0.6332916284657145,0,4,/tinfufans/jul2022,Tabular Playground Series - Jul 2022
7962,102167695,12.0,0.8233493016071708,6,17,/djustin/tps22jul-clustering-ensembling-improved,Tabular Playground Series - Jul 2022
7963,102214969,13.0,,0,4,/rm1000/improved-clustering-and-ensembling,Tabular Playground Series - Jul 2022
7964,99921311,10.0,0.4825232830133921,10,23,/desalegngeb/tpsjuly2022-all-you-need-is-knn,Tabular Playground Series - Jul 2022
7965,103342202,20.0,,1,18,/aliabdin1/tps-jul-2022-some-clustering-metrics,Tabular Playground Series - Jul 2022
7966,100953055,47.0,,5,14,/vwoodnz/improving-meat-for-ensemble-voting,Tabular Playground Series - Jul 2022
7967,102208428,35.0,,4,9,/itspavansatish/bayesiangaussianmixture,Tabular Playground Series - Jul 2022
7968,100131921,54.0,0.2807960211322837,9,14,/akmalmir/clustering-with-pycaret-for-beginners-tps-07-2022,Tabular Playground Series - Jul 2022
7969,100801624,49.0,,17,48,/adaubas/tps-jul22-lgbm-extratree-qda-soft-voting,Tabular Playground Series - Jul 2022
7970,99799196,59.0,0.2192186601440961,2,22,/thedevastator/brute-forcing-k,Tabular Playground Series - Jul 2022
7971,100806016,70.0,,2,9,/buraaldal/bgmm-baseline-fuzzy-c-means-k-means,Tabular Playground Series - Jul 2022
7972,106861530,62.0,,14,34,/lazer999/tps-pca-k-means-simplified-4-everyone,Tabular Playground Series - Jul 2022
7973,101349440,64.0,,0,20,/jillanisofttech/tps-jul-2022-unsupervised-and-supervised-learning,Tabular Playground Series - Jul 2022
7974,100100658,120.0,,12,37,/shariful07/tps-july-2022-clustering,Tabular Playground Series - Jul 2022
7975,102060531,107.0,0.8178527548806427,1,13,/rishabhkmr/tps-jul22-clustering-ensembling,Tabular Playground Series - Jul 2022
7976,100540801,109.0,,21,39,/ayushv322/tabular-playground-july-eda-gmm-pca,Tabular Playground Series - Jul 2022
7977,102061796,87.0,0.8176655996029603,0,0,/moghazy/the-fine-art-of-fine-tuning,Tabular Playground Series - Jul 2022
7978,102213722,89.0,0.8173975624331427,0,0,/garywsg/powertransformer-bgmm-clustering,Tabular Playground Series - Jul 2022
7979,103640923,104.0,,0,1,/andrewsale/tps-jul22-vbgm,Tabular Playground Series - Jul 2022
7980,100932946,82.0,0.5532490269929812,41,91,/ashaykatrojwar/eda-pca-bayesian-gaussian-mixture,Tabular Playground Series - Jul 2022
7981,102005177,105.0,0.8166180582644486,3,12,/sanaaburrows/tps-2022jul-voting-classifier,Tabular Playground Series - Jul 2022
7982,101317363,142.0,,2,16,/jankrol21/tps-jul-2022-unifom-cluster-size-postprocessing,Tabular Playground Series - Jul 2022
7983,99912514,94.0,,4,13,/mhslearner/tps-jul-2022-cluster-analysis,Tabular Playground Series - Jul 2022
7984,101543399,140.0,,1,10,/abhinavkum/unsupervised-learning-beginner,Tabular Playground Series - Jul 2022
7985,102136158,99.0,0.8084944889802096,12,40,/abdulravoofshaik/clustering-using-denoising-autoencoder-tutorial,Tabular Playground Series - Jul 2022
7986,100942069,101.0,0.5965842025643531,3,11,/nagsdata/gaussianmixture-july,Tabular Playground Series - Jul 2022
7987,100462375,149.0,0.6044594591202692,27,65,/pourchot/simple-soft-voting,Tabular Playground Series - Jul 2022
7988,100189547,156.0,,5,8,/eduus710/tps-jul-22-metrics-vs-lb,Tabular Playground Series - Jul 2022
7989,100543467,182.0,,10,16,/joshuaswords/how-to-cluster-on-mass-tps-jul-2022,Tabular Playground Series - Jul 2022
7990,102178023,191.0,0.8045514242355064,0,19,/m1y7k8/tps-jul-2022-clustering,Tabular Playground Series - Jul 2022
7991,101478069,188.0,,17,43,/karlcini/bayesiangmmclassifier,Tabular Playground Series - Jul 2022
7992,101582259,202.0,0.7355020511426413,2,22,/sifrun/gaussian-mixture-model-is-all-you-need-0-7355,Tabular Playground Series - Jul 2022
7993,100681627,194.0,,0,2,/grandlee/machine-learning-introduction,Tabular Playground Series - Jul 2022
7994,101637386,195.0,,2,4,/sumit46656/03-tps-july-2022-explained-simply,Tabular Playground Series - Jul 2022
7995,100813176,198.0,0.6024963610862817,0,7,/skywolfmo/simple-clustering-0-6,Tabular Playground Series - Jul 2022
7996,100098463,211.0,,8,40,/plarmuseau/bruteforce-clustering,Tabular Playground Series - Jul 2022
7997,99890714,219.0,,6,9,/wasshoiwasshoi/tps-2022-july-quick-eda-and-k-means-baseline,Tabular Playground Series - Jul 2022
7998,126936162,220.0,,4,16,/waldemar/pca-umap-kmean-gmm,Tabular Playground Series - Jul 2022
7999,102051784,231.0,0.7355020511426413,0,11,/shaequeen/tps-july-22-gaussian-mixture,Tabular Playground Series - Jul 2022
8000,100750204,235.0,,2,6,/nitishraj/tps-july-2022-initial-experiments,Tabular Playground Series - Jul 2022
8001,102352539,237.0,0.7333249921137267,0,1,/harrylhw/notebookcf7a4b47c6,Tabular Playground Series - Jul 2022
8002,102186656,243.0,0.7302983483224953,0,1,/wxilson/k-means-bgmm,Tabular Playground Series - Jul 2022
8003,102112715,254.0,0.0,0,2,/hosseinbehjat/bgmm-bgmmc-tpsjul22,Tabular Playground Series - Jul 2022
8004,101987271,257.0,0.687168147240538,1,1,/tapendrakumar09/baysian-mixture-and-classifier,Tabular Playground Series - Jul 2022
8005,100739320,265.0,,11,23,/docxian/tps-2022-july-eda-dataexplorer-starter,Tabular Playground Series - Jul 2022
8006,102519816,267.0,,0,1,/yasirhussain1987/clustering-using-bgm-model-and-xgb-cassifier,Tabular Playground Series - Jul 2022
8007,101486311,277.0,0.5822058257338734,4,6,/rudyschn/rudy-s-tps-july-2022,Tabular Playground Series - Jul 2022
8008,100441044,281.0,,12,23,/melonpasta/tps-jul-2022-pca-eda-trying,Tabular Playground Series - Jul 2022
8009,102004622,316.0,0.5535551918016146,0,0,/barbagrande007/bbg007-bgm,Tabular Playground Series - Jul 2022
8010,101242757,300.0,0.6127443212752076,18,63,/ricopue/tps-jul22-clusters-and-lgb,Tabular Playground Series - Jul 2022
8011,103326027,319.0,,0,2,/evalieskovsk/tps-jul-22-clustering,Tabular Playground Series - Jul 2022
8012,100043914,330.0,,22,25,/cv13j0/tps-jun22-unsupervised-clustering-with-keras,Tabular Playground Series - Jul 2022
8013,101562623,331.0,0.6082104677325758,2,16,/ijcrook/graph-based-ensemble-clustering,Tabular Playground Series - Jul 2022
8014,102034540,347.0,,33,61,/akioonodera/tps-jul2022,Tabular Playground Series - Jul 2022
8015,100387600,342.0,,3,16,/subhajitbag/tsne-elbow-method-gaussian-mixtures,Tabular Playground Series - Jul 2022
8016,99795579,359.0,0.1752258219927844,8,23,/ryanbarretto/clustering-baseline,Tabular Playground Series - Jul 2022
8017,101355853,446.0,,2,8,/leandrodestefani/tps-jul-22-gaussianmixture-gbm,Tabular Playground Series - Jul 2022
8018,102029355,360.0,,2,7,/umangsavani/tps-2022jul-eda-outlier-bgmm,Tabular Playground Series - Jul 2022
8019,101860239,386.0,,5,19,/sanjaylalwani/tps-jul22-bgmm-clustering,Tabular Playground Series - Jul 2022
8020,100828932,374.0,0.601118836846107,8,21,/pinstripezebra/gaussian-clustering,Tabular Playground Series - Jul 2022
8021,101887296,400.0,,2,8,/youseefmoemen/tps-july-lgb-feature-selection-and-data-sampling,Tabular Playground Series - Jul 2022
8022,101703239,387.0,0.6010101823191797,6,13,/bogdandoicin/brute-force-clustering-improved,Tabular Playground Series - Jul 2022
8023,100632273,403.0,0.6010047858546543,11,32,/mehrdadsadeghi/tps-july2022-scaling-feature-selection,Tabular Playground Series - Jul 2022
8024,100651494,391.0,0.2649648151311826,0,1,/stelioskaralis/tps-july-2022-clustering,Tabular Playground Series - Jul 2022
8025,100651494,391.0,0.6010047858546543,0,1,/stelioskaralis/tps-july-2022-clustering,Tabular Playground Series - Jul 2022
8026,100778160,405.0,,0,0,/paulomarquies/tps-jul-22-pca-and-bgm,Tabular Playground Series - Jul 2022
8027,99972039,424.0,0.2576861143186956,2,5,/ohba0321/tps2207-eda-standardscaler-k-means-clusters-6,Tabular Playground Series - Jul 2022
8028,101783117,421.0,,13,29,/digvijaysinhgohil/auto-eda-with-dataprep-and-bgm-model,Tabular Playground Series - Jul 2022
8029,101976005,438.0,,0,11,/athews/tpsjuly22-knn-gmm-bgmm-pca-boosting-nn,Tabular Playground Series - Jul 2022
8030,102098509,431.0,,0,4,/majkaf/tbs-jul-2022-clustering,Tabular Playground Series - Jul 2022
8031,102413894,447.0,0.5989418371117493,0,0,/vermaavi/tps-july-22-clustering,Tabular Playground Series - Jul 2022
8032,101110229,444.0,0.2858963282568693,3,2,/makotouchiyama/tps-202207-robustscaler-code,Tabular Playground Series - Jul 2022
8033,100917951,464.0,0.5979974987106829,13,35,/naveenkonam1985/tps-july-22-clustering-with-bayesiangmm,Tabular Playground Series - Jul 2022
8034,100364896,468.0,,0,6,/santosh1974/play-ground-july-first,Tabular Playground Series - Jul 2022
8035,101192536,436.0,0.3484991404915329,1,14,/nknarendra7/gmm-clustering-for-july-tps,Tabular Playground Series - Jul 2022
8036,101927778,454.0,,1,5,/scchuy/tab202207-cluster-soft-vote,Tabular Playground Series - Jul 2022
8037,99885019,490.0,,1,7,/ehekatlact/tps2207-umap-visualize,Tabular Playground Series - Jul 2022
8038,100697377,479.0,0.596650827090459,0,13,/harshghadiya/tps-july-2022-clustering-gmm-and-bgmm,Tabular Playground Series - Jul 2022
8039,101229146,492.0,,0,13,/abdulaziz04/powertransformer-bgm,Tabular Playground Series - Jul 2022
8040,100215918,501.0,0.5966229500633466,0,9,/zhangcheche/nothing-to-be-revealed-tps-7-2022,Tabular Playground Series - Jul 2022
8041,100139999,494.0,0.2417223861428675,0,1,/gopalgoyal612002/tps-july-simple-pca-kmeans,Tabular Playground Series - Jul 2022
8042,101678621,477.0,0.5955433749548613,1,3,/prashantpathak244/july-playground,Tabular Playground Series - Jul 2022
8043,100499736,515.0,0.4749605720742244,2,7,/andrewnuk/eda-basics,Tabular Playground Series - Jul 2022
8044,99806612,483.0,,3,9,/datastrophy/tps7-22-gussian-mixture-pca-1d-and-2d-viz,Tabular Playground Series - Jul 2022
8045,100932687,524.0,,3,14,/mohamedmagdy11/tps-jul22-eda-kmeans-gmm-modeling,Tabular Playground Series - Jul 2022
8046,100665614,533.0,,0,12,/stautxie/tp-july-2022-eda-baseline-lb-0-585,Tabular Playground Series - Jul 2022
8047,100638353,543.0,0.5532083681584661,0,0,/siddhantbhagat93/scaling-method,Tabular Playground Series - Jul 2022
8048,100638353,543.0,0.2680103469811989,0,0,/siddhantbhagat93/scaling-method,Tabular Playground Series - Jul 2022
8049,100638353,543.0,0.2669106740778045,0,0,/siddhantbhagat93/scaling-method,Tabular Playground Series - Jul 2022
8050,100638353,543.0,0.3059951572561464,0,0,/siddhantbhagat93/scaling-method,Tabular Playground Series - Jul 2022
8051,100638353,543.0,0.5868833335429922,0,0,/siddhantbhagat93/scaling-method,Tabular Playground Series - Jul 2022
8052,100638353,543.0,0.5700274912390445,0,0,/siddhantbhagat93/scaling-method,Tabular Playground Series - Jul 2022
8053,100638353,543.0,0.5532083681584661,0,0,/siddhantbhagat93/scaling-method,Tabular Playground Series - Jul 2022
8054,101241964,536.0,,0,2,/mmojz642/tps-jul22-preprocess-issues,Tabular Playground Series - Jul 2022
8055,102184971,534.0,0.4754108917963987,3,8,/harshul23/tps-july22-eda-clustering-opt-k-0-54,Tabular Playground Series - Jul 2022
8056,99847330,556.0,0.0969898805215057,1,6,/ltrahul/tabular-playground-series-july-2022-solution,Tabular Playground Series - Jul 2022
8057,100917266,564.0,,3,15,/slythe/clustering-techniques-tps-jul-22,Tabular Playground Series - Jul 2022
8058,101980428,575.0,,5,9,/hugolearn/tps-trying,Tabular Playground Series - Jul 2022
8059,102190195,617.0,0.522069765853116,11,14,/imnaho/choose-colums-bayesiangaussianmixture,Tabular Playground Series - Jul 2022
8060,101100514,618.0,,0,6,/waizaidoc/playground-july-2022,Tabular Playground Series - Jul 2022
8061,102049609,622.0,0.519726602818578,0,1,/datauma/cluster-analysis,Tabular Playground Series - Jul 2022
8062,101933345,658.0,0.4840452321315524,0,3,/pythonkumar/clustering-k-means-dbscan-gmm-bgmm-dendogram-viz,Tabular Playground Series - Jul 2022
8063,99960179,633.0,0.1615037553885432,0,3,/tracyporter/jul-22-unsupervised-kmeans,Tabular Playground Series - Jul 2022
8064,99916551,638.0,0.2375603960805277,2,6,/yus002/tps-07-k-means,Tabular Playground Series - Jul 2022
8065,99952091,640.0,0.5179761817241069,4,27,/sfktrkl/tps-july-2022,Tabular Playground Series - Jul 2022
8066,99864370,643.0,0.1652179283765707,5,10,/codersaurabh/clustering-algorithms,Tabular Playground Series - Jul 2022
8067,101124040,632.0,,1,14,/abdulghaffaransari/pca-and-gmm-combo,Tabular Playground Series - Jul 2022
8068,101485451,662.0,0.4309834783428766,6,16,/muneeb2405/sklearn-clusteing,Tabular Playground Series - Jul 2022
8069,99852231,628.0,,11,40,/nikhilkhetan/setting-up-evaluation-metrics,Tabular Playground Series - Jul 2022
8070,101095887,683.0,0.5068267943245522,6,23,/akashmathur2212/the-ultimate-guide-to-unsupervised-ml,Tabular Playground Series - Jul 2022
8071,101824597,709.0,0.4994623359668275,0,2,/ahana09/july-tps,Tabular Playground Series - Jul 2022
8072,100506044,719.0,,0,15,/pragya1110/tps-july22-unsupervised-clustering-method,Tabular Playground Series - Jul 2022
8073,101665529,708.0,,0,3,/dername/tps-jul-22-eda,Tabular Playground Series - Jul 2022
8074,101577511,722.0,0.4940690573805619,1,5,/karlpetz/clustering-eda-model,Tabular Playground Series - Jul 2022
8075,102284971,738.0,,0,7,/yudumpacin/determinecontrolstates-v2,Tabular Playground Series - Jul 2022
8076,101914663,748.0,0.2206908462631862,0,4,/hirotokitamur/hk-tabular-playground-series-jul-2022,Tabular Playground Series - Jul 2022
8077,100553040,752.0,,4,14,/bibekupadhyaya/eda-pca-k-means,Tabular Playground Series - Jul 2022
8078,99800775,769.0,,10,21,/lucifergd192/clustering-is-all-you-need-kmeans-gauss-mix,Tabular Playground Series - Jul 2022
8079,100207684,761.0,,2,12,/bahadoreizadkhah/pca-gaussian-mixture,Tabular Playground Series - Jul 2022
8080,100145200,771.0,0.2566488509622725,6,15,/arunpurakkatt/eda-pca-kmeans-clustering,Tabular Playground Series - Jul 2022
8081,100482639,774.0,0.1445235126132896,1,8,/zuari1993/keeping-it-simple,Tabular Playground Series - Jul 2022
8082,100196775,793.0,0.2542082984366331,1,6,/sdysch/tps-july-2022,Tabular Playground Series - Jul 2022
8083,101996681,809.0,0.3889453227199633,2,6,/darnishmarshal/tps-july-2022-ensemble-mixture,Tabular Playground Series - Jul 2022
8084,102158465,813.0,0.1587386685434874,0,4,/troooonnn/tps-july-2022,Tabular Playground Series - Jul 2022
8085,102158465,813.0,0.3237087142727256,0,4,/troooonnn/tps-july-2022,Tabular Playground Series - Jul 2022
8086,102158465,813.0,0.2506824661396497,0,4,/troooonnn/tps-july-2022,Tabular Playground Series - Jul 2022
8087,102158465,813.0,0.3780720566896764,0,4,/troooonnn/tps-july-2022,Tabular Playground Series - Jul 2022
8088,101875470,820.0,,0,1,/roshanbhaipatel/notebook82eec1cb63,Tabular Playground Series - Jul 2022
8089,100978271,822.0,,8,13,/surendra01/kmeans-dbscan-gmm,Tabular Playground Series - Jul 2022
8090,101544749,825.0,,4,7,/ollibolli/gaussian-mixture-models-cheatsheet,Tabular Playground Series - Jul 2022
8091,99899188,830.0,0.2276940286689714,0,6,/nainapandey96/clustering-with-kmeans-and-gmm,Tabular Playground Series - Jul 2022
8092,102141864,836.0,,1,8,/nourhadrich/tab-play-with-k-means-pca-t-sne-beginner,Tabular Playground Series - Jul 2022
8093,102045089,842.0,,0,0,/tookiprotvic/kiptoo-pca,Tabular Playground Series - Jul 2022
8094,102210804,848.0,,8,13,/michaelmortenson/help-first-time-pca-here,Tabular Playground Series - Jul 2022
8095,100234883,851.0,0.2652564107781985,4,9,/antonellomartiello/tps-july22-eda-and-fuzzy-kmeans,Tabular Playground Series - Jul 2022
8096,101931186,862.0,1.841487985481863e-05,0,1,/varundurvasula/tps-clustering,Tabular Playground Series - Jul 2022
8097,101496271,883.0,0.2384467658340738,0,5,/taos2000/clustering-pca-kmeans-bayes-auto-encoder,Tabular Playground Series - Jul 2022
8098,100431726,893.0,,16,56,/firuzjuraev/tps-july-2022-clear-clustering-roadmap,Tabular Playground Series - Jul 2022
8099,100259779,926.0,,1,8,/saeidghomi/tabular-playground-kmeans,Tabular Playground Series - Jul 2022
8100,99837229,943.0,0.2418426666531469,1,7,/hasangam/scikit-learn-kmeans-clustering-baseline,Tabular Playground Series - Jul 2022
8101,102070024,947.0,0.2379997269853102,0,1,/ocanaydin/basic-clustering,Tabular Playground Series - Jul 2022
8102,100067924,945.0,0.2414065617599605,5,11,/taranmarley/pca-and-kmeans,Tabular Playground Series - Jul 2022
8103,100251598,992.0,0.2382208043446126,6,31,/milanvaddoriya/tabular-playground-july,Tabular Playground Series - Jul 2022
8104,100058259,1020.0,0.0331991974792104,2,7,/akanshakhandelwal08/tps-july-22,Tabular Playground Series - Jul 2022
8105,102192572,989.0,,0,3,/regiusherder/kmeans-clustering,Tabular Playground Series - Jul 2022
8106,100006405,1029.0,,2,7,/muki2003/tps-k-mean-clustering-tensorflow-dnn,Tabular Playground Series - Jul 2022
8107,99806814,1091.0,,3,13,/bannourchaker/auto-eda-part1,Tabular Playground Series - Jul 2022
8108,100969938,1101.0,,4,4,/biswadata/unsupervised-learning-clustering,Tabular Playground Series - Jul 2022
8109,102210407,1124.0,0.1741161276982599,0,1,/tariqchhussain/base-tps-july-2022,Tabular Playground Series - Jul 2022
8110,100432863,1152.0,,27,41,/leodaniel/k-means-clearly-explained,Tabular Playground Series - Jul 2022
8111,100654433,1164.0,,4,13,/dextermojo/eda-with-kmeans-and-famd,Tabular Playground Series - Jul 2022
8112,99964320,1165.0,0.0701806277139868,0,2,/mayureshnm/tps-july-22-with-mini-batch-k-means-clustering,Tabular Playground Series - Jul 2022
8113,100863300,1172.0,,6,7,/mohammadhossein77/tps-jul-pca-k-means,Tabular Playground Series - Jul 2022
8114,100799032,1227.0,,0,8,/harsh2040/intro-to-clustering,Tabular Playground Series - Jul 2022
8115,102132036,195.0,,0,6,/hikarutabata/resize-to-512x512-jpg,Mayo Clinic - STRIP AI
8116,107533197,29.0,,0,7,/yuahyodo/29th-place-solution,Mayo Clinic - STRIP AI
8117,101387887,443.0,,4,7,/tscheung/pytorch-mayo-clinic-baseline-resnet18,Mayo Clinic - STRIP AI
8118,100567180,265.0,,18,65,/yasufuminakama/mayo-train-images-size-1024-n-16-1,Mayo Clinic - STRIP AI
8119,102991781,12.0,,0,0,/sviatoslavsakharov/mayoclinic-patch-images-final,Mayo Clinic - STRIP AI
8120,105814693,481.0,,0,0,/limseonggeun/newbie-mayo-clinic-pb-0-6,Mayo Clinic - STRIP AI
8121,101598465,604.0,,3,99,/paulorzp/strip-ai-exploratory-data-analysis,Mayo Clinic - STRIP AI
8122,101949083,612.0,,10,35,,Mayo Clinic - STRIP AI
8123,101543635,47.0,0.6473614036649125,3,0,/takeajioka/inference-size-224-swin-tiny,Mayo Clinic - STRIP AI
8124,100481413,637.0,0.8394452821317623,1,13,/docxian/strip-ai-eda-of-structured-data,Mayo Clinic - STRIP AI
8125,104477113,664.0,,2,14,/zhehaoliang/eda-of-mayo-from-statistical-perspective,Mayo Clinic - STRIP AI
8126,103273828,671.0,0.5166086913145251,2,24,/rishavnandi/mayo-clinic,Mayo Clinic - STRIP AI
8127,104313513,180.0,0.712742863244836,3,8,/dongdongxzoez/glcm-lgbm-baseline,Mayo Clinic - STRIP AI
8128,104043510,571.0,,0,7,/hiba007/mayo-clinic-eda-making-tiles-removing-background,Mayo Clinic - STRIP AI
8129,106667840,463.0,,7,14,/raghavgarg12/data-pre-processing,Mayo Clinic - STRIP AI
8130,100840474,8.0,,0,7,/basfest/mayo-clinic-strip-ai-downscale-x30-png,Mayo Clinic - STRIP AI
8131,106401688,283.0,,0,1,/lau01b/strip-ai-training,Mayo Clinic - STRIP AI
8132,103022541,216.0,0.6358712659288824,2,18,/himanshunayal/mc-strip-ai-tensorflow-inference-public-lb-0-6,Mayo Clinic - STRIP AI
8133,105059432,209.0,,0,4,/matsutake94/mayo-aspect-ratio-analysis,Mayo Clinic - STRIP AI
8134,107520856,7.0,,2,12,/icemantd/feature-cluster-tile-pseudo-label-training-mayo,Mayo Clinic - STRIP AI
8135,100997969,218.0,,1,38,/alejopaullier/background-vs-clots-classifier,Mayo Clinic - STRIP AI
8136,102989270,760.0,,19,61,/nghihuynh/mc-strip-ai-exploratory-data-analysis,Mayo Clinic - STRIP AI
8137,104685743,533.0,,2,15,/qcqced/strip-ai-eda-data-preprocessing-1k-png,Mayo Clinic - STRIP AI
8138,107021508,164.0,,4,10,/saurabhsawhney/initial-impressions-and-dumbmodel-submission,Mayo Clinic - STRIP AI
8139,100292201,799.0,,6,35,/tmyok1984/mayo-convert-tif-to-jpg,Mayo Clinic - STRIP AI
8140,105394797,214.0,,0,0,/bobfromjapan/mayo-train-images-size-384-n-64,Mayo Clinic - STRIP AI
8141,107111535,204.0,,0,3,/nikitaglazunov/mayo-image-class-training,Mayo Clinic - STRIP AI
8142,107054603,3.0,0.6556448796653651,0,1,/sikeda/mayo-submission-multi512,Mayo Clinic - STRIP AI
8143,107195638,510.0,,0,1,/marchworks/fork-of-working-mayo-submition,Mayo Clinic - STRIP AI
8144,100598380,13.0,,4,33,/dschettler8845/mcsai-exploratory-data-analysis-baseline,Mayo Clinic - STRIP AI
8145,105955625,185.0,,22,54,/tr1gg3rtrash/mayo-clinic-best-preprocessing-notebook,Mayo Clinic - STRIP AI
8146,103137764,243.0,,22,91,/jirkaborovec/bloodclots-eda-load-wsi-prune-background,Mayo Clinic - STRIP AI
8147,104198948,230.0,,0,6,/jlcordoba/mayo-clinic-strip-ai-svc,Mayo Clinic - STRIP AI
8148,106203918,156.0,0.674656569632348,0,1,/devesh1496/conv-classifier,Mayo Clinic - STRIP AI
8149,103594351,168.0,,0,5,/rajatharigasp/mayo-eda,Mayo Clinic - STRIP AI
8150,107797281,35.0,,0,1,/xiejialun/notebook47db8c2e63,Mayo Clinic - STRIP AI
8151,104302167,535.0,,28,79,/junjitakeshima/mayo-simple-cnn-starter-eng,Mayo Clinic - STRIP AI
8152,108862855,54.0,,0,1,/daisypeartree/strokecode,Mayo Clinic - STRIP AI
8153,103253108,31.0,,0,6,/ksooklall/mayo-clinic-eda-and-preprocessing,Mayo Clinic - STRIP AI
8154,120823605,303.0,2.321181919391737,0,6,/aniruddhapa/classify-blood-clot-origin-in-ischemic-stroke,Mayo Clinic - STRIP AI
8155,101890478,63.0,,13,33,/manikanthgoud/mayo-clinic-strip-ai-exploratory-data-analysis,Mayo Clinic - STRIP AI
8156,102199993,64.0,,4,21,/raghavprabhakar66/stroke-blood-clot-classification,Mayo Clinic - STRIP AI
8157,100856303,85.0,,3,18,/iuryck/quick-blood-clot-slicing,Mayo Clinic - STRIP AI
8158,103361557,90.0,,0,1,/ernestogarciaruiz/mayo-clinic-strip-ai-baseline-submission,Mayo Clinic - STRIP AI
8159,104403069,28.0,,1,1,/djagatiya/strip-tiler-t1024-r224-n20,Mayo Clinic - STRIP AI
8160,100309289,131.0,0.6933247011386958,12,31,/venkatkumar001/stripai-baseline-understanding-only-csv,Mayo Clinic - STRIP AI
8161,100322156,132.0,0.6931649489105377,0,0,/josephkibira/mayo-clinic,Mayo Clinic - STRIP AI
8162,101015933,540.0,,8,81,/analokamus/a-fast-tile-generation,Mayo Clinic - STRIP AI
8163,106717432,141.0,,0,5,/yinhaojie/baseline-with-resnet-by-paddle,Mayo Clinic - STRIP AI
8164,105087544,145.0,,0,0,/v1olet1nor1/mayo-make-data,Mayo Clinic - STRIP AI
8165,104847806,51.0,0.7547674828374062,1,12,/rodrigocarrillo/import-model-trained-locally-20220715,Mayo Clinic - STRIP AI
8166,102392158,769.0,,11,27,/minhajulhoque/mayo-clinic-efficientnet-transfer-learning,Mayo Clinic - STRIP AI
8167,102974879,169.0,,1,11,/raufmomin/weighted-multi-class-logarithmic-loss-function,Mayo Clinic - STRIP AI
8168,103389218,149.0,,6,5,/vyacheslavshen/vit-train-submission-pipeline,Mayo Clinic - STRIP AI
8169,103597204,179.0,,2,4,/maunilshah/stroke-blood-clot-origin-training,Mayo Clinic - STRIP AI
8170,105097634,9.0,,0,2,/fujiyu/cnn-strip-ai-inference-ecc345,Mayo Clinic - STRIP AI
8171,102573935,819.0,,0,9,/yiheng/load-wsi-and-extract-patches-with-monai,Mayo Clinic - STRIP AI
8172,106638774,572.0,,0,0,/datakite/mayo-clinic-classification,Mayo Clinic - STRIP AI
8173,104928943,505.0,,1,10,/sakima/medical-whole-slide-processing-speed-up,Mayo Clinic - STRIP AI
8174,104304926,844.0,0.7486796327504033,0,10,/solapurruchitha/mayo-simple-cnn,Mayo Clinic - STRIP AI
8175,107712229,437.0,,0,3,/vijaybj/top-score-preprocessing-mayo-clinic,Mayo Clinic - STRIP AI
8176,103066832,400.0,,14,11,/iraqai/facebook-deit-torch-lightning-starter-train,Mayo Clinic - STRIP AI
8177,100250406,866.0,,5,23,/towhidultonmoy/implementing-custom-weighted-multi-class-log-loss,Mayo Clinic - STRIP AI
8178,101652738,440.0,,0,0,/mongramosjr/minivggnet-training-on-stroke-blood-clot,Mayo Clinic - STRIP AI
8179,104147724,830.0,0.7719546657599862,0,14,/jonathanma02/cnn-blood-clot-origin-classifier,Mayo Clinic - STRIP AI
8180,102000636,514.0,,1,2,/joshuacburt/mayo-clinic-strip-stroke-blood-clot-origin-1-8,Mayo Clinic - STRIP AI
8181,104944375,325.0,0.945711986899598,0,4,/rajnishkumar546/clinic-strip,Mayo Clinic - STRIP AI
8182,109238412,499.0,0.9505819512055746,0,0,/raghava50/notebookeac6784007,Mayo Clinic - STRIP AI
8183,100389613,558.0,0.806808570164281,3,33,/awaldeep/first-look-eda-baseline-sub,Mayo Clinic - STRIP AI
8184,100546638,559.0,0.806808570164281,13,38,/arunpurakkatt/eda-image-processing-exploration,Mayo Clinic - STRIP AI
8185,104927546,569.0,,0,1,/wowzwzw/pytorch-mayo-clinic-baseline-resnet18,Mayo Clinic - STRIP AI
8186,106817514,570.0,,0,0,/s0mes0me/transmil-for-h5,Mayo Clinic - STRIP AI
8187,106704890,542.0,,1,9,/leweisele/mayo-clinic-strip-ai-patch-sampler,Mayo Clinic - STRIP AI
8188,104161229,815.0,,0,1,/sphadtare/resnet,Mayo Clinic - STRIP AI
8189,105341264,157.0,0.8704883405164562,0,0,/hateflow/strip-ai-submission-pipeline,Mayo Clinic - STRIP AI
8190,103872500,833.0,,0,5,/abhilashojha/model-training,Mayo Clinic - STRIP AI
8191,106187412,856.0,,0,5,/lavanyaadapa501/mayo-clinic-strip-ai,Mayo Clinic - STRIP AI
8192,115057370,537.0,3.683308408085254,0,1,/lilysica/cnn-model-submission,Mayo Clinic - STRIP AI
8193,101959905,776.0,,1,1,/frozenwolf/vit-pytorch-training-inference,Mayo Clinic - STRIP AI
8194,104463260,812.0,,0,7,/abhisekdash37/mayo-dataset-of-img-slices,Mayo Clinic - STRIP AI
8195,100535338,591.0,,11,29,/nickuzmenkov/strip-ai-eda-data-preparation,Mayo Clinic - STRIP AI
8196,102140927,797.0,1.3344940449339984,1,4,/klukin/mayo-sub,Mayo Clinic - STRIP AI
8197,100562690,841.0,,4,10,/xiafire/split-image-to-256-256-patch-256-256-patch,Mayo Clinic - STRIP AI
8198,106455476,850.0,5.452566251463368,0,4,/kareemusama/blood-origin-classification,Mayo Clinic - STRIP AI
8199,107634430,863.0,,0,0,/thomaspdm/mayoclinic-pipeline,Mayo Clinic - STRIP AI
8200,108188341,2.0,0.6945884640311071,6,13,/w3579628328/2nd-place-solution,Google Universal Image Embedding
8201,107693455,6.0,,0,0,/socratis/guie-clip-pca,Google Universal Image Embedding
8202,108525063,4.0,0.5784726722834295,4,31,/simjeg/guie-a-zero-shot-solution,Google Universal Image Embedding
8203,104588931,10.0,,6,24,/yamash73/guie-clip-w-o-adaptiveavgpooling,Google Universal Image Embedding
8204,102898451,19.0,0.3743357096565131,0,0,/kerrit/gim-v2-clip,Google Universal Image Embedding
8205,106513793,18.0,,0,0,/ammarali32/guie-tfrecord-met,Google Universal Image Embedding
8206,103849636,23.0,,1,14,/motono0223/guei-keras-load-tfrecords,Google Universal Image Embedding
8207,107626574,35.0,0.6319399438323606,0,2,/klekovkin/35th-place-2xclip,Google Universal Image Embedding
8208,107710849,40.0,,2,5,/slavabarkov/google-universal-image-embedding-submission,Google Universal Image Embedding
8209,103285852,37.0,,1,9,/alenic/clip-gradcam,Google Universal Image Embedding
8210,101746397,38.0,0.0,2,5,/manwithaflower/help-to-find-mistake-please,Google Universal Image Embedding
8211,102015536,52.0,,5,39,/evilpsycho42/understand-comp-domain-and-imagenet-21k-labels,Google Universal Image Embedding
8212,107652830,76.0,0.0,0,2,/ogidif/openclip-laion2b-with-omnibenchmarkv2-and-nca,Google Universal Image Embedding
8213,106705966,71.0,,0,3,/jslim7/guie-130k-tfrecord,Google Universal Image Embedding
8214,105111907,83.0,0.2935191186001291,2,1,/kirderf/baseline-from-2020-score-boost-idea,Google Universal Image Embedding
8215,103657998,88.0,,1,11,/emphymachine/clip-embeddings-convnext-swin-tta,Google Universal Image Embedding
8216,101208517,101.0,0.3299740764744004,1,6,/algerwang/embeddings-brute-force,Google Universal Image Embedding
8217,107220597,105.0,0.5017174335709653,5,23,/natnitarach/guie-0-0-vit-l-14-336px-vit-h-14-224px-laion2b,Google Universal Image Embedding
8218,100836107,126.0,,0,3,/kolovrado/visual-transformer-pretrained-0-254,Google Universal Image Embedding
8219,102911956,177.0,0.4472564268740548,0,5,/dragonzhang/rn50x64-vit-l-14-openai-clip,Google Universal Image Embedding
8220,104530652,206.0,0.2230719377835379,0,0,/tombot231/basic-submit-coca-e6e4e5,Google Universal Image Embedding
8221,104279478,278.0,,0,19,/ivanpan/pytorch-clip-onnx-to-speed-up-inference,Google Universal Image Embedding
8222,101755922,281.0,0.3429142363361419,3,6,/hwigeon/guie-dino-pretrained-weight-submission,Google Universal Image Embedding
8223,104634654,295.0,0.3813134586303738,3,25,/tmyok1984/image-embedding-timm-pretrained-weights,Google Universal Image Embedding
8224,104032458,312.0,0.4536184921149273,4,41,/hmendonca/torch-official-clip-timm-embeddings,Google Universal Image Embedding
8225,102742409,320.0,,0,26,/seshurajup/guie-check-approx-estimate-time-before-submit,Google Universal Image Embedding
8226,104690159,338.0,0.0126593216677468,0,5,/e0xextazy/beit-embedding-baseline,Google Universal Image Embedding
8227,101845368,411.0,0.385742060920285,0,2,/tscheung/embeddings-brute-force,Google Universal Image Embedding
8228,101806034,442.0,0.4051306977748974,2,36,/iglovikov/who-can-improve-the-score,Google Universal Image Embedding
8229,105370346,452.0,0.4832469215813353,4,13,/michailindmitry/how-to-use-sklearn-pca-in-submission,Google Universal Image Embedding
8230,104761488,453.0,,3,15,/vitaliykinakh/gpr1200-benchmark-images-retrieval,Google Universal Image Embedding
8231,101938059,491.0,,0,3,/massy103/pytorch-sample-gpu-submittion,Google Universal Image Embedding
8232,101897759,503.0,,11,31,/orkatz2/who-can-improve-the-score-simple-flip-tta,Google Universal Image Embedding
8233,103397958,543.0,,1,16,/yosefdk/model-evaluator-script,Google Universal Image Embedding
8234,102058896,512.0,0.4588248001728237,3,31,/arstimgames/clip-embeddings,Google Universal Image Embedding
8235,102626906,508.0,0.2911427954201769,5,9,/bcabcae/pca-dim-reduction-on-cifar,Google Universal Image Embedding
8236,101682728,566.0,,7,38,/moeinshariatnia/random-vs-avg-max-dim-reduction,Google Universal Image Embedding
8237,107445491,633.0,0.4472564268740548,0,0,/brandonlwillett/googleuniversalembedding,Google Universal Image Embedding
8238,100685247,596.0,0.2179088356016416,3,37,/dschettler8845/guie-in-depth-eda-baseline-similarity-model-tf,Google Universal Image Embedding
8239,107670868,637.0,0.0129617627997407,0,0,/doanthinhvo/who-can-improve-the-score,Google Universal Image Embedding
8240,103928741,660.0,,7,50,/queyrusi/efficientnet-elements-of-image-embedding,Google Universal Image Embedding
8241,101363701,661.0,0.385158781594297,0,17,/omomo17/convnext-xlarge-baseline,Google Universal Image Embedding
8242,106361673,741.0,0.385742060920285,2,8,/saraswatitiwari/google-universal-image-embedding,Google Universal Image Embedding
8243,106361673,741.0,0.385742060920285,2,8,/saraswatitiwari/google-universal-image-embedding,Google Universal Image Embedding
8244,102905945,792.0,0.360218189673795,0,2,/shreydan/baseline-submission-convnext-base-in22ft1k,Google Universal Image Embedding
8245,102310487,799.0,0.3300928926333978,0,16,/rhtsingh/google-universal-image-embedding-convnext-infer,Google Universal Image Embedding
8246,104556368,804.0,0.3442752214301143,0,0,/hendrikjoosten/guie-pytorch-ensembling-cool-name-models,Google Universal Image Embedding
8247,107171397,829.0,0.3070209548498594,1,1,/youseefmoemen/transfer-learning-using-bit,Google Universal Image Embedding
8248,101004647,837.0,0.2888636854612224,0,2,/skoushik/swin-pretrained-embeddings,Google Universal Image Embedding
8249,101419912,863.0,,2,41,/carloalbertobarbano/pytorch-ensemble-pretrained-baselines-training,Google Universal Image Embedding
8250,108766857,935.0,0.4148736228127031,0,3,/sarindasamarasinghe/assigment-3-cap6411,Google Universal Image Embedding
8251,108766857,935.0,0.4148736228127031,0,3,/sarindasamarasinghe/assigment-3-cap6411,Google Universal Image Embedding
8252,100747951,951.0,,3,5,/yashvrdnjain/guie-pytorch-baseline-train,Google Universal Image Embedding
8253,101027219,980.0,0.1736228127025272,2,4,/gopalgoyal612002/image-embadding,Google Universal Image Embedding
8254,113393402,4.0,,11,12,/pearsejim01/fiverr-spam-2nd-in-publiclb-and-privatelb,Predict Potential Spammers on Fiverr
8255,103667877,5.0,0.891239235397975,2,3,/gehallak/fiverr-eda-lgbm,Predict Potential Spammers on Fiverr
8256,105805257,13.0,0.9002086446413857,1,8,/fritzcremer/a-24-line-solution,Predict Potential Spammers on Fiverr
8257,105095246,38.0,,0,0,/vizdom/fiverr-xgb-tuned,Predict Potential Spammers on Fiverr
8258,112231098,19.0,,34,97,/ravi20076/fiverr-extensive-eda,Predict Potential Spammers on Fiverr
8259,102069596,31.0,0.8801889945552905,3,12,/chtalhaanwar/fiverr-spammer-automl-solution-complete,Predict Potential Spammers on Fiverr
8260,102835086,10.0,0.8984043839996635,1,10,/sahaaaanattygalle/fiverr-spam-pred-basic-eda-h20,Predict Potential Spammers on Fiverr
8261,103141350,56.0,0.8899642480786791,6,15,/nitinchoudhary012/fiverr-spammers-detection,Predict Potential Spammers on Fiverr
8262,102854273,7.0,0.8966280625310553,8,27,/kaniya/fiverr-spammers-automl-guided-solution,Predict Potential Spammers on Fiverr
8263,102499321,6.0,0.866267888158069,13,25,/hskhawaja/fiverr-spammer-pycaret-automl,Predict Potential Spammers on Fiverr
8264,105009474,34.0,0.891233117494955,2,15,/cbhavik/fiverr-xgb-tuned-eda,Predict Potential Spammers on Fiverr
8265,103980630,74.0,0.889713247329756,10,24,/qayyum453/fiverr-spammer-xgbclassifier-model,Predict Potential Spammers on Fiverr
8266,103067470,30.0,,1,2,/zakariabentaleb/predict-spammers-on-fiverr-features-selection,Predict Potential Spammers on Fiverr
8267,105762946,67.0,0.8940077284235114,4,6,/shibumohapatra/fiverr,Predict Potential Spammers on Fiverr
8268,104688727,110.0,,0,8,/bachaboos/cnn-predict-potential,Predict Potential Spammers on Fiverr
8269,106567097,45.0,,1,3,/razarizwanahmed/predict-potential-spammers,Predict Potential Spammers on Fiverr
8270,106809863,77.0,,0,0,/shaharyarsajid/predict-random-forest,Predict Potential Spammers on Fiverr
8271,102665583,94.0,0.887091898184351,0,1,/haseeb85/fiverr-spammer-detection-xgboost,Predict Potential Spammers on Fiverr
8272,103603507,98.0,,0,14,/lucasmorin/fiverr-lgbm-ensemble,Predict Potential Spammers on Fiverr
8273,102284274,117.0,0.8771745081333657,0,1,/navinpatwari/spammer-on-fiverr,Predict Potential Spammers on Fiverr
8274,109586774,113.0,,0,2,/ziadhamadafathy/predict-spammers-on-fiverr-with-using-ml-models,Predict Potential Spammers on Fiverr
8275,129186689,119.0,,3,8,/rsesha/aicamp-special-suloclassifier-87-score,Predict Potential Spammers on Fiverr
8276,102729897,127.0,,2,3,/rishabh2007/86-fiver-potential-spammers,Predict Potential Spammers on Fiverr
8277,102758773,141.0,,2,6,/ahmadarsim/fiverr-spam-machine-learning-with-high-score-97-7,Predict Potential Spammers on Fiverr
8278,102216448,13.0,,8,21,/bardiakh/monai-io-windowing-overlay-saving,RSNA 2022 Cervical Spine Fracture Detection
8279,109255300,22.0,0.4208094218967808,0,1,/longyikim/22nd-inference-code,RSNA 2022 Cervical Spine Fracture Detection
8280,106596054,34.0,,0,4,/solverworld/rsna2022-comp-metric,RSNA 2022 Cervical Spine Fracture Detection
8281,105002810,49.0,,0,1,/bernardohenz/dataset-test-sorted,RSNA 2022 Cervical Spine Fracture Detection
8282,109337582,58.0,,0,1,/arunodhayan/effib1ns,RSNA 2022 Cervical Spine Fracture Detection
8283,109050951,50.0,0.5247098255349721,0,0,/shigengtian/window-infer-single-model-lb,RSNA 2022 Cervical Spine Fracture Detection
8284,108135987,70.0,0.481221618170062,1,13,/chenboluo/infer-pytorch-effnetv2-single-model-mlp,RSNA 2022 Cervical Spine Fracture Detection
8285,105978094,90.0,,0,11,/charliezimmerman/competition-metric-numpy-train-format-v2,RSNA 2022 Cervical Spine Fracture Detection
8286,104527826,461.0,,4,52,/jirkaborovec/spine-fracture-eda-loading-dicom-3d-browse,RSNA 2022 Cervical Spine Fracture Detection
8287,103711756,472.0,,6,12,/vmuzhichenko/rsna-22-dicom-to-numpy-3d,RSNA 2022 Cervical Spine Fracture Detection
8288,103767136,208.0,,1,14,/itsuki9180/create-idwise-tf-records,RSNA 2022 Cervical Spine Fracture Detection
8289,108114024,161.0,,0,3,/fx6300/binary-weighted-log-loss,RSNA 2022 Cervical Spine Fracture Detection
8290,102191823,163.0,,3,32,/tscheung/quick-data-look-rough-data-clean-easy-cnn,RSNA 2022 Cervical Spine Fracture Detection
8291,108256438,120.0,,0,10,/juwonyeo/rsna-fracture-detection-ensemble,RSNA 2022 Cervical Spine Fracture Detection
8292,107414069,195.0,,9,22,/dinowun/eda-simplified-rsna-cfd,RSNA 2022 Cervical Spine Fracture Detection
8293,130807097,102.0,,0,1,/vulpestrader/rsna-fracture-detection-ensemble-solution,RSNA 2022 Cervical Spine Fracture Detection
8294,103989458,455.0,,0,0,/maxmelichov/help-me,RSNA 2022 Cervical Spine Fracture Detection
8295,102211203,224.0,,0,5,,RSNA 2022 Cervical Spine Fracture Detection
8296,103452735,230.0,0.5661768609161081,0,0,/ayanjhunjhunwala/ayan-efficientnetimprove,RSNA 2022 Cervical Spine Fracture Detection
8297,104046366,269.0,,5,19,/toghrultahirov/tensorflow-simple-cnn-architecture,RSNA 2022 Cervical Spine Fracture Detection
8298,106587851,301.0,,5,45,/sparkyjunior/windowing-in-ct-scans,RSNA 2022 Cervical Spine Fracture Detection
8299,103964530,394.0,0.5670023621184169,0,1,/robber19/ir3d-inference,RSNA 2022 Cervical Spine Fracture Detection
8300,104889265,447.0,,0,18,/eliudmunyala/teamkenya-eda,RSNA 2022 Cervical Spine Fracture Detection
8301,109336392,449.0,,3,6,/titericz/cx-segmentation,RSNA 2022 Cervical Spine Fracture Detection
8302,109244211,452.0,,0,4,/seyered/eda-rsna-2022-cervical-spine,RSNA 2022 Cervical Spine Fracture Detection
8303,105097476,481.0,,0,5,/mersotc/load-jpeg-lossless-images-with-simpleitk,RSNA 2022 Cervical Spine Fracture Detection
8304,104101358,506.0,,0,1,/shihhsuanchen/cspine-overview,RSNA 2022 Cervical Spine Fracture Detection
8305,122160977,507.0,,0,0,/doyeonkimm/croppingvoxel29slices,RSNA 2022 Cervical Spine Fracture Detection
8306,113435809,540.0,,0,0,/hieunt01/rsna-eda,RSNA 2022 Cervical Spine Fracture Detection
8307,104176885,608.0,,0,0,/barteksadlej123/rsna-2022-cervical-spine-monai-numpy-input,RSNA 2022 Cervical Spine Fracture Detection
8308,108040030,676.0,,1,8,/juhjoo/rsna-2022-tfrecords,RSNA 2022 Cervical Spine Fracture Detection
8309,104493566,551.0,,10,49,/nghihuynh/rsna-cervical-spine-fracture-eda,RSNA 2022 Cervical Spine Fracture Detection
8310,104635846,671.0,,1,2,/ikorol/creating-data-set-with-preprocessed-dcm-images,RSNA 2022 Cervical Spine Fracture Detection
8311,103588606,543.0,,0,2,/kvsnoufal/convnext-on-sagittal-slices,RSNA 2022 Cervical Spine Fracture Detection
8312,104180291,545.0,,0,2,/maunilshah/rsna-cervical-spine-fracture-detection,RSNA 2022 Cervical Spine Fracture Detection
8313,111138962,691.0,,0,4,/ankitraj23/rsna-2022-tf-keras-training-phase-with-tpu,RSNA 2022 Cervical Spine Fracture Detection
8314,103539915,609.0,,9,52,/leventelippenszky/rsna-eda-dicom-segmentations-bboxes-3d-plot,RSNA 2022 Cervical Spine Fracture Detection
8315,105584749,688.0,,4,4,/drrajkulkarni/pytorch-rsna-mini-resnet50,RSNA 2022 Cervical Spine Fracture Detection
8316,105974856,583.0,,0,0,/junhyeonkwon/about-dcm-orientation,RSNA 2022 Cervical Spine Fracture Detection
8317,102258194,611.0,,4,16,/kretes/segmentations-fracture-zoom-in,RSNA 2022 Cervical Spine Fracture Detection
8318,103280447,622.0,,16,100,/thedevastator/tf-rsna-efficient-net-baseline,RSNA 2022 Cervical Spine Fracture Detection
8319,102235043,632.0,,0,9,/bluech/dicom-eda-wip-cspine-fracture-detection,RSNA 2022 Cervical Spine Fracture Detection
8320,108135903,784.0,0.5724543511706052,0,3,/myominhtet/efficientnet-v2-infer,RSNA 2022 Cervical Spine Fracture Detection
8321,104019532,767.0,,5,57,/ipythonx/cervical-spine-fracture-detection-quick-eda,RSNA 2022 Cervical Spine Fracture Detection
8322,103163736,775.0,,5,44,/kongaevans/tensorflow-data-input-pipeline-alexnet-cnn,RSNA 2022 Cervical Spine Fracture Detection
8323,108292074,675.0,,0,12,/significantbutter/preprocess-cropping-vertebrae-with-yolo,RSNA 2022 Cervical Spine Fracture Detection
8324,108994697,785.0,,0,0,/morganmb/data-preparation-64x64x64-interpol-order-3,RSNA 2022 Cervical Spine Fracture Detection
8325,105439042,740.0,0.5825238906447301,0,2,/chuckhatt/dummy-notebook,RSNA 2022 Cervical Spine Fracture Detection
8326,105197692,812.0,,0,6,/weixinxu/infer-pytorch-effnetv2-single-model-pl-0-49,RSNA 2022 Cervical Spine Fracture Detection
8327,105739545,682.0,,4,10,/amineteffal/helloworld-rsna,RSNA 2022 Cervical Spine Fracture Detection
8328,104042680,872.0,,0,14,/anoukstein/simplify-data-by-creating-sagittal-slices,RSNA 2022 Cervical Spine Fracture Detection
8329,102001683,819.0,,0,23,/queyrusi/fastest-submission-in-the-west,RSNA 2022 Cervical Spine Fracture Detection
8330,102361261,823.0,,1,13,/mohdmuttalib/cervical-fractures-pydicom-fastai,RSNA 2022 Cervical Spine Fracture Detection
8331,107953914,836.0,,2,9,/vigneshirtt/rsna2022-keras-competition-loss,RSNA 2022 Cervical Spine Fracture Detection
8332,108582740,849.0,,0,0,/aparida/vit-trials,RSNA 2022 Cervical Spine Fracture Detection
8333,109219264,863.0,,0,0,/mridulmittal/iiita-final-submission,RSNA 2022 Cervical Spine Fracture Detection
8334,107998063,871.0,4.319344502611578,0,1,/samanthahassal/cervical-spine-fracture,RSNA 2022 Cervical Spine Fracture Detection
8335,107998063,871.0,4.193974798945186,0,1,/samanthahassal/cervical-spine-fracture,RSNA 2022 Cervical Spine Fracture Detection
8336,107998063,871.0,3.863731920503221,0,1,/samanthahassal/cervical-spine-fracture,RSNA 2022 Cervical Spine Fracture Detection
8337,107998063,871.0,4.358359532865901,0,1,/samanthahassal/cervical-spine-fracture,RSNA 2022 Cervical Spine Fracture Detection
8338,107998063,871.0,4.342517104561256,0,1,/samanthahassal/cervical-spine-fracture,RSNA 2022 Cervical Spine Fracture Detection
8339,102867365,873.0,,2,2,/hitarthagarwal/rsnacf-comp1,RSNA 2022 Cervical Spine Fracture Detection
8340,103542403,11.0,0.5909532242305814,38,82,/pourchot/hunting-for-missing-values,Tabular Playground Series - Aug 2022
8341,103291904,551.0,,2,17,/crained/preprocessing-eda-tps-aug22,Tabular Playground Series - Aug 2022
8342,104370286,101.0,,4,12,/infrarosso/tps-aug-2022-eda-lgbm-model-random-search,Tabular Playground Series - Aug 2022
8343,104269617,757.0,,6,30,/mhslearner/tps-aug-eda-keras-neural-network,Tabular Playground Series - Aug 2022
8344,104571818,602.0,0.585967472724312,2,19,/tinfufans/aug2022,Tabular Playground Series - Aug 2022
8345,103618458,368.0,0.5864032730825598,9,33,,Tabular Playground Series - Aug 2022
8346,105402720,815.0,,9,59,,Tabular Playground Series - Aug 2022
8347,102695715,788.0,0.5895511724474841,1,11,/alikayed/tps08-logisticregression-and-some-fe-c83a47,Tabular Playground Series - Aug 2022
8348,108753434,808.0,,34,88,/ravi20076/tpsaug22-extensiveeda,Tabular Playground Series - Aug 2022
8349,104598925,820.0,0.5939647451555121,4,42,/durgeshrao9993/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8350,104598925,820.0,0.5939647451555121,4,42,/durgeshrao9993/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8351,104046978,799.0,0.5939213890245888,5,11,/rhythmcam/optimize-score-round,Tabular Playground Series - Aug 2022
8352,104504615,779.0,0.5939559925093633,0,14,/anubhavde/tabular-playground-series-august2022,Tabular Playground Series - Aug 2022
8353,103109784,701.0,0.5787997679531021,0,6,/hikarutabata/tps-aug22-minimum-lgbm,Tabular Playground Series - Aug 2022
8354,103597026,601.0,,52,103,/devsubhash/tps-august-eda-failure-prediction,Tabular Playground Series - Aug 2022
8355,102294371,765.0,,7,15,/maxsarmento/easy-eda-with-pandas-profiling,Tabular Playground Series - Aug 2022
8356,102877531,746.0,0.5853606904412962,13,46,/sarthmirashi07/soak-it-all-up-tps-aug22-bagging-ensemble,Tabular Playground Series - Aug 2022
8357,104005088,376.0,0.5020941214785866,6,30,/kostiantynlavronenko/tps-08-22-logistic-regression,Tabular Playground Series - Aug 2022
8358,104541117,583.0,0.5913964541605602,5,35,/mehrankazeminia/tps22aug-logisticr-lgbm-keras,Tabular Playground Series - Aug 2022
8359,102349009,638.0,0.5758485995766162,1,8,/trixytea/tps-aug-22-lightgbm-logistic-regression,Tabular Playground Series - Aug 2022
8360,102272858,916.0,0.5037985466536394,2,15,/darnishmarshal/tps-aug-22-lightgbm-baseline,Tabular Playground Series - Aug 2022
8361,102485219,921.0,0.5849017871682136,1,8,/remyharris/tps-aug-22-logistic-ga-features-selection,Tabular Playground Series - Aug 2022
8362,102485219,921.0,0.5819331134994301,1,8,/remyharris/tps-aug-22-logistic-ga-features-selection,Tabular Playground Series - Aug 2022
8363,103607300,47.0,,0,8,/sejoongkim/tps-aug2022-filling-out-missing-values,Tabular Playground Series - Aug 2022
8364,104560526,20.0,0.5911400830483634,4,28,/act18l/stacked-model-mlp-logisticregression-random,Tabular Playground Series - Aug 2022
8365,104649486,320.0,0.5889112115290669,2,3,/shimizuyusyuke/tps-aug-22-optimizing-ensemble-weights-optuna,Tabular Playground Series - Aug 2022
8366,102942563,106.0,,2,21,/mattop/race-to-lb-0-6-keep-it-simple-tps-aug-2022,Tabular Playground Series - Aug 2022
8367,104695297,359.0,0.5910798322748738,1,3,/nortontok/tab-playground-competition,Tabular Playground Series - Aug 2022
8368,104809144,28.0,,22,69,/vishnu123/tps-aug-22-top-2-logistic-regression-cv-fe,Tabular Playground Series - Aug 2022
8369,104657120,487.0,0.58918213645986,0,0,/argyrisanastopoulos/private-score-0-59144-combine-logisticregression,Tabular Playground Series - Aug 2022
8370,102266380,9.0,,2,28,/takanashihumbert/interesting-patterns-found-in-category-features,Tabular Playground Series - Aug 2022
8371,104234686,569.0,0.5737056261195245,0,6,/scchuy/tps-202208-eda-resample-lgb,Tabular Playground Series - Aug 2022
8372,106404324,513.0,,14,29,/mohamedalisalama/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8373,103241768,501.0,,0,5,/canonicalized/basic-logisticregression-model,Tabular Playground Series - Aug 2022
8374,104439825,504.0,0.5917256961406937,1,4,/saraswatitiwari/tabular-playground-series-august-2022,Tabular Playground Series - Aug 2022
8375,125067082,74.0,,25,64,/usamabalochhh/eda-full-logistic-regression-explanation,Tabular Playground Series - Aug 2022
8376,103665398,160.0,,7,25,/heoquixote/tps-aug-2022-lgbmimputer-pycaret-0-59065,Tabular Playground Series - Aug 2022
8377,102683452,620.0,,62,213,/ambrosm/tpsaug22-eda-which-makes-sense,Tabular Playground Series - Aug 2022
8378,102763074,309.0,0.5876150056993975,0,26,/themikejones/tps-aug-22-votingclassifier,Tabular Playground Series - Aug 2022
8379,104535038,41.0,,25,92,/desalegngeb/tps08-logisticregression-qlattice,Tabular Playground Series - Aug 2022
8380,103583237,201.0,,0,7,/eunbhinkim/tps-final2,Tabular Playground Series - Aug 2022
8381,104661558,425.0,0.5793199397492265,4,3,/geokocha/lightgbm-tps-aug,Tabular Playground Series - Aug 2022
8382,103957768,177.0,,0,12,/sophieb/tps-aug-22-eda-baseline-with-pipeline,Tabular Playground Series - Aug 2022
8383,103379436,365.0,0.5910782038755903,14,76,/thedevastator/tps-aug-simple-baseline,Tabular Playground Series - Aug 2022
8384,103634864,475.0,,2,17,/andreasstavrou/tps-august-eda-preprocessing-baseline,Tabular Playground Series - Aug 2022
8385,103582530,323.0,0.5746323888617489,16,54,/ashaykatrojwar/tps-aug-neural-network-and-eda,Tabular Playground Series - Aug 2022
8386,106596546,54.0,,6,25,/pietromaldini1/standing-on-the-head-of-giants-nn-optuna,Tabular Playground Series - Aug 2022
8387,102331063,81.0,0.5850183194919394,3,8,/heyspaceturtle/tps-aug22-logistic-regression,Tabular Playground Series - Aug 2022
8388,102500212,305.0,,4,23,/arootda/tps-aug-22-eda-pycaret-baseline,Tabular Playground Series - Aug 2022
8389,103286278,328.0,0.5907460104217555,5,25,/holliwainwright/tps-aug-12-fe-logisticregression-random,Tabular Playground Series - Aug 2022
8390,103223015,329.0,,7,8,/abdullahsangha/tps-aug-eda-nulls-lgbmimpute-xgboost,Tabular Playground Series - Aug 2022
8391,103902315,129.0,0.5906035254844488,0,0,/zhialexanderyang/tabular-playground-series-trial,Tabular Playground Series - Aug 2022
8392,102633828,227.0,0.5854011968734734,0,5,/leehann/simple-effective-logistic-regression-deepshare,Tabular Playground Series - Aug 2022
8393,115404632,57.0,,3,25,/jcaliz/tps-aug22-eda-logisticregression,Tabular Playground Series - Aug 2022
8394,102518536,7.0,,0,1,/amritsarkar/tabular-playground-blended,Tabular Playground Series - Aug 2022
8395,104686899,6.0,,7,21,/alvinleenh/tpsaug22-ensemble-ctb-lgb-lr,Tabular Playground Series - Aug 2022
8396,103450658,181.0,0.5904144276176518,12,21,/majidabdoos/tps-aug-2022-lgbmimputer-pca-lr-0-59041,Tabular Playground Series - Aug 2022
8397,102914604,247.0,0.5837815502361179,1,5,/dongjun819/tps-aug-2022,Tabular Playground Series - Aug 2022
8398,103988653,566.0,0.5758296694349454,1,5,/ayhampar/lightgbm-quickstart,Tabular Playground Series - Aug 2022
8399,105237763,179.0,,5,10,/gauravmalik26/tps-august-2022-highest-score-late-submission,Tabular Playground Series - Aug 2022
8400,104504039,223.0,,8,20,/juhjoo/0-5902-tps-aug-lightgbm-xgboost-ann-ensemble,Tabular Playground Series - Aug 2022
8401,102368462,880.0,,0,16,/hivanya/logisticregression-and-fill-nan-by-imputers,Tabular Playground Series - Aug 2022
8402,102504314,173.0,0.5858526705748249,8,48,/taronic/tps-eda-feature-engineering-selection-more,Tabular Playground Series - Aug 2022
8403,102980881,844.0,0.5901388210389188,25,81,/samuelcortinhas/tps-aug-22-failure-prediction,Tabular Playground Series - Aug 2022
8404,105393265,56.0,,2,3,/rockyyashchauhan/aug-chal-for-top-100-score,Tabular Playground Series - Aug 2022
8405,103958759,347.0,,0,9,/kuntzej/tps-aug-2022-relationship-btwn-products,Tabular Playground Series - Aug 2022
8406,103900521,22.0,,1,12,/hamidrezabakhtaki/tp-aug-2022-v2,Tabular Playground Series - Aug 2022
8407,103363884,83.0,,0,3,/slythe/tps-aug-22-first-look,Tabular Playground Series - Aug 2022
8408,102261998,259.0,0.5828663898387885,1,10,/alexryzhkov/tps-aug-22-lightautoml-starter,Tabular Playground Series - Aug 2022
8409,102883736,275.0,0.5897958394398306,2,15,/delai50/standing-on-the-head-of-giants-more-fe,Tabular Playground Series - Aug 2022
8410,104282870,14.0,,0,3,/nourhadrich/tps-aug-neural-network,Tabular Playground Series - Aug 2022
8411,103105282,44.0,0.5877898550724637,2,7,/ameerhamza0311/simple-baseline,Tabular Playground Series - Aug 2022
8412,102699236,135.0,,2,5,/windvoice/tps-aug2022-extratrees-optuna-tuning-example,Tabular Playground Series - Aug 2022
8413,103065894,385.0,0.589446547793519,0,3,/julianjohs/tps-aug-22-feature-selection-some-new-features,Tabular Playground Series - Aug 2022
8414,103113023,50.0,,4,14,/leandrodestefani/stratifiedgroupkfold-logisticregression-nn,Tabular Playground Series - Aug 2022
8415,102325654,1347.0,,1,6,/hosseinbehjat/display-some-insights-tps-aug2022,Tabular Playground Series - Aug 2022
8416,103923670,66.0,,0,1,/namelessfairy/linear-model-with-3-features,Tabular Playground Series - Aug 2022
8417,103245669,169.0,0.588390327308256,10,23,/sfktrkl/tps-aug-2022,Tabular Playground Series - Aug 2022
8418,102991819,895.0,0.5881751750529229,3,16,/theathena/tps-aug-22-pca-logistic-regression,Tabular Playground Series - Aug 2022
8419,103548632,123.0,0.5858469711773326,1,7,/jamiedonaldmccann/tabular-aug22-icg-dsc,Tabular Playground Series - Aug 2022
8420,102902744,451.0,0.5881000651359714,3,10,/allenbrownz/tps-aug-22-knorau,Tabular Playground Series - Aug 2022
8421,104125056,1068.0,0.5856606212343266,1,4,/bogdandoicin/imputation-ann,Tabular Playground Series - Aug 2022
8422,104125056,1068.0,0.5856606212343266,1,4,/bogdandoicin/imputation-ann,Tabular Playground Series - Aug 2022
8423,103851158,559.0,0.5822860690441296,4,13,/thierryneusius/tps-202208-knn-imputation-and-logisticregression,Tabular Playground Series - Aug 2022
8424,110784935,64.0,,27,66,/hasanbasriakcay/tpsaug22-insightful-eda-new-lib-featimp,Tabular Playground Series - Aug 2022
8425,102444211,411.0,0.5861771291320632,26,57,/varunnagpalspyz/top-15-just-another-tps-eda-log-reg-baseline,Tabular Playground Series - Aug 2022
8426,102280426,60.0,0.5268388698908972,2,6,/satoshiss/tpsaug-product-failure-prediction,Tabular Playground Series - Aug 2022
8427,103876199,974.0,0.5879002808988764,2,3,/rsesha/lazy-sulo-aug-tps-score-0-5878-in-5-lines,Tabular Playground Series - Aug 2022
8428,102511154,707.0,0.5878326005536557,11,28,/pinstripezebra/eda-baseline-model,Tabular Playground Series - Aug 2022
8429,103523721,136.0,0.5860824784237095,1,15,/tilii7/does-lasso-regression-work-here-you-betcha,Tabular Playground Series - Aug 2022
8430,109232256,571.0,0.5865974596971177,1,4,/angellizaldi/playground-ago,Tabular Playground Series - Aug 2022
8431,102364293,709.0,,0,4,/stpeteishii/tps0822-histplot,Tabular Playground Series - Aug 2022
8432,103446134,321.0,,0,0,/jj150618/tps-aug-22-eda-and-modeling-with-lda,Tabular Playground Series - Aug 2022
8433,104651341,43.0,0.5819113336590132,3,10,/qqzzxxdd/private-score-0-59168-simple-fe-autogluon,Tabular Playground Series - Aug 2022
8434,104457313,225.0,0.58141263637844,2,9,/michaelgwinn/tps-aug22,Tabular Playground Series - Aug 2022
8435,102503092,840.0,,11,76,/vencerlanz09/0-58624-poisson-regressor-eda-explanation,Tabular Playground Series - Aug 2022
8436,103097690,419.0,0.5826944919394236,0,6,/saotome/use-pycaret-belend,Tabular Playground Series - Aug 2022
8437,102486655,27.0,,8,5,/arturra/1-exploratory-data-analysis,Tabular Playground Series - Aug 2022
8438,103589743,26.0,,1,1,/jorgeascencion/tps-2022-aug-neural-net-w-imputer,Tabular Playground Series - Aug 2022
8439,104590160,702.0,,4,13,/aryanml007/tps-august-2022-logistic-regression-feat-engg,Tabular Playground Series - Aug 2022
8440,103109376,344.0,,0,0,/yinging8561/pj-eun,Tabular Playground Series - Aug 2022
8441,104388651,1180.0,0.5131729360039081,14,32,/imnaho/predict-with-neural-network,Tabular Playground Series - Aug 2022
8442,102243046,437.0,,0,7,/gauravduttakiit/failure-prediction-autoviz,Tabular Playground Series - Aug 2022
8443,102739708,872.0,0.4360449234652336,3,10,/muki2003/eda-randomforest-tps-august-product-failure,Tabular Playground Series - Aug 2022
8444,103243060,582.0,0.5860277234978016,0,5,/hugolearn/tps-aug-practice,Tabular Playground Series - Aug 2022
8445,102383541,1129.0,0.5,2,9,/marcorusse/tps-aug-22-lasso-regression,Tabular Playground Series - Aug 2022
8446,103847157,224.0,0.5807205666829507,4,12,/ohba0321/eda-lightgbm-cross-validation,Tabular Playground Series - Aug 2022
8447,103323157,892.0,,0,9,/pasuvulasaikiran/tps-aug-2022-failure-prediction,Tabular Playground Series - Aug 2022
8448,104573733,1038.0,0.5807815298811269,3,21,/sergeyyakovlev1312/predicting-with-nn,Tabular Playground Series - Aug 2022
8449,102864732,1024.0,0.5,0,7,/ibraheemseyam/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8450,103876399,184.0,0.5859188242957173,0,6,/omarvivas/xgb-tps-aug22-v1,Tabular Playground Series - Aug 2022
8451,102651229,334.0,0.5858009688975737,0,5,/jinbao/tps-jinbao-lr,Tabular Playground Series - Aug 2022
8452,102422562,705.0,0.5849904331542094,2,12,/zhangcheche/tps-8-eda-logisticregression-baseline,Tabular Playground Series - Aug 2022
8453,102797382,845.0,,2,8,/majkaf/tbs-aug-2022-binary-classification,Tabular Playground Series - Aug 2022
8454,102300219,532.0,,0,11,/nnjjpp/eda-and-baseline-model-tps-aug-2022,Tabular Playground Series - Aug 2022
8455,104263825,644.0,,2,10,/viktorfairuschin/tps-aug-22-av-public-vs-private,Tabular Playground Series - Aug 2022
8456,102364498,358.0,,1,13,/gupadi/tpsaug-eda-unique-productcodes-attributes-comb,Tabular Playground Series - Aug 2022
8457,103141073,12.0,,3,6,/deepak2r/simple-easy-to-understand-baseline,Tabular Playground Series - Aug 2022
8458,104346661,82.0,0.5860071649568475,1,3,/bernhardklinger/tps-august-2022-h2o-automl,Tabular Playground Series - Aug 2022
8459,102971053,545.0,0.5860918417195896,0,8,/razvanciubotaru/tps-2022-eda-logistic-regression,Tabular Playground Series - Aug 2022
8460,103252029,25.0,0.5861001872659176,2,5,/jinsatp/eda-and-logistic-regression-for-beginners,Tabular Playground Series - Aug 2022
8461,104304388,5.0,0.584003216088585,6,42,/scgupta/tps-2022-aug-eda-baseline-logistic-regression,Tabular Playground Series - Aug 2022
8462,103345903,1009.0,0.5750170981924768,1,8,/cinciadedadoscomr/oversampling-smote-mlp,Tabular Playground Series - Aug 2022
8463,104076299,430.0,0.5860244666992347,2,13,/abdulaziz04/basic-flow-with-logistic-regression,Tabular Playground Series - Aug 2022
8464,102250896,196.0,,0,5,/jaskiratbenipal/eda-trying-different-models-overfitted-tree,Tabular Playground Series - Aug 2022
8465,102884490,281.0,,3,28,/oscarm524/tabular-aug-2022-eda-fe-logistic,Tabular Playground Series - Aug 2022
8466,102522889,304.0,,14,39,/dhirajkumar612/iterative-imputer-logistic-regression-0-58,Tabular Playground Series - Aug 2022
8467,103541473,15.0,0.5857340009770395,7,18,/mohamedmagdy11/tps-aug22-eda-logisticregression-with-optuna,Tabular Playground Series - Aug 2022
8468,102493767,897.0,,3,6,/harisonmwangi/tps-august-2022-adversarial-validation,Tabular Playground Series - Aug 2022
8469,103415613,174.0,0.5840992916463117,2,2,/danielkhromov/tps-aug22-eda-modeling,Tabular Playground Series - Aug 2022
8470,102252926,134.0,,2,6,/guptadikshant/tps-aug-22-eda,Tabular Playground Series - Aug 2022
8471,104398205,267.0,,9,17,/alexandershumilin/tps-aug-2022-with-xgboost-and-gridsearchcv,Tabular Playground Series - Aug 2022
8472,102520988,461.0,,7,12,/rajeevnair676/simple-eda-and-xgb-missing-value-impute,Tabular Playground Series - Aug 2022
8473,102434734,115.0,0.5836653232372577,2,5,/krbharat/lda-regression-baseline-no-eda-fe-fs,Tabular Playground Series - Aug 2022
8474,103315650,496.0,,2,13,/juanantoniosuwardi1/basic-machine-learning-tps-aug22,Tabular Playground Series - Aug 2022
8475,104217413,732.0,0.5829915730337079,15,41,/akioonodera/tps-aug22-lgbm-bin-opt,Tabular Playground Series - Aug 2022
8476,104573978,293.0,0.5850185230418499,1,9,/cshweng/tps-2022,Tabular Playground Series - Aug 2022
8477,102959624,943.0,0.5760389187428757,1,4,/abdu0ch/tabular-aug,Tabular Playground Series - Aug 2022
8478,102379581,967.0,,24,83,/cabaxiom/tps-aug-22-eda-logistic-regression-baseline,Tabular Playground Series - Aug 2022
8479,103531370,178.0,,4,11,/ahmedaljuaid/eda-prediction,Tabular Playground Series - Aug 2022
8480,104573907,830.0,0.5854653150952613,9,19,/ranjeetshrivastav/tps-aug-plotly-pycaret-lda,Tabular Playground Series - Aug 2022
8481,103206434,706.0,0.5787198746132551,2,8,/jtbontinck/tpot-experiment-another-out-of-office-notebook,Tabular Playground Series - Aug 2022
8482,104117436,1162.0,0.5852652255333007,0,2,/yefimsokolov/logistic-regression-data-analysis-tps-aug-22,Tabular Playground Series - Aug 2022
8483,104479452,404.0,,1,5,/diracturing/tps-aug-22-eda-model-testing-basics,Tabular Playground Series - Aug 2022
8484,102611911,875.0,0.5852086386581989,1,6,/priyanagda/eda-linear-regression-aug-tps,Tabular Playground Series - Aug 2022
8485,104392913,145.0,0.582623147695815,0,0,/barbagrande007/bbg007-aug22,Tabular Playground Series - Aug 2022
8486,104019661,941.0,0.5834935271128481,2,7,/vasiliygolikov/comparison-of-imputation-techniques,Tabular Playground Series - Aug 2022
8487,105980478,980.0,,2,2,/ahmetekiz/tps-aug-2022-starter,Tabular Playground Series - Aug 2022
8488,104228988,739.0,,0,2,/seungjoo01/notebookbac32cc065,Tabular Playground Series - Aug 2022
8489,104498677,743.0,,10,48,/anubhavgoyal10/tps-august-ann-score-0-584,Tabular Playground Series - Aug 2022
8490,104250442,987.0,,1,3,/kobzetsu/pytorch-for-start,Tabular Playground Series - Aug 2022
8491,104204547,137.0,0.5825189301416708,1,8,/filippobuonco95/logistic-regression,Tabular Playground Series - Aug 2022
8492,104603241,996.0,0.5830746213971666,0,10,/toshimelonhead/tps-august-2022,Tabular Playground Series - Aug 2022
8493,102474913,646.0,0.5844318921999674,0,1,/konomuabe/tps-aug-2002,Tabular Playground Series - Aug 2022
8494,103478314,408.0,0.5805141670737665,0,5,/mregrt/automl-predict,Tabular Playground Series - Aug 2022
8495,102646723,913.0,,0,6,/saumitgp/0-58288-linear-reg,Tabular Playground Series - Aug 2022
8496,158690755,950.0,,0,3,/ashishsiwach/product-testing,Tabular Playground Series - Aug 2022
8497,103778129,957.0,0.5841131330402215,1,31,/piyushjain16/august-challenge2,Tabular Playground Series - Aug 2022
8498,103778129,957.0,0.5841131330402215,1,31,/piyushjain16/august-challenge2,Tabular Playground Series - Aug 2022
8499,104636098,381.0,,1,8,/daesunryu/ml-tps-august-score-0-58943,Tabular Playground Series - Aug 2022
8500,104443221,869.0,0.5792198949682462,1,2,/chrismysen/tabular-playground-august-2022-xgboost,Tabular Playground Series - Aug 2022
8501,103573664,1087.0,,0,1,/datascientistsohail/tpgs-aug2022,Tabular Playground Series - Aug 2022
8502,103247604,653.0,,3,8,/wasshoiwasshoi/2022-tps-aug-quick-eda,Tabular Playground Series - Aug 2022
8503,102824991,870.0,,6,28,/docxian/tps-2022-aug-glm-starter-r,Tabular Playground Series - Aug 2022
8504,103452270,393.0,,0,5,/harryho096/eda-fe-gridsearch,Tabular Playground Series - Aug 2022
8505,102252282,764.0,0.5836392688487217,0,10,/scholzy/tps-august-eda-simple-logisticregression,Tabular Playground Series - Aug 2022
8506,103088459,1471.0,,1,10,/mustafakeser4/tps-august-eda,Tabular Playground Series - Aug 2022
8507,111859448,288.0,,18,59,/kevinmorgado/top-20-product-failure-prediction,Tabular Playground Series - Aug 2022
8508,103687273,932.0,,8,10,/qayyum453/tabular-playground-series-prediction,Tabular Playground Series - Aug 2022
8509,102416658,901.0,,0,3,/itspavansatish/bayesiangaussianmixture-classifer,Tabular Playground Series - Aug 2022
8510,102833461,945.0,,2,11,/misaelcribeiro/tps-rfe-logging-many-models-performance,Tabular Playground Series - Aug 2022
8511,102833936,894.0,0.5831873880475492,1,11,/meln1337/tabular-playground-aug-2022,Tabular Playground Series - Aug 2022
8512,103791117,862.0,0.5585658891060088,0,0,/igor185/tensorflow-baseline,Tabular Playground Series - Aug 2022
8513,103791117,862.0,0.5585658891060088,0,0,/igor185/tensorflow-baseline,Tabular Playground Series - Aug 2022
8514,102243703,944.0,,1,5,/sindhuinti/tabular-comp,Tabular Playground Series - Aug 2022
8515,103151988,835.0,0.5721238397655105,1,20,/fourteenflames/tabplayground-aug22,Tabular Playground Series - Aug 2022
8516,103151988,835.0,0.5831939016446833,1,20,/fourteenflames/tabplayground-aug22,Tabular Playground Series - Aug 2022
8517,104557097,555.0,,1,0,/hunterdlugas/tps-august-2022-processing,Tabular Playground Series - Aug 2022
8518,102779822,717.0,0.5830812367692558,0,0,/rizkykiky/need-eda-to-understand,Tabular Playground Series - Aug 2022
8519,102779822,717.0,0.5816851897085166,0,0,/rizkykiky/need-eda-to-understand,Tabular Playground Series - Aug 2022
8520,102524428,415.0,0.5769530613906529,1,6,/demko1/tps-aug-2022-comp,Tabular Playground Series - Aug 2022
8521,104471466,1217.0,0.5829311187103078,1,4,/hasanmumtaz16/tps-aug2022-just-a-normal-ml-workflow,Tabular Playground Series - Aug 2022
8522,102742988,1131.0,0.5828477650219834,2,4,/mdashifmallick/tabular-pg-series-lr-model,Tabular Playground Series - Aug 2022
8523,131279516,533.0,,0,0,/shanu1988/notebook4fd3c8eed2,Tabular Playground Series - Aug 2022
8524,115496952,548.0,,1,1,/abdoulayebalde/tps-eda-and-catboost-0-58246-aug-2022d,Tabular Playground Series - Aug 2022
8525,103218329,722.0,,2,7,/sdysch/tps-aug-2022,Tabular Playground Series - Aug 2022
8526,104027409,736.0,,0,3,/valentindefour/tps-august-2022-h2o-vs-manual-ml,Tabular Playground Series - Aug 2022
8527,103557088,1010.0,0.5818455870379418,1,8,/lavonteadams/tps-aug-22-kerasregressor,Tabular Playground Series - Aug 2022
8528,103564779,874.0,0.5788049584758183,1,0,/kottoz/lightgbm-test,Tabular Playground Series - Aug 2022
8529,102832994,1031.0,,1,5,/pmassouf/stacking-starter-score-0-58,Tabular Playground Series - Aug 2022
8530,104640900,953.0,0.581632470281713,10,23,/reymaster/ensemble-voter-iterative-imputation-0-582,Tabular Playground Series - Aug 2022
8531,105970487,436.0,,0,1,/tomjosephmo/logistic-regression-with-missing-values-accounted,Tabular Playground Series - Aug 2022
8532,102252429,879.0,0.5815332397003745,0,9,/foolishboi/baseline-xgboost-submission,Tabular Playground Series - Aug 2022
8533,102831797,640.0,,5,10,/tolgayan/tps-aug22-nice-to-meet-you,Tabular Playground Series - Aug 2022
8534,104168504,303.0,,1,3,/raj401/eda-preprocessed-data-tps-aug,Tabular Playground Series - Aug 2022
8535,103979145,1096.0,0.5797926844162189,0,7,/jagdmir/lgbm-0-579,Tabular Playground Series - Aug 2022
8536,103979145,1096.0,0.5780523326819736,0,7,/jagdmir/lgbm-0-579,Tabular Playground Series - Aug 2022
8537,104412289,58.0,,0,1,/liveforever/tps-nn,Tabular Playground Series - Aug 2022
8538,102358777,864.0,0.5810081827063996,4,22,/delilahrooney/tps-aug-22-lightgbm-xgb-logisticregression,Tabular Playground Series - Aug 2022
8539,104522856,369.0,,2,13,/lucasmorin/tpsaug22-base-lgbm-ensemble,Tabular Playground Series - Aug 2022
8540,102941596,1112.0,0.5215728301579547,0,9,/miyahayers/tps-aug-22-autokeras-for-each-product-code,Tabular Playground Series - Aug 2022
8541,104583967,1041.0,0.5803922406774141,12,21,/mikita1580/tabular-playground-nn,Tabular Playground Series - Aug 2022
8542,103379652,574.0,0.5,0,9,/youseefmoemen/tps-aug-ellipticenvlope-dimreduction,Tabular Playground Series - Aug 2022
8543,104652353,960.0,,1,2,/andrew44456/tabularpg-aug-challenge-rfr-randomsearchcv,Tabular Playground Series - Aug 2022
8544,102221303,1228.0,,0,31,/mpwolke/tab-aug-2022-my-failure,Tabular Playground Series - Aug 2022
8545,102959312,968.0,,0,6,/pdenieves/tps-aug22-eda-with-dython,Tabular Playground Series - Aug 2022
8546,104567014,1116.0,,0,5,/mateussehn/tabular-playground-series-aug-2022-score-0-58,Tabular Playground Series - Aug 2022
8547,102280770,1193.0,0.5797915648917115,1,17,/jackyron/tps-aug-22-lightgbm-optuna,Tabular Playground Series - Aug 2022
8548,104250793,660.0,0.5719446140693698,1,12,/antonsruberts/tabtransformer-w-pre-training,Tabular Playground Series - Aug 2022
8549,103612026,1069.0,,1,1,/gyeong6/tps-8-project,Tabular Playground Series - Aug 2022
8550,104144867,1194.0,0.579498554795636,0,0,/ihoushin/tps-aug2022-pytorch-simplenn,Tabular Playground Series - Aug 2022
8551,102287196,676.0,0.5794799299788308,1,7,/juanhubert/tps-aug-22-xgboost-optuna,Tabular Playground Series - Aug 2022
8552,102889778,491.0,0.5295719345383488,12,32,/sanjaylalwani/august-22-tps-eda-lgbm,Tabular Playground Series - Aug 2022
8553,102670719,1090.0,0.5506375183194919,3,5,/casati8/kaggle-tps2022-aug-fastai-baseline,Tabular Playground Series - Aug 2022
8554,103687120,713.0,,0,1,/gunholee/simple-preprocessing-xgboost-0-57832,Tabular Playground Series - Aug 2022
8555,102680133,1254.0,0.5780432747109592,1,1,/sviatoslavsakharov/tps-aug22-first-model,Tabular Playground Series - Aug 2022
8556,103297136,931.0,0.5776750529229767,0,1,/wellissongomess/notebook-w,Tabular Playground Series - Aug 2022
8557,102279324,382.0,,1,6,/ceruttivini/tps-aug-22-exploratory-analysis,Tabular Playground Series - Aug 2022
8558,103070296,1132.0,,3,10,/robertturro/tps-august-eda-feature-selection,Tabular Playground Series - Aug 2022
8559,104163661,1114.0,,0,0,/wfan2022/notebook-playground-aug2022-neural-networks,Tabular Playground Series - Aug 2022
8560,130560519,1135.0,,2,6,/ankitaanand28/tps-aug22,Tabular Playground Series - Aug 2022
8561,102350150,1175.0,0.5665789366552678,2,6,/meisa0/tps-aug-22-feature-engineering-impute-lgbm,Tabular Playground Series - Aug 2022
8562,104517123,1182.0,0.4897997068881289,2,14,/ahmedtoba/sklearn-algorithms-and-dnn-keras-pytorch,Tabular Playground Series - Aug 2022
8563,102667878,1155.0,,0,4,/abedwazwaz/tps-august-eda,Tabular Playground Series - Aug 2022
8564,105843875,1120.0,0.4995815013841393,5,16,/francescoliveras/tabular-pg-nn-en-es,Tabular Playground Series - Aug 2022
8565,102962188,1160.0,,3,6,/nknarendra7/deep-learning-approach-on-regressions,Tabular Playground Series - Aug 2022
8566,104376595,1000.0,,0,1,/thomassimm/tabular-playground-aug22,Tabular Playground Series - Aug 2022
8567,110138362,656.0,,6,12,/pravashpurkayastha/tpg-aug-product-review,Tabular Playground Series - Aug 2022
8568,120450290,1049.0,,0,1,/fortuneuwha/super-soaker-predicting-product-failures,Tabular Playground Series - Aug 2022
8569,102696535,1201.0,0.5710374938935027,0,0,/marioyuniortoribio/august-2022-kaggle,Tabular Playground Series - Aug 2022
8570,103545806,1205.0,,1,4,/rutikachavan/tabular-playground-series,Tabular Playground Series - Aug 2022
8571,105081433,1225.0,,0,0,/marcuspop/gdmlbootcamp-ml-practice-kaggle-tabular-august,Tabular Playground Series - Aug 2022
8572,102873000,1199.0,0.5679598192476796,6,6,/akashmathur2212/lgbm-xgb-catboost-ensemble-with-hyperopt-tuning,Tabular Playground Series - Aug 2022
8573,103689528,1188.0,0.5665323237257776,0,3,/mahdeemushfiquekamal/tps-aug-ensembling-basic-models,Tabular Playground Series - Aug 2022
8574,103075143,1261.0,,0,7,/ltrahul/tps-august-2022-solution,Tabular Playground Series - Aug 2022
8575,104056836,1218.0,,0,3,/ddiyoungx4/tps-aug-2022-randomforest,Tabular Playground Series - Aug 2022
8576,104550094,1122.0,,1,7,/paultimothymooney/how-to-make-a-submission-to-august-tps-using-tf-df,Tabular Playground Series - Aug 2022
8577,103527375,1294.0,,2,10,/cameron858/tps-aug22,Tabular Playground Series - Aug 2022
8578,103021350,1789.0,0.5006354828203876,0,5,/srsses/playground-august,Tabular Playground Series - Aug 2022
8579,104047143,1296.0,0.5333886989089724,0,4,/tleonel/ml-approach-with-smote-and-ensemble,Tabular Playground Series - Aug 2022
8580,104377913,1277.0,,10,28,/manthanx/tpsaug22-eda-logregression-tunegridsearchcv,Tabular Playground Series - Aug 2022
8581,103529101,1251.0,,0,9,/nurielreuven/tabular-playground-aug-22-eda-modeling,Tabular Playground Series - Aug 2022
8582,103962217,1265.0,0.5589075476306791,0,0,/fredriktrulsson/tps-aug-22-exploring-the-data,Tabular Playground Series - Aug 2022
8583,103361920,1331.0,0.5260169353525485,0,9,/massimot/tpg-22-08-xgboost-oversampling,Tabular Playground Series - Aug 2022
8584,102255325,1291.0,0.5549759811105683,1,5,/tracyporter/aug-22-tabular,Tabular Playground Series - Aug 2022
8585,104521955,1334.0,0.5543260462465397,0,0,/kelizatoh/aug-2022-tabular-playground-logistic-regression,Tabular Playground Series - Aug 2022
8586,102371244,1253.0,0.4783060576453346,2,19,/rosanigel/tps-aug-22-tensorflow-decision-forest,Tabular Playground Series - Aug 2022
8587,103038523,1370.0,0.5379994097052597,0,6,/pavankumarmantha/tps-aug-2022-100-accuracy,Tabular Playground Series - Aug 2022
8588,102314729,1223.0,,0,7,/makotouchiyama/english-eda-1-missingval-r-tps-202208,Tabular Playground Series - Aug 2022
8589,103432186,1311.0,,0,5,/theyoof/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8590,102454020,1452.0,0.5485303696466374,2,7,/carolinacarerra/tps-aug-22-autokeras,Tabular Playground Series - Aug 2022
8591,103194534,1450.0,0.5051253867448299,1,7,/eaterofspirits/adversarial-validation-train-and-test-data-differ,Tabular Playground Series - Aug 2022
8592,103052965,1866.0,,0,6,/abdulghaffaransari/tps-aug-2022-best-ensemble-learning-technique,Tabular Playground Series - Aug 2022
8593,104759542,1451.0,,1,4,/aklimarimi/cat-lgb,Tabular Playground Series - Aug 2022
8594,102765991,1503.0,0.4892472724312001,4,11,/aidenfoster/tps-aug-22-probabilistic-regression,Tabular Playground Series - Aug 2022
8595,103240389,1382.0,0.5329435352548445,0,0,/dantecosta/aug-22,Tabular Playground Series - Aug 2022
8596,104221826,1433.0,,0,5,/athews/tps-aug-22-tensorflow-and-lightgbm-starter,Tabular Playground Series - Aug 2022
8597,102822562,1531.0,0.5054464867285459,3,10,/tariqbartlett/tps-aug-22-bayesian-neural-network,Tabular Playground Series - Aug 2022
8598,103108320,1537.0,,0,2,/kanantaghiyev/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8599,116557980,1474.0,,0,0,/sagar2168616/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8600,103567019,1465.0,,1,6,/haekang/0809-tabular,Tabular Playground Series - Aug 2022
8601,102674733,1629.0,0.5175382673831623,1,12,/freddymeriwether/tps-aug-22-fe-pycaret,Tabular Playground Series - Aug 2022
8602,102674733,1629.0,0.5155341149649895,1,12,/freddymeriwether/tps-aug-22-fe-pycaret,Tabular Playground Series - Aug 2022
8603,103188500,1585.0,0.498949377137274,7,13,/shristi13sri/tps-aug-22-failure-prediction,Tabular Playground Series - Aug 2022
8604,104069692,1522.0,0.5097170656244912,2,18,/rumbleftw/august-2022-tabular-playground-series,Tabular Playground Series - Aug 2022
8605,104463062,1540.0,0.50929836345872,0,1,/junhooo/junho1,Tabular Playground Series - Aug 2022
8606,104203825,1593.0,,0,0,/hosseinrezazadeh/notebookb3e4fcf537,Tabular Playground Series - Aug 2022
8607,102883217,1840.0,,2,8,/datarohitingole/tps-aug-2022-autogluon-automl,Tabular Playground Series - Aug 2022
8608,102447077,1630.0,,0,3,/adwaitkesharwani/starter-notebook,Tabular Playground Series - Aug 2022
8609,102865525,1849.0,,2,9,/bibekupadhyaya/randomforest-logisticregression-naivebayes-svm,Tabular Playground Series - Aug 2022
8610,103986356,1671.0,0.5018227894479727,0,3,/gurpreetchaggar/basic-eda-and-logistic-regression-model,Tabular Playground Series - Aug 2022
8611,104629886,1834.0,,1,4,/abhigyandatta/super-soaker-eda-tps-aug22,Tabular Playground Series - Aug 2022
8612,107296020,1668.0,,1,1,/ahmedashraf123/tabular-playground-series,Tabular Playground Series - Aug 2022
8613,105011880,1747.0,,0,5,/jeetkumarpal/tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8614,102580905,1730.0,0.5003511235955056,4,4,/gopalgoyal612002/tps-aug-xgboost-classifier-eda,Tabular Playground Series - Aug 2022
8615,103988624,1496.0,0.5,0,6,/manthannagpurkar/tps-aug-lr-dt-rf-svm-knn-naivebayes,Tabular Playground Series - Aug 2022
8616,104633254,1835.0,0.5002007002116919,0,2,/atharv111/randomforestclassifier,Tabular Playground Series - Aug 2022
8617,105204316,1480.0,,0,9,/atrijtalgery/tps08-22-iterative-imputation-smotenc-svc,Tabular Playground Series - Aug 2022
8618,105197751,1803.0,,2,9,/cerocycle/initial-analysis-of-aug-2022-competition,Tabular Playground Series - Aug 2022
8619,103791227,1804.0,,0,4,/anassmellouki1/deep-learning-using-keras,Tabular Playground Series - Aug 2022
8620,104096977,1811.0,,4,9,/ruslannuriyev/eda-and-modeling,Tabular Playground Series - Aug 2022
8621,104593630,1836.0,,0,0,/vibhutikhanduri/notebook3367780aa6,Tabular Playground Series - Aug 2022
8622,102381350,1743.0,,0,8,/devic1/tps-aug-22,Tabular Playground Series - Aug 2022
8623,102650525,1587.0,0.4991892607067253,0,4,/hirotokitamur/hk-tabular-playground-series-aug-2022,Tabular Playground Series - Aug 2022
8624,108157470,3.0,,3,24,/bamps53/efficient-video-loading-with-threading,DFL - Bundesliga Data Shootout
8625,107807841,8.0,,2,11,/zzy990106/fork-of-fork-of-dfl-notebook-4fold,DFL - Bundesliga Data Shootout
8626,102769646,9.0,,15,77,/shinmurashinmura/dfl-yolov5-ball-detection,DFL - Bundesliga Data Shootout
8627,102872043,12.0,,0,35,/kurupical/detect-all-action-every-1-or-0-5-seconds,DFL - Bundesliga Data Shootout
8628,106244322,19.0,,13,75,/laeyoung/dfl-notebook-sponsored-by-aindao,DFL - Bundesliga Data Shootout
8629,118484112,28.0,,0,3,,DFL - Bundesliga Data Shootout
8630,102548045,47.0,,6,26,/amiiiney/dfl-mapping-the-scoring-intervals-to-the-frames,DFL - Bundesliga Data Shootout
8631,105345046,62.0,,2,5,/stgkrtua/dfl-yolov5-balldetect-without-internet-torch1-9,DFL - Bundesliga Data Shootout
8632,103266412,63.0,,2,18,/cbeaud/detect-all-action-every-0-58-or-1-seconds,DFL - Bundesliga Data Shootout
8633,105134888,70.0,,0,12,/takaito/homography-transformation,DFL - Bundesliga Data Shootout
8634,103775589,119.0,,4,10,/kostiantynlavronenko/dfl-bundesliga-data-overview,DFL - Bundesliga Data Shootout
8635,103236137,168.0,,0,6,/skalskip/dfl-bundesliga-detection-and-tracking,DFL - Bundesliga Data Shootout
8636,106399487,226.0,,2,29,/dinowun/eda-simplified-dfl-bundesliga-shootout,DFL - Bundesliga Data Shootout
8637,102512334,293.0,,6,18,/roniheka/preprocess-difference-extraction-between-frames,DFL - Bundesliga Data Shootout
8638,103765607,315.0,,0,3,/ryumdra/first-impression-dfl,DFL - Bundesliga Data Shootout
8639,132835372,317.0,,0,1,/ethanhu8093/bundesliga-pretrained-yolov8-ball-detection,DFL - Bundesliga Data Shootout
8640,103139233,347.0,,4,64,/its7171/yolov7-finetune-with-soccernet,DFL - Bundesliga Data Shootout
8641,102620027,366.0,,9,26,/ghrangel/semantic-segmentation-bundesliga,DFL - Bundesliga Data Shootout
8642,106881945,395.0,0.0636220517186022,0,3,/saraswatitiwari/deutsche-fu-ball-liga,DFL - Bundesliga Data Shootout
8643,113319726,409.0,,0,3,/madeiramml10/noise-stripping-for-soccer-event-detection,DFL - Bundesliga Data Shootout
8644,102576453,417.0,0.0330676608234962,3,19,/sugahara/dfl-poor-baseline-en-jp,DFL - Bundesliga Data Shootout
8645,106179958,428.0,,1,7,/tutusini/augmentally-generate-training-data-from-dfl-videos,DFL - Bundesliga Data Shootout
8646,103790882,461.0,,0,15,/samir95/pytorch-video-dataloader,DFL - Bundesliga Data Shootout
8647,102153253,465.0,,2,21,/yokuyama/fast-video-resizing-with-ffmpeg-384x216,DFL - Bundesliga Data Shootout
8648,104651520,472.0,,0,4,/prajwalsood/tf-keras-dfl-vivit-with-weighted-softmax,DFL - Bundesliga Data Shootout
8649,102082971,477.0,0.0,2,17,/tscheung/fastest-submission-in-the-east,DFL - Bundesliga Data Shootout
8650,103164546,492.0,,0,5,/ahmedtarek26/eda-dfl-bundesliga-data-shootout,DFL - Bundesliga Data Shootout
8651,108960188,494.0,,0,2,/rodrigostallsikora/yolo-v5-video-inference-ball-detection,DFL - Bundesliga Data Shootout
8652,105650987,13.0,,12,33,/gladwell/one-crop2-solution,AI Village Capture the Flag @ DEFCON
8653,105433399,20.0,,2,3,/vkonstantakos/hotdog-challenges-overlay-vs-gradient,AI Village Capture the Flag @ DEFCON
8654,105444224,21.0,,0,7,/amarneh/answer-to-some-of-the-questions-lb-0-894,AI Village Capture the Flag @ DEFCON
8655,106081707,44.0,,0,1,/tatamikenn/defcon30-salt,AI Village Capture the Flag @ DEFCON
8656,105473735,58.0,,2,16,/vwoodnz/deepfake-do-a-flip,AI Village Capture the Flag @ DEFCON
8657,105458452,60.0,,0,7,,AI Village Capture the Flag @ DEFCON
8658,105453745,78.0,,0,7,/yosshi999/defcon30-bruteforce-baseball-using-optuna,AI Village Capture the Flag @ DEFCON
8659,107517233,84.0,,0,1,/danila/solutions-ai-village-ctf-defcon,AI Village Capture the Flag @ DEFCON
8660,105311579,99.0,,0,5,/jbomitchell/bazball,AI Village Capture the Flag @ DEFCON
8661,105625580,150.0,,1,2,/vangap/murderbots-solution-with-simple-logisticregression,AI Village Capture the Flag @ DEFCON
8662,105459494,170.0,,0,2,/joatom/defcon30-ctf-some-solutions-0-342,AI Village Capture the Flag @ DEFCON
8663,104918400,603.0,,0,8,/mpwolke/dontshareflags-csi-wolke,AI Village Capture the Flag @ DEFCON
8664,111149305,2.0,0.8158132906439481,10,56,/senkin13/2nd-place-gru-cite,Open Problems - Multimodal Single-Cell Integration
8665,105814014,133.0,,0,1,/kaggledummie007/cite-keras-optuna,Open Problems - Multimodal Single-Cell Integration
8666,122103214,29.0,0.8149185554651902,5,12,/songqizhou/private-29th-public-4th-s-basical-single-model-nn,Open Problems - Multimodal Single-Cell Integration
8667,109565504,19.0,,14,284,/ambrosm/msci-eda-which-makes-sense,Open Problems - Multimodal Single-Cell Integration
8668,111231421,3.0,,1,23,/mhyodo/w2v-feature-sample,Open Problems - Multimodal Single-Cell Integration
8669,113303210,9.0,0.8129106632883575,0,0,/dvmodeler/silver-place-post-processing-transform,Open Problems - Multimodal Single-Cell Integration
8670,111298643,5.0,,0,1,/qqzzxxdd/cite-5th-solution-lgbm-training,Open Problems - Multimodal Single-Cell Integration
8671,110132905,693.0,,0,2,/lcbupt/notebook152a49ec8c,Open Problems - Multimodal Single-Cell Integration
8672,105042624,21.0,,6,25,/takanashihumbert/there-are-35-features-in-multiome-data-constant-0,Open Problems - Multimodal Single-Cell Integration
8673,104482688,47.0,,1,8,/masato114/chromatin-gene-conversion-train,Open Problems - Multimodal Single-Cell Integration
8674,106583794,108.0,,8,68,/sakurakotanida/eda-in-japanese,Open Problems - Multimodal Single-Cell Integration
8675,107351621,92.0,,0,0,/bejeweled/multiome-rf-feature-selection,Open Problems - Multimodal Single-Cell Integration
8676,105158194,448.0,,8,35,/mehrankazeminia/1-5-msci22-eda,Open Problems - Multimodal Single-Cell Integration
8677,104462772,165.0,0.7750247310989302,5,12,/nandodmelo/cite-xgboost-v1,Open Problems - Multimodal Single-Cell Integration
8678,109559197,127.0,,0,2,/tttzof351/mmscel-crossvalidation-schemes-193f49,Open Problems - Multimodal Single-Cell Integration
8679,103595883,139.0,,2,14,/sskknt/en-jp-quick-data-preview-and-column-name-patterns,Open Problems - Multimodal Single-Cell Integration
8680,104493794,497.0,0.7933057038089045,1,10,/jsmithperera/msci-citeseq-quickstart-v3,Open Problems - Multimodal Single-Cell Integration
8681,107688481,709.0,,0,10,/kirkdco/msci-multiome-sparse-datasets,Open Problems - Multimodal Single-Cell Integration
8682,117724154,459.0,,14,68,/usamabalochhh/single-cell-integration-explore-data,Open Problems - Multimodal Single-Cell Integration
8683,105868827,529.0,,1,23,/tamaryo/lb-0-807-citeseq-tabnet-baseline,Open Problems - Multimodal Single-Cell Integration
8684,104285352,461.0,,2,40,/xiafire/lb0-830-lgbm-optuna-msci-citeseq,Open Problems - Multimodal Single-Cell Integration
8685,108291339,483.0,,0,7,/insiyajafferji/cite-seq-data-analysis-exploration,Open Problems - Multimodal Single-Cell Integration
8686,106427199,287.0,,0,3,/viictte/data-process,Open Problems - Multimodal Single-Cell Integration
8687,106678325,234.0,0.7963254448779091,0,20,/geraseva/magic-feature-selection,Open Problems - Multimodal Single-Cell Integration
8688,105172766,332.0,0.7979730540960193,4,26,/ravishah1/citeseq-rna-to-protein-encoder-decoder-nn,Open Problems - Multimodal Single-Cell Integration
8689,108181885,452.0,,0,4,/olegzakh/transform-input-by-grouping-features-multiome,Open Problems - Multimodal Single-Cell Integration
8690,109922570,537.0,,0,0,/yanasem/mmscel-crossvalidation-schemes-sim-featur-26bc84,Open Problems - Multimodal Single-Cell Integration
8691,106474650,591.0,,0,9,/konomuabe/convert-data-for-speed-up,Open Problems - Multimodal Single-Cell Integration
8692,104578004,141.0,0.7928518637114129,13,69,/vuonglam/tune-lgbm-only-final-cite-task,Open Problems - Multimodal Single-Cell Integration
8693,105260280,604.0,,10,129,/vslaykovsky/lb-0-811-normalized-ensembles-for-pearson-s-r,Open Problems - Multimodal Single-Cell Integration
8694,104584358,618.0,,4,75,/fabiencrom/multimodal-single-cell-creating-sparse-data,Open Problems - Multimodal Single-Cell Integration
8695,120090802,88.0,,0,2,/artemfedorov/eda-notebook,Open Problems - Multimodal Single-Cell Integration
8696,108148265,700.0,,0,1,/bobfromjapan/msci-merging-submission,Open Problems - Multimodal Single-Cell Integration
8697,108369989,721.0,,0,3,/grac2h5/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8698,104790483,633.0,,14,93,/swimmy/lgbm-baseline-msci-citeseq,Open Problems - Multimodal Single-Cell Integration
8699,104430282,718.0,,2,10,/narendra/msci-high-level-eda,Open Problems - Multimodal Single-Cell Integration
8700,108617498,807.0,0.8069292820846937,0,38,/user327934/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8701,104163713,763.0,,23,78,/sbunzini/reduce-memory-usage-by-95-with-sparse-matrices,Open Problems - Multimodal Single-Cell Integration
8702,108968301,808.0,,0,2,/nastyakiryak/mmscel-dca-features-load-example-cell-cycle-v,Open Problems - Multimodal Single-Cell Integration
8703,109464081,809.0,0.8069292820846937,0,11,/evgenibikov/mmscel-crossvalidation-schemes-eb,Open Problems - Multimodal Single-Cell Integration
8704,108577402,903.0,0.805436050432247,0,5,/anigrigor/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8705,108920515,904.0,,0,4,/kirillpetrikov/mmscel-dca-features-load-example-cell-cycle,Open Problems - Multimodal Single-Cell Integration
8706,109216680,905.0,0.805436050432247,0,2,/arteziak/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8707,110045727,906.0,0.805436050432247,0,5,/arinatsvetkova/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8708,109481772,901.0,,0,1,/marijabruttan/mmscel-crossval-ridge,Open Problems - Multimodal Single-Cell Integration
8709,109893156,925.0,,0,1,/sonyagrey/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8710,109207109,926.0,0.8052007215415757,0,1,/ergardtalice/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8711,109226013,927.0,0.8052007215415757,0,5,/jessicajones13/mmscel-som-try,Open Problems - Multimodal Single-Cell Integration
8712,110057448,928.0,,0,3,/hydrophonyx/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8713,109224230,933.0,0.8052002577662986,0,2,/leonidafanasev/mmscel-linermodel,Open Problems - Multimodal Single-Cell Integration
8714,109292424,930.0,0.805200104317034,1,7,/lizabogdan/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8715,109331074,931.0,0.805200104317034,0,1,/astrik/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8716,110379175,932.0,0.805200104317034,0,0,/sankkan/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8717,104542229,939.0,,1,19,/stautxie/reduce-memory-footprint-of-competition-data,Open Problems - Multimodal Single-Cell Integration
8718,107295164,961.0,0.8035694669936753,16,64,/lucasmorin/msci-citeseq-tf-keras-nn-custom-loss,Open Problems - Multimodal Single-Cell Integration
8719,113125041,719.0,,0,6,/kseniyapetrova/cite-hvg,Open Problems - Multimodal Single-Cell Integration
8720,108598108,946.0,0.8021190735865459,1,14,/annanparfenenkova/ridge-with-reactome-features,Open Problems - Multimodal Single-Cell Integration
8721,108373702,1020.0,0.7912173987831849,0,3,/claptar/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8722,105542904,1096.0,,4,22,/norifumiirie/heatmap-of-multiome-data,Open Problems - Multimodal Single-Cell Integration
8723,104910580,1097.0,,8,40,/erivanoliveirajr/multimodal-single-cell-integration,Open Problems - Multimodal Single-Cell Integration
8724,108382912,1111.0,0.72984005759203,1,6,/dmisky/mmscel-crossvalidation-schemes-v0-1,Open Problems - Multimodal Single-Cell Integration
8725,108891561,1112.0,0.72984005759203,0,2,/alexanderkalmykov/mmscel-crossvalidation-schemes,Open Problems - Multimodal Single-Cell Integration
8726,103801478,1122.0,,4,47,/jirkaborovec/mmscel-inst-eda-stat-predictions,Open Problems - Multimodal Single-Cell Integration
8727,103439720,1119.0,0.7188938610581099,1,57,/shuntarotanaka/simple-submission-average-by-gene-id,Open Problems - Multimodal Single-Cell Integration
8728,112303377,1151.0,,0,3,/pzarzycki/opm-multi-cite-simple-mlp-models,Open Problems - Multimodal Single-Cell Integration
8729,107599000,1177.0,,1,3,/juliarymuza/notebook6d95a9efe1,Open Problems - Multimodal Single-Cell Integration
8730,109885280,1201.0,,3,9,/pollicio/analisis-unicelular-chile,Open Problems - Multimodal Single-Cell Integration
8731,105584879,313.0,,0,1,/liampresland/holiday-mini-eda,Tabular Playground Series - Sep 2022
8732,104714885,16.0,,1,10,/paulrudolph/tabular-sep-2022-eda-insights-baseline-model,Tabular Playground Series - Sep 2022
8733,125071691,157.0,,31,74,/usamabalochhh/time-series-using-xgboost,Tabular Playground Series - Sep 2022
8734,104710988,197.0,,5,16,/griffenthoma/tps-sep-22-eda-discovering-year-2020-data-oddity,Tabular Playground Series - Sep 2022
8735,104953792,2.0,7.820791163190374,8,18,/akmalmir/tps-09-2022-no-machine-learning-solution,Tabular Playground Series - Sep 2022
8736,104874623,224.0,5.141941932376014,2,23,/cbhavik/score-5-14-tps-eda-lgbm-baseline,Tabular Playground Series - Sep 2022
8737,105566805,3.0,,9,27,/paddykb/tps-2022-09-compare-to-best-public-notebook,Tabular Playground Series - Sep 2022
8738,107546138,34.0,,40,95,/ravi20076/tpssep22-eda-visualization,Tabular Playground Series - Sep 2022
8739,106663207,4.0,,28,71,/shariful07/tps-sep-2022-lgbmregressor-and-eda,Tabular Playground Series - Sep 2022
8740,105919367,210.0,,2,7,/naiborhujosua/tps-10-tabnet-xgboost,Tabular Playground Series - Sep 2022
8741,107147359,287.0,,57,75,/lazer999/time-series-tps-eda-xgb-simplified,Tabular Playground Series - Sep 2022
8742,105129190,156.0,23.05471931432815,2,12,/tinfufans/sept2022,Tabular Playground Series - Sep 2022
8743,105490465,22.0,4.496314582882845,2,13,/saumilagrawal10/high-tps08,Tabular Playground Series - Sep 2022
8744,105721282,117.0,12.310691761921094,1,9,/sagnik1511/tps-believing-in-prophet,Tabular Playground Series - Sep 2022
8745,106813325,6.0,,1,7,/ritrex/tabular-playground-series-sept-2022,Tabular Playground Series - Sep 2022
8746,104705508,194.0,6.607628413889131,2,13,/archietram/copied-from-nischay-dhankhar-with-a-tiny-change,Tabular Playground Series - Sep 2022
8747,105000991,575.0,28.73993716704507,25,97,/jcaliz/tps-sep22-eda-baseline-you-were-looking-for,Tabular Playground Series - Sep 2022
8748,106870626,26.0,4.458360544572637,38,62,/vishnu123/tps-sep-22-eda-lasso-groupkfold-mean-ratios,Tabular Playground Series - Sep 2022
8749,105304812,49.0,,3,10,/zzettrkalpakbal/covid-data-leakage,Tabular Playground Series - Sep 2022
8750,104880346,45.0,,0,6,/hkhiroshima/tps2022-sep-eda-lgbm-baseline,Tabular Playground Series - Sep 2022
8751,115278065,46.0,,7,34,/nanduvardhanreddy/tbs-eda,Tabular Playground Series - Sep 2022
8752,104693563,58.0,6.839667937450349,0,7,/act18l/tps2209-lightgbm-optuna,Tabular Playground Series - Sep 2022
8753,105380400,220.0,9.8528151065496,0,1,/significantbutter/tps-sept-using-radial-basis-function-rbf,Tabular Playground Series - Sep 2022
8754,104674144,64.0,6.955330307047647,2,11,/ducanger/tps-sep-lgbm-simple-baseline,Tabular Playground Series - Sep 2022
8755,140998111,62.0,,22,91,/kevinmorgado/feature-engineering-book-sales,Tabular Playground Series - Sep 2022
8756,104693510,80.0,,4,18,/oscarm524/tabular-sep-2022-eda,Tabular Playground Series - Sep 2022
8757,105703385,212.0,,0,5,/davidzambrano87/eda-september-tabular-playground,Tabular Playground Series - Sep 2022
8758,106300867,85.0,,2,11,/nicholasting/simple-prophet-nicholas-ting,Tabular Playground Series - Sep 2022
8759,105074018,135.0,,41,176,/cabaxiom/tps-sep-22-eda-and-linear-regression-baseline,Tabular Playground Series - Sep 2022
8760,105671738,105.0,,21,20,/kalininvladislav/eda-and-ml-tps-sep-2022,Tabular Playground Series - Sep 2022
8761,105474780,109.0,35.63166272549974,3,9,/mikhaildonskoy/comparing-main-ml-models-in-10-minutes,Tabular Playground Series - Sep 2022
8762,105320607,126.0,,1,7,/sandeepmajumdar/tps-sep-2022-visualize-gdp-per-capita,Tabular Playground Series - Sep 2022
8763,105476954,100.0,4.647385089810149,1,11,/vladislavleonov/disaggregate-forecast-cabaxiom-fork,Tabular Playground Series - Sep 2022
8764,105451102,96.0,4.504082494870855,8,26,/kaggleqrdl/disaggregate-forecast-cabaxiom-fork,Tabular Playground Series - Sep 2022
8765,104783983,322.0,,3,32,/mattop/tps-sep-2022-eda,Tabular Playground Series - Sep 2022
8766,105022331,137.0,,2,14,/mustafakeser4/tps-sep,Tabular Playground Series - Sep 2022
8767,106974784,36.0,,5,12,/kornelhowil/36th-place-solution-tps-sep22-eda-ridge-cv,Tabular Playground Series - Sep 2022
8768,104861318,154.0,,18,81,/ehekatlact/tps2209-ridge-lgbm-eda-topdownapproach,Tabular Playground Series - Sep 2022
8769,104894620,299.0,,3,18,/mhslearner/tps-sep-time-series-analysis-eda-lgbm,Tabular Playground Series - Sep 2022
8770,105682291,214.0,,0,0,/alexandrkolomijec/tps-september22,Tabular Playground Series - Sep 2022
8771,105027072,207.0,10.420138559264643,0,2,/zwqer2345/sept-2022-10-42013,Tabular Playground Series - Sep 2022
8772,106946395,337.0,5.950057421585339,20,66,/rayenghali023/simple-lightgbm-gridsearchcv-cross-val-5-93,Tabular Playground Series - Sep 2022
8773,105614325,206.0,,2,8,/wasshoiwasshoi/2022-tps-sep-quick-eda,Tabular Playground Series - Sep 2022
8774,105066411,227.0,25.028260770094,21,42,,Tabular Playground Series - Sep 2022
8775,104897586,250.0,,0,5,/santosh1974/play-ground-sept-first,Tabular Playground Series - Sep 2022
8776,104656930,364.0,,1,21,/alejopaullier/tps-september-2022-eda,Tabular Playground Series - Sep 2022
8777,104764403,301.0,7.330333313534928,0,1,/canonicalized/tps-sep-time-series-forecasting,Tabular Playground Series - Sep 2022
8778,105579412,310.0,,1,6,/stpeteishii/tps0922-histplot,Tabular Playground Series - Sep 2022
8779,106444147,325.0,5.165813679704416,27,106,/samuelcortinhas/tps-sept-22-timeseries-analysis,Tabular Playground Series - Sep 2022
8780,105119170,546.0,6.831466267073706,4,22,/ibraheemseyam/circle-time-units-pca-eda-pycaret,Tabular Playground Series - Sep 2022
8781,105190066,469.0,,10,19,/saraswatitiwari/tps-september-2022,Tabular Playground Series - Sep 2022
8782,104873158,319.0,13.48155017371506,0,1,/romankuliievych/tabular-playground-series-sep-2022,Tabular Playground Series - Sep 2022
8783,105935004,361.0,5.526511033343351,0,0,/namelessfairy/improvised-ema-device,Tabular Playground Series - Sep 2022
8784,106577909,306.0,192.2725016009697,2,3,/scchuy/tps-202209-lastyearfeatures-catboost,Tabular Playground Series - Sep 2022
8785,106965520,222.0,,0,1,/tejaswikumar24/tabular-september-playground-challenge,Tabular Playground Series - Sep 2022
8786,105416160,359.0,5.52697128415003,25,23,/satoshiss/tps-22-sep-review-time-series-and-some-ideas,Tabular Playground Series - Sep 2022
8787,106373964,381.0,5.5695448068965545,33,65,/hosseinbehjat/no-need-to-aggregate-and-disaggregate-tpssep22,Tabular Playground Series - Sep 2022
8788,105441388,378.0,,2,10,/rsesha/lazy-sulo-sep-tps-score-5-55,Tabular Playground Series - Sep 2022
8789,106773233,393.0,6.804652969708607,11,17,/brysonje/dates-feature-eng-catboost-regressor,Tabular Playground Series - Sep 2022
8790,106773233,393.0,6.804652969708607,11,17,/brysonje/dates-feature-eng-catboost-regressor,Tabular Playground Series - Sep 2022
8791,104792549,371.0,,18,30,/manishwahale/tps-sep22-eda,Tabular Playground Series - Sep 2022
8792,106503213,362.0,5.820679564383429,3,8,/alex97andreev/tuning-of-elasticnet-hyperparameters,Tabular Playground Series - Sep 2022
8793,105792726,213.0,5.88761182253381,0,0,/llllllillllilll/notebooka1e6ce774f,Tabular Playground Series - Sep 2022
8794,106567233,366.0,,9,21,/raghulraj422/time-series-prediction-tps-sept-2022,Tabular Playground Series - Sep 2022
8795,106144915,735.0,6.330785595528946,0,8,/roccoincardona/tabular-series-sep22-intro-analysis-xgboost,Tabular Playground Series - Sep 2022
8796,106574996,740.0,,12,19,/shibumohapatra/tabular-playground-series-sep-2022,Tabular Playground Series - Sep 2022
8797,105865090,474.0,,0,0,/manguu/simple-lightgbm-gridsearchcv-encoding-weight,Tabular Playground Series - Sep 2022
8798,155949789,438.0,,12,29,/egeakyol/tps-sep-eda-modelling-6-77378-with-shap,Tabular Playground Series - Sep 2022
8799,106043996,318.0,17.629107221288056,11,15,/alvinleenh/tpssep22-ensemble-model-ctb-xgb-lgb,Tabular Playground Series - Sep 2022
8800,104712389,435.0,,2,15,/viktorfairuschin/tps-sep-22-stl-decomposition,Tabular Playground Series - Sep 2022
8801,106070807,442.0,,8,12,/gelgel5633/6-24-ensemble-lgbm-cat-rf-xgb,Tabular Playground Series - Sep 2022
8802,105761245,448.0,,52,66,/landfallmotto/tps-sep-22-eda-histgradientboosting-6-06,Tabular Playground Series - Sep 2022
8803,106855690,714.0,13.512990194251294,1,2,/zhdonas/tps-september-2022-cci-nn,Tabular Playground Series - Sep 2022
8804,105082043,389.0,,0,10,/stautxie/tabular-challenge-sep-2022-baseline,Tabular Playground Series - Sep 2022
8805,104714300,519.0,,1,4,/mrandri19/tpssep22-7-figure-eda,Tabular Playground Series - Sep 2022
8806,106092848,395.0,6.203289817630949,0,10,/viktortaran/tps-sep-2022,Tabular Playground Series - Sep 2022
8807,104977537,415.0,,42,98,/anubhavgoyal10/tps-september-in-depth-eda-score-6-20,Tabular Playground Series - Sep 2022
8808,107100608,399.0,,2,7,/aklimarimi/top-29-winning-solution-lol,Tabular Playground Series - Sep 2022
8809,104796176,509.0,,4,22,/ameerhamza0311/lightgbm,Tabular Playground Series - Sep 2022
8810,105334321,429.0,,2,6,/sahilr05/tabular-playground-series-r2-score-98,Tabular Playground Series - Sep 2022
8811,105632100,923.0,6.359847874835809,0,3,/mohitkarelia/playground-series-sept-2022,Tabular Playground Series - Sep 2022
8812,105632100,923.0,6.359847874835809,0,3,/mohitkarelia/playground-series-sept-2022,Tabular Playground Series - Sep 2022
8813,106636665,513.0,6.369676687096123,20,40,/samerrkhann/eda-is-all-you-need-visualizing-tps,Tabular Playground Series - Sep 2022
8814,106856764,763.0,,3,6,/weivvz/tps-sep-22-catboosterregressor-gridsearchcv,Tabular Playground Series - Sep 2022
8815,106892024,766.0,,0,1,/hangsu2022/tabular-playground-series-sep-catbooster,Tabular Playground Series - Sep 2022
8816,104731569,590.0,,16,40,/manthanx/tps-sep22-pycaret-voting-regressor-blend-6-58,Tabular Playground Series - Sep 2022
8817,106701591,436.0,6.642043843338969,6,16,/michaelgwinn/tpssep22-basic-eda-features-6-55-lb,Tabular Playground Series - Sep 2022
8818,104832574,454.0,8.109676093374048,0,4,/chrismysen/decisiontreemodel-tabular-playground-sept-2022,Tabular Playground Series - Sep 2022
8819,104689396,563.0,15.295650184737491,0,22,/nischaydnk/tps-sept-leak-free-catboost-baseline,Tabular Playground Series - Sep 2022
8820,106952006,479.0,,1,2,/daniil7191/sept-22-xgb-prophet,Tabular Playground Series - Sep 2022
8821,104953647,592.0,,1,6,/catadanna/tabular-folds-sep-2022,Tabular Playground Series - Sep 2022
8822,106395589,536.0,6.912860193401108,15,30,/ahmedtoba/xgb-vs-nn,Tabular Playground Series - Sep 2022
8823,105068666,528.0,6.687410834347681,0,8,/kostiantynlavronenko/tps-09-22-regression,Tabular Playground Series - Sep 2022
8824,106891625,621.0,7.656162788501559,0,1,/prosenjit123/pg-sep2022,Tabular Playground Series - Sep 2022
8825,106062020,568.0,6.967219479433867,12,34,/akioonodera/tps-sep22-lgbm-reg-optuna,Tabular Playground Series - Sep 2022
8826,104649241,577.0,6.811673827110536,4,35,/kotrying/tps0922,Tabular Playground Series - Sep 2022
8827,104750352,566.0,7.550482196835048,2,9,/chiehjulin/tps-sep-2022,Tabular Playground Series - Sep 2022
8828,104750352,566.0,6.962276250989376,2,9,/chiehjulin/tps-sep-2022,Tabular Playground Series - Sep 2022
8829,106788133,538.0,9.364119270615776,40,42,/mikita1580/tabular-playground-sep-lama,Tabular Playground Series - Sep 2022
8830,104784084,1301.0,,2,20,/paultimothymooney/use-tf-decision-forests-to-submit-to-tds-sep-22,Tabular Playground Series - Sep 2022
8831,106187932,588.0,,0,11,/gauravduttakiit/tps092022-lazypredict,Tabular Playground Series - Sep 2022
8832,105271585,578.0,,1,10,/salihkundakc/tabular-lgbm-0-969,Tabular Playground Series - Sep 2022
8833,104854915,553.0,6.809116519330639,0,12,/cesarsupo/tps-09-votingregressor,Tabular Playground Series - Sep 2022
8834,106926410,527.0,6.819457636587366,11,29,/reymaster/eda-time-series-features-votingregressor,Tabular Playground Series - Sep 2022
8835,105798570,608.0,6.827360597086535,0,2,/mamiglia/tps-09-22,Tabular Playground Series - Sep 2022
8836,105014179,619.0,,17,28,/ranjeetshrivastav/tps-sep-22-pycaret,Tabular Playground Series - Sep 2022
8837,105038038,579.0,,0,2,/itspavansatish/xgb-parameter-tuning,Tabular Playground Series - Sep 2022
8838,105944992,585.0,6.971496180076158,0,1,/amaneamane/basic-eda,Tabular Playground Series - Sep 2022
8839,106630801,662.0,,4,3,/osamarakan/day-of-the-week-feature-some-ideas,Tabular Playground Series - Sep 2022
8840,104942973,424.0,6.963062062555238,5,22,/himanshunayal/tps-sep-2022-using-smape-for-evaluation,Tabular Playground Series - Sep 2022
8841,105598770,645.0,,0,2,/param302/notebook-1,Tabular Playground Series - Sep 2022
8842,104875332,598.0,6.973698740677029,0,3,/hirotokitamur/hk-tabular-playground-series-sep-2022,Tabular Playground Series - Sep 2022
8843,106639242,606.0,6.999102351336594,13,10,/prievaragabriella/simple-tps-sept,Tabular Playground Series - Sep 2022
8844,105287424,599.0,7.011785976585065,0,4,/harshhzz/eda-and-modelling,Tabular Playground Series - Sep 2022
8845,106657182,628.0,,6,18,/bayremabdellaoui/xgboost-baseline-eda,Tabular Playground Series - Sep 2022
8846,104857974,649.0,,0,5,/hugolearn/tps-sep-practice,Tabular Playground Series - Sep 2022
8847,104889686,675.0,7.082092948123139,1,7,/aatiffraz/tps-09-2022-a-shopkeeper-s-perspective-baseline,Tabular Playground Series - Sep 2022
8848,113689661,660.0,39.58610097253551,13,9,/cid007/tps-sept-baseline-model,Tabular Playground Series - Sep 2022
8849,107642266,404.0,,0,0,/elitea92/notebook-team-gmlboot-albertolou,Tabular Playground Series - Sep 2022
8850,107041516,705.0,,0,2,/mukaseevru/tps-sep-22-lama-lightautoml,Tabular Playground Series - Sep 2022
8851,129344223,718.0,25.122072341386364,17,57,/toshimelonhead/forecasting-sktime-edition,Tabular Playground Series - Sep 2022
8852,107124084,652.0,7.597384753794412,0,0,/danilopaula/tps-sep22-eda-fe-hyperparametertunning-lgbm,Tabular Playground Series - Sep 2022
8853,105941828,559.0,7.422872853439934,0,5,/ohba0321/tps2209-edaandlightgbm,Tabular Playground Series - Sep 2022
8854,105984626,428.0,7.645363366764005,1,4,/angelmartinezromero/tabular,Tabular Playground Series - Sep 2022
8855,106386407,701.0,,6,6,/yangtony1999/easy-to-follow-guidance-tps-sep,Tabular Playground Series - Sep 2022
8856,105826915,515.0,8.377903771096218,1,1,/yy123123/tps-sep-2022-simple-to-use-stacked-lstm,Tabular Playground Series - Sep 2022
8857,106988958,907.0,21.645806774768094,0,0,/starship006/september-tabular-playground-series-2022,Tabular Playground Series - Sep 2022
8858,106877655,744.0,,0,2,/jeetkumarpal/tabular-playground-series-sep-2022,Tabular Playground Series - Sep 2022
8859,105561654,785.0,7.756107109242999,0,2,/bahaakhaled97/informative-eda-simple-ensemble-models,Tabular Playground Series - Sep 2022
8860,110221673,784.0,,0,1,/jnavio/notebook-september,Tabular Playground Series - Sep 2022
8861,105403702,899.0,26.077648431669783,1,6,/miwojc/tps2209-00,Tabular Playground Series - Sep 2022
8862,106697014,787.0,9.216005122224573,10,9,/imnaho/tps-22-sep,Tabular Playground Series - Sep 2022
8863,104713080,698.0,,2,8,/yanmazas/data-analysis-for-my-first-shared-notebook,Tabular Playground Series - Sep 2022
8864,105577194,451.0,39.440940321532665,1,4,/javiersaenz/using-modeltime-r-library,Tabular Playground Series - Sep 2022
8865,107188376,827.0,,8,13,/gauravmalik26/stacking-xgb-catboost-lgb-tps-sep-2022,Tabular Playground Series - Sep 2022
8866,106855529,850.0,9.603406437882787,2,4,/lucaverderio/tps-kaggle-merchandise-stores-tensorflow,Tabular Playground Series - Sep 2022
8867,104730083,516.0,35.374093247686986,0,7,/vijayendrad/tabular-playground-sep22,Tabular Playground Series - Sep 2022
8868,105227615,946.0,,3,11,/saumitgp/gradient-boosting-97-9,Tabular Playground Series - Sep 2022
8869,106514186,894.0,34.17060349299546,0,2,/luisvcs/tabular-eda-feature-and-tf-modelling,Tabular Playground Series - Sep 2022
8870,106514186,894.0,34.17060349299546,0,2,/luisvcs/tabular-eda-feature-and-tf-modelling,Tabular Playground Series - Sep 2022
8871,108425359,935.0,,0,1,/snehangsude/tps-sep-2022,Tabular Playground Series - Sep 2022
8872,106590248,903.0,17.175574277057308,6,21,/sergeyyakovlev1312/time-series-prediction-using-nn,Tabular Playground Series - Sep 2022
8873,116817820,835.0,,1,1,/deepshikha0105/tabular-playground,Tabular Playground Series - Sep 2022
8874,104884093,829.0,,0,6,/mhadani/tps-sep-2022,Tabular Playground Series - Sep 2022
8875,106904480,974.0,12.074189910452205,0,0,/re22an/predict-book-sales-2021-tps-sep-2022,Tabular Playground Series - Sep 2022
8876,104905901,797.0,,0,7,/debadri1010/tabular-playground-sept-2022-eda,Tabular Playground Series - Sep 2022
8877,104670032,879.0,11.498707149352896,1,5,/tracyporter/sep-22-tabular,Tabular Playground Series - Sep 2022
8878,106138822,957.0,,2,7,/eldarsarajlic/beginner-time-series-code-commentary,Tabular Playground Series - Sep 2022
8879,104662325,960.0,12.310691761921094,5,9,/racastroc/basic-implementation-of-prophet-forecasting-model,Tabular Playground Series - Sep 2022
8880,105036060,945.0,13.578339676611364,0,0,/ahmetemrebelge/lstm-and-adjusting-batch-size-epoch-num,Tabular Playground Series - Sep 2022
8881,105211946,911.0,,1,6,/nuritasthedataist/tps-sept-22-lgbm,Tabular Playground Series - Sep 2022
8882,104964771,885.0,52.02814141367704,0,4,/nurielreuven/tps-sep-2022-eda-lstm-model,Tabular Playground Series - Sep 2022
8883,104849552,927.0,,2,9,/davidhguerrero/eda-to-gain-insights-tpssep22,Tabular Playground Series - Sep 2022
8884,106743407,972.0,,1,3,/ytakashina/tps-index-creation,Tabular Playground Series - Sep 2022
8885,106334932,980.0,39.78374431988525,0,1,/barbagrande007/september-bbg007,Tabular Playground Series - Sep 2022
8886,106334932,980.0,39.78374431988525,0,1,/barbagrande007/september-bbg007,Tabular Playground Series - Sep 2022
8887,105704059,998.0,,5,15,/sardorabdirayimov/target-encoding-high-cardinality-feature,Tabular Playground Series - Sep 2022
8888,106894949,971.0,,0,0,/ashishtop/date-variables-eda-model,Tabular Playground Series - Sep 2022
8889,105423455,1002.0,,2,8,/sidharkal/playground-notebook,Tabular Playground Series - Sep 2022
8890,106786859,999.0,,3,5,/atrijtalgery/tps09-22-gaussian-mix-seasonality-encoding-mlpreg,Tabular Playground Series - Sep 2022
8891,106061940,997.0,69.23077096746711,2,5,/excitingstuff/8-87-m-a-e,Tabular Playground Series - Sep 2022
8892,104800318,1036.0,25.668050518615605,3,9,/cyborg123/simple-regression,Tabular Playground Series - Sep 2022
8893,106814776,1145.0,,8,12,/jineeshkb/tabular-play-series-simple-xgb-model,Tabular Playground Series - Sep 2022
8894,105199978,1020.0,,0,9,/nishantdhingra/detailed-eda-tps-september-2022,Tabular Playground Series - Sep 2022
8895,106865869,1042.0,21.919310340163705,5,15,/msayak/tps-sep22-lr-ridge,Tabular Playground Series - Sep 2022
8896,105978263,1066.0,,1,8,/jamesmcguigan/tps-2022-09-profilereport-autoeda,Tabular Playground Series - Sep 2022
8897,106970570,984.0,,4,5,/thesarfaraz/multiple-arma-models-tps-sep2022,Tabular Playground Series - Sep 2022
8898,110856168,1138.0,,0,9,/lizavetababior/google-ml-bootcamp-learning,Tabular Playground Series - Sep 2022
8899,105522374,1116.0,26.96127317656937,0,0,/efaniorimutembo/xgboost-approach,Tabular Playground Series - Sep 2022
8900,104886951,1131.0,25.876641488834068,0,1,/shamimahossain/tfdf-regression,Tabular Playground Series - Sep 2022
8901,106433946,1092.0,,2,11,/girishvutukuri/exercise-tabular-playground,Tabular Playground Series - Sep 2022
8902,104859381,1148.0,27.12611460757887,0,10,/r0hn00/tps-sept22,Tabular Playground Series - Sep 2022
8903,104780247,1155.0,27.90461420400289,0,3,/owaishaseeb/book-sale-prediction,Tabular Playground Series - Sep 2022
8904,106920017,1175.0,28.206665370852622,4,11,/ayushjain001/tabular-playground-series-september,Tabular Playground Series - Sep 2022
8905,106924512,1226.0,29.0880536474399,2,5,/une510/tps-sep-2022,Tabular Playground Series - Sep 2022
8906,105420857,1245.0,,0,5,/datarohitingole/tps-sep-22-xgbregressor-catboostregressor,Tabular Playground Series - Sep 2022
8907,105731769,1300.0,,0,1,/deokmoonkang/tabular-2022-sep,Tabular Playground Series - Sep 2022
8908,106393272,1309.0,,0,5,/yessicaangulolen/notebook-tps-september-ipynb,Tabular Playground Series - Sep 2022
8909,105919768,1314.0,44.02395414795277,0,0,/realapex/tabular-data-draft-1,Tabular Playground Series - Sep 2022
8910,105588859,1321.0,,1,3,/ahndonghoon/my-first-kaggle-submission,Tabular Playground Series - Sep 2022
8911,106722424,1343.0,,0,2,/marcuspop/september-tabular-tf-timeseries,Tabular Playground Series - Sep 2022
8912,105477839,1351.0,,2,20,/susnato/tps-2022-sep-adversarial-validation,Tabular Playground Series - Sep 2022
8913,113468486,10.0,,0,3,/habedi/embed-documents,Feedback Prize - English Language Learning
8914,111329532,8.0,0.4375376969517735,0,9,/rashmibanthia/fb3-single-model-avg-2-seeds-gold-solution,Feedback Prize - English Language Learning
8915,111126206,218.0,,0,0,/kittyelephant/fb3-deberta-family-inference-weight-tune-6979f1,Feedback Prize - English Language Learning
8916,107322856,812.0,,0,6,/renokan/engll-analysis-of-the-trash-or-not,Feedback Prize - English Language Learning
8917,113628180,45.0,0.4394234788331808,0,0,/vlomme/fork-of-fb3-fast-cpu,Feedback Prize - English Language Learning
8918,105321484,3.0,0.446754780703229,22,254,/cdeotte/rapids-svr-cv-0-450-lb-0-44x,Feedback Prize - English Language Learning
8919,111136249,9.0,,0,4,/conjuring92/pl-sampling-analysis,Feedback Prize - English Language Learning
8920,110828858,906.0,0.4390092429006322,2,34,/batprem/deberta-layerwiselr-lastlayerreini-infer,Feedback Prize - English Language Learning
8921,105360054,46.0,,7,99,/vad13irt/optimization-approaches-for-transformers-part-2,Feedback Prize - English Language Learning
8922,105891005,90.0,0.4463321575589289,0,2,/leehann/feedback-ell-infer,Feedback Prize - English Language Learning
8923,109800011,593.0,,0,0,/millerrfu/1-fb3-eda,Feedback Prize - English Language Learning
8924,108224340,6.0,,0,0,/tikutiku/fb3-14-v1-01-deberta-v3-base-class012,Feedback Prize - English Language Learning
8925,111475552,84.0,,0,1,/tmhrkt/fb3-embedding-learning-training,Feedback Prize - English Language Learning
8926,110046473,743.0,,2,17,/currypurin/feedback3-duplication-with-past-competition-data,Feedback Prize - English Language Learning
8927,106842088,794.0,,1,2,/quangphm/fb3-try-to-find-features-for-each-target,Feedback Prize - English Language Learning
8928,107450764,119.0,,3,29,/verracodeguacas/spacy-linguistic-features-svr-and-optuna,Feedback Prize - English Language Learning
8929,105151572,102.0,0.4416981592997754,0,4,/pjmathematician/gluon-feedback-2,Feedback Prize - English Language Learning
8930,107613052,20.0,0.4368751924921968,0,4,/columbia2131/fb3-sub-exp16202122303132333638464748,Feedback Prize - English Language Learning
8931,104570449,1112.0,,0,2,/arvissu/quick-starts-deberta-training-1-epoch,Feedback Prize - English Language Learning
8932,111436752,639.0,,0,4,/illidan7/poormannlp-py,Feedback Prize - English Language Learning
8933,112600614,938.0,0.4458369012553982,2,2,/takamichitoda/fb3-efficiency-19th-scoringtime-is-345,Feedback Prize - English Language Learning
8934,107628356,35.0,,0,1,/tmishinev/feedback-prize-tfidf-ridge-baseline,Feedback Prize - English Language Learning
8935,107274771,174.0,,27,129,,Feedback Prize - English Language Learning
8936,107079811,341.0,,0,1,/pyagoubi/fb3-bert-large,Feedback Prize - English Language Learning
8937,104589977,142.0,,0,2,/arvinddevarkonda/fb3-creating-folds-using-bins,Feedback Prize - English Language Learning
8938,104648733,117.0,,3,6,/tomoyayanagi/feedback3-topics-identification-with-bertopic,Feedback Prize - English Language Learning
8939,106572281,479.0,0.5066900997606304,2,5,/maverickss26/feedback-analysis-using-svr-boruta,Feedback Prize - English Language Learning
8940,108599326,162.0,0.4381640970114355,0,0,/shigengtian/ensemble-9-10-11-12,Feedback Prize - English Language Learning
8941,114813841,521.0,,0,1,/junseonglee11/fb3-create-tfrecord,Feedback Prize - English Language Learning
8942,112661442,106.0,,0,1,/bachan/fb3-notebook-0-436099-private-lb,Feedback Prize - English Language Learning
8943,107284111,532.0,,11,73,/javigallego/english-language-learning-complete-eda,Feedback Prize - English Language Learning
8944,104857182,541.0,0.5057616943979055,0,12,/jeremyadamsfisher/distilbert-fpell-x-huggingface-trainer,Feedback Prize - English Language Learning
8945,112389822,2321.0,0.5570385700327013,0,0,/alexisterry/english,Feedback Prize - English Language Learning
8946,107243332,970.0,0.5327728284066281,6,13,/electro/fp3-bag-of-words-tensorflow-starter,Feedback Prize - English Language Learning
8947,106202633,568.0,,0,5,/xinzewu/wxz1-bert,Feedback Prize - English Language Learning
8948,111375511,186.0,,0,11,/realstay/cv0-43-fb3-pytorch-model,Feedback Prize - English Language Learning
8949,112361178,2.0,,0,3,/goldenlock/best-pb-online-1127,Feedback Prize - English Language Learning
8950,112566901,89.0,,0,0,/msanselme/notebook1,Feedback Prize - English Language Learning
8951,104717188,77.0,,2,14,/yujikomi/all-essays-for-3-feedback-competitions,Feedback Prize - English Language Learning
8952,105578885,294.0,0.444315108735486,3,20,/ebn7amdi/baseline,Feedback Prize - English Language Learning
8953,109246763,1058.0,,0,1,/parksu92/english-language-learning-vectorization-lgbm,Feedback Prize - English Language Learning
8954,111139083,335.0,0.5354681229703145,0,7,/rockerritesh/multi-label-regression-with-tfidf,Feedback Prize - English Language Learning
8955,109452827,365.0,,0,3,/tafreen/notebook-ell,Feedback Prize - English Language Learning
8956,109532240,367.0,,19,52,/qcqced/fbp-baseline-eda-preprocess,Feedback Prize - English Language Learning
8957,111752158,369.0,0.438846095475587,0,0,/elainechun/fb3-single-pytorch-model-inference,Feedback Prize - English Language Learning
8958,106022161,415.0,,2,7,/danofer/ell-nlp-feature-engineering-textacy-textstat,Feedback Prize - English Language Learning
8959,108172888,109.0,,2,33,/vslaykovsky/1-2-more-training-data-from-fb2021,Feedback Prize - English Language Learning
8960,112274461,1372.0,0.4627592551675623,0,1,/bajajganesh/deberta-v3base-layerwiselr-lastlayerreinit-5folds,Feedback Prize - English Language Learning
8961,114503050,573.0,,14,58,/kevinmorgado/language-initial-eda-and-feature-engineering,Feedback Prize - English Language Learning
8962,110470279,1166.0,0.439009244916237,13,31,/jundthird/kor-deberta-base-layerwiselr-lastlayerreinit,Feedback Prize - English Language Learning
8963,112909128,686.0,,1,3,/sambhramakhushi/sambhramassubmition,Feedback Prize - English Language Learning
8964,105130041,688.0,0.4426450218272735,0,1,/arkadius/baseline,Feedback Prize - English Language Learning
8965,111694637,690.0,,1,17,/kohashi0000/stacking-with-lr-0-46,Feedback Prize - English Language Learning
8966,111774506,698.0,,2,17,/johanmoncouti/is-bloom-a-teacher,Feedback Prize - English Language Learning
8967,108485981,713.0,0.5110072954161821,0,6,/egorsheremetov3/bert-defined-for-every-feature,Feedback Prize - English Language Learning
8968,111021627,1472.0,0.4677287962813537,0,8,/lysatrf/roberta-demo-0-46,Feedback Prize - English Language Learning
8969,110099854,1367.0,0.7964892735466605,2,5,/sandeepmnair/word2vec-ml-approach,Feedback Prize - English Language Learning
8970,110198538,827.0,0.438846095475587,0,34,/ridwanultanvir/feedback-prize-english-language-pytorch-model,Feedback Prize - English Language Learning
8971,107479722,834.0,0.588830041737511,0,1,/tdoh86/baseline-sklearn,Feedback Prize - English Language Learning
8972,106268451,852.0,,0,0,/growbigger/essay-analyze-with-bert-tensorflow,Feedback Prize - English Language Learning
8973,105355647,871.0,0.5306811352054247,0,1,/w1326627677/feedback-lgbm-doc2vec,Feedback Prize - English Language Learning
8974,105435189,935.0,,4,35,/atharvaingle/feedback-3-0-eda-metric-analyze-folds,Feedback Prize - English Language Learning
8975,107331382,1059.0,,2,4,/xxxxyyyy80008/feedback-prize-english-language-learning-eda,Feedback Prize - English Language Learning
8976,106880487,1422.0,,2,15,/tadakasuryateja/feedback-prize-3-ell-eda,Feedback Prize - English Language Learning
8977,110885489,1189.0,0.5336973790800457,3,11,/lonnieqin/multi-label-regression-with-conv1d,Feedback Prize - English Language Learning
8978,106511250,1126.0,0.5285338453137179,6,15,/suryadeepti/basic-approach,Feedback Prize - English Language Learning
8979,109512428,1375.0,0.5201019331599844,2,10,/shuntakinami/tfidf-lgbm-simple-model,Feedback Prize - English Language Learning
8980,105952744,1377.0,0.5543616978295761,0,4,/anomanderake/chaining-regressor-models,Feedback Prize - English Language Learning
8981,104666227,950.0,,5,9,/chaitanyagiri/feedback-3-eda-train,Feedback Prize - English Language Learning
8982,104616285,1323.0,0.5404173508305683,0,0,/sharmoul/feedback-prize-ell-baseline,Feedback Prize - English Language Learning
8983,112455528,1331.0,0.4501768566186055,0,0,/glebasik/feedback-prize,Feedback Prize - English Language Learning
8984,108500790,1495.0,,0,2,/marcgoff/mcrmse-explanation-algorithm,Feedback Prize - English Language Learning
8985,105480536,1496.0,,0,5,/joonhankim93/fb3-simple-eda,Feedback Prize - English Language Learning
8986,104829339,1283.0,0.5306466690482873,7,15,/venkatkumar001/fp3-simple-baseline-kfold-lr-rf-solution,Feedback Prize - English Language Learning
8987,109125350,1289.0,0.557914282229724,0,1,/yuriao/english-language-learning-lgbm-doc2vec,Feedback Prize - English Language Learning
8988,107645338,1341.0,0.4467551096076749,0,2,/hokkey/notebook20221010,Feedback Prize - English Language Learning
8989,109766532,1577.0,0.4501652640713856,0,1,/nhkhoi/english-language-learning-training-2,Feedback Prize - English Language Learning
8990,109766532,1577.0,0.4501652640713856,0,1,/nhkhoi/english-language-learning-training-2,Feedback Prize - English Language Learning
8991,105779221,1017.0,,0,2,/takeshisuzuki/how-do-annotators-score,Feedback Prize - English Language Learning
8992,111521727,1633.0,0.4432278057748423,0,0,/sr5htq/english-essay-feedback,Feedback Prize - English Language Learning
8993,104885693,1037.0,,0,5,/bibhabasumohapatra/my-dataset-exp-for-long-text-hope-works-out,Feedback Prize - English Language Learning
8994,106278975,1652.0,0.5376731189984236,18,44,/swimmy/stacking-xgboost-lgbm-ridge-catboost,Feedback Prize - English Language Learning
8995,104880636,1648.0,,6,55,/debarshichanda/fb3-custom-hf-trainer-w-b-starter,Feedback Prize - English Language Learning
8996,106116374,1664.0,0.531117135581456,0,7,/kawamoto/english-language-learning-eda-with-nltk,Feedback Prize - English Language Learning
8997,106104153,1658.0,,4,19,/chazzer/feedback-3-eda-with-plotly,Feedback Prize - English Language Learning
8998,112190166,1728.0,,0,0,/jasonchoi3/fb3-train-jasonchoi,Feedback Prize - English Language Learning
8999,104714381,1501.0,0.4565206662995528,0,8,/thedrcat/fb3-ordinal-regression-baseline-inference,Feedback Prize - English Language Learning
9000,112162029,1669.0,0.4466805616655978,1,0,/prem134/bert-last-2-layers-retrain-and-globalmaxpool1d,Feedback Prize - English Language Learning
9001,105960292,1519.0,,2,8,/takeng/eda-misspelling,Feedback Prize - English Language Learning
9002,112009982,1697.0,0.5145402278782726,0,0,/gshchen/fb3-multi-gbdt-v1-train,Feedback Prize - English Language Learning
9003,105204314,1643.0,,0,1,/kvsnoufal/linear-regression-tfidf-feedback3,Feedback Prize - English Language Learning
9004,108332626,1691.0,0.4818608266769206,0,4,/bayremabdellaoui/feedback-prize-easy-with-bert,Feedback Prize - English Language Learning
9005,104589810,1700.0,,2,17,/chetan8007/max-token-length-1428,Feedback Prize - English Language Learning
9006,143913177,1705.0,,0,2,/wisawesome/24th-place-eff-prize-feedback-prize-ell-train,Feedback Prize - English Language Learning
9007,108617645,1708.0,,0,0,/subhankarnag/feedback-ell,Feedback Prize - English Language Learning
9008,108617645,1708.0,,0,0,/subhankarnag/feedback-ell,Feedback Prize - English Language Learning
9009,111128191,1732.0,0.4849209431040678,0,0,/kkahloots/deberta-t5-embedding,Feedback Prize - English Language Learning
9010,119254414,1754.0,0.4530994869714706,0,0,/pavelmalykh/roberta-fine-tunung,Feedback Prize - English Language Learning
9011,106960695,1774.0,0.5434572868105,3,22,/alvinleenh/fb3-why-not-tf-idf-text-vectorization,Feedback Prize - English Language Learning
9012,111851849,1782.0,0.4629960800902049,0,3,/vitouphy/feedback-prize-with-pretrained-tf-roberta,Feedback Prize - English Language Learning
9013,108054268,1731.0,,8,26,/shreydan/first-look-at-data-eda-read-some-essays,Feedback Prize - English Language Learning
9014,113402273,1744.0,,0,0,/girlduck/hfembedding-svr-train,Feedback Prize - English Language Learning
9015,112516377,1719.0,,0,0,/sagarikajadon/feedback3-deberta,Feedback Prize - English Language Learning
9016,109446864,1781.0,,2,5,/raj26000/fb3-0-46-pytorch-deberta-base-parallel-training,Feedback Prize - English Language Learning
9017,107983370,1791.0,0.4624996699439656,0,2,/riadalmadani/infrerence-roberta-model,Feedback Prize - English Language Learning
9018,107983370,1791.0,0.4624996699439656,0,2,/riadalmadani/infrerence-roberta-model,Feedback Prize - English Language Learning
9019,109415192,1821.0,0.5247279607309724,0,5,/oumounimestapha/tfidf-svr,Feedback Prize - English Language Learning
9020,111608691,1804.0,0.5254922790242865,0,9,/harishganesh3/distilbert-lstm,Feedback Prize - English Language Learning
9021,158764348,1812.0,,0,0,/kendevoe/ell-deberta-v3-base,Feedback Prize - English Language Learning
9022,105956344,1843.0,,1,5,/rayenghali023/basic-distilbert-offline-model-tensorflow-gpu-nlp,Feedback Prize - English Language Learning
9023,120550925,1834.0,,1,2,/amitabhphatak/feedback-prize,Feedback Prize - English Language Learning
9024,105757333,1844.0,0.4984362792463745,0,4,/amaudruz/feedbackprize-bertridge,Feedback Prize - English Language Learning
9025,109730468,1888.0,0.4746348555481643,0,0,/sanmaprogramming/notebook-nlp-1,Feedback Prize - English Language Learning
9026,115928480,1924.0,0.4880493175886522,0,3,/nmbailey/ell-feedback-prize-distilbert,Feedback Prize - English Language Learning
9027,110290375,1899.0,0.4814345455693303,0,0,/noemieren/bert1111,Feedback Prize - English Language Learning
9028,107770588,1895.0,0.6014679927068832,4,19,/timokerr/absolute-baseline-test-no-training,Feedback Prize - English Language Learning
9029,110391419,1949.0,0.4893923094981045,0,2,/mdbodrulalam/ell-feedback-prize-prediction,Feedback Prize - English Language Learning
9030,112510852,2254.0,0.5077301853895494,0,17,/skiplik/feedback-ell-w-pytorch-first-time-train,Feedback Prize - English Language Learning
9031,105994236,1983.0,,4,10,/seonghyeone/fb3-bert-simple,Feedback Prize - English Language Learning
9032,108899835,1994.0,0.4915037067285969,0,1,/vection/feedback-deberta-v3-custom,Feedback Prize - English Language Learning
9033,104934002,1920.0,,0,0,/msvensson222/unexpected-submission-scoring-error,Feedback Prize - English Language Learning
9034,105985788,1948.0,0.5079489653191738,9,40,/junjitakeshima/ell-simple-roberta-starter-eng,Feedback Prize - English Language Learning
9035,105816245,1988.0,0.4989485371362702,0,1,/omarrelsayeed/simple-deberta-v3-large-1-epoch-0-49-lb,Feedback Prize - English Language Learning
9036,112413620,1998.0,,0,0,/nikto547/syntax,Feedback Prize - English Language Learning
9037,132121069,2049.0,0.507332705037088,13,80,/tangelus/english-language-learning-vectorization-lgbm,Feedback Prize - English Language Learning
9038,105650248,2060.0,,0,0,/devanshu12122/feedback-prize-english-lang-roberta,Feedback Prize - English Language Learning
9039,107493042,2090.0,,0,3,/ozoozo/feedback-prize-lightgbm-tfidfvectorizer,Feedback Prize - English Language Learning
9040,111954193,2055.0,0.6153461475832697,0,1,/pzarzycki/ell-competition-simple-model,Feedback Prize - English Language Learning
9041,105588789,2054.0,,0,2,/saansd2003/feedback-prize-lang-learn-ulmfit-baseline,Feedback Prize - English Language Learning
9042,107692581,2119.0,0.571842515823759,0,1,/danielmoram/cnn-feature-extractor-ridge-free4allell,Feedback Prize - English Language Learning
9043,112473922,2042.0,,0,0,/ritatsepeleva/notebook34921e58cf,Feedback Prize - English Language Learning
9044,105509236,2136.0,,0,3,/avilaqba/draft-2-score-0-51,Feedback Prize - English Language Learning
9045,109763190,2101.0,,0,0,/shahsavari86/statistical-inferences-multioutput-classification,Feedback Prize - English Language Learning
9046,107411514,2032.0,0.5205177644534907,0,2,/dilthoms/ell-sub,Feedback Prize - English Language Learning
9047,105108359,2171.0,2.948967686536004,0,2,/mdshahbazalam/simple-mlp-2,Feedback Prize - English Language Learning
9048,113244660,2155.0,,1,3,/josarago/0-45-score-with-lightgbm-and-deberta-feature,Feedback Prize - English Language Learning
9049,111514562,2217.0,0.5242042948358097,0,0,/negi0897/tfidfvectorizer,Feedback Prize - English Language Learning
9050,106679129,2185.0,0.5264358458313214,6,20,/francescoliveras/feedbackprice-en-es,Feedback Prize - English Language Learning
9051,110066747,2187.0,,1,2,/samratthapa/quick-baseline-tfidf-and-lightgbm,Feedback Prize - English Language Learning
9052,110111074,2105.0,0.5263821678694214,0,2,/iori76sushi/keras-lgb-simple-ensemble,Feedback Prize - English Language Learning
9053,116817138,2117.0,0.5114214151822666,0,3,/minyewoo/dense-layers,Feedback Prize - English Language Learning
9054,131618112,2182.0,,2,11,/mohdmuttalib/english-language-learning,Feedback Prize - English Language Learning
9055,107973094,2196.0,,4,9,/jimgruman/tidymodels-lightgbm,Feedback Prize - English Language Learning
9056,106846291,2223.0,0.5285338453137179,0,0,/santosh1974/feedback-learning-edanalysis-simple-model,Feedback Prize - English Language Learning
9057,111339088,2240.0,0.5316851865674826,4,7,/johnnytay/nlp-feedback-on-english-language-learning,Feedback Prize - English Language Learning
9058,107606308,2156.0,,2,6,/joeroberts/processing-into-kfolds,Feedback Prize - English Language Learning
9059,105884234,2244.0,0.5339617745679107,0,6,/shudhatmajain/analysis-and-eda,Feedback Prize - English Language Learning
9060,116804671,2245.0,,0,1,/neeekit/notebook747e163b41,Feedback Prize - English Language Learning
9061,105326665,2229.0,0.5348427900577787,7,33,/rijudhara/ell-lgbmregressor,Feedback Prize - English Language Learning
9062,105769571,2230.0,0.5348427900577787,0,0,/aanyakhan/lgbmregressor,Feedback Prize - English Language Learning
9063,105921823,2280.0,0.5359000654481233,5,17,/jazivxt/old-school,Feedback Prize - English Language Learning
9064,110211326,2318.0,,0,0,/mitchhuang777/compete-feedback-prize-english-language-learning,Feedback Prize - English Language Learning
9065,113838496,2271.0,,6,23,/jonbown/feedback-prize-candidate-model-exploration,Feedback Prize - English Language Learning
9066,104715443,2286.0,0.5431480135274434,0,6,/finlay/feedback-prize-tfidf-ml-model-english,Feedback Prize - English Language Learning
9067,105274268,2304.0,,7,16,/rachanabisht/ell-eda,Feedback Prize - English Language Learning
9068,105715217,2307.0,0.5726034720735694,0,0,/maulberto3/fp3-2022-vect-f-extr-cv-pipe-hps,Feedback Prize - English Language Learning
9069,105709582,2301.0,,0,0,/sajutr/notebookaa1cc8ef8a,Feedback Prize - English Language Learning
9070,105033476,2290.0,,0,4,/johnpap6/ell-eda-is-essay-length-predictive-or-not,Feedback Prize - English Language Learning
9071,106795641,2322.0,0.5494567842780643,5,20,/tracyporter/ell-nlp-multioutput,Feedback Prize - English Language Learning
9072,111433590,2335.0,0.6306885874507628,0,9,/paarthbhatnagar/fb3-pytorch-lightning-roberta-baseline-mlp,Feedback Prize - English Language Learning
9073,111007955,2289.0,,0,0,/schlagg/2nd-try-bert-based-regression,Feedback Prize - English Language Learning
9074,108189698,2354.0,0.5796618710167645,1,5,/msvrao/competition,Feedback Prize - English Language Learning
9075,107547841,2409.0,,12,35,/riteshsinha/feedback-prize-data-exploration,Feedback Prize - English Language Learning
9076,107381683,2392.0,0.578175814693203,3,8,/prajittr/basic-nlp-xgb-score-0-57,Feedback Prize - English Language Learning
9077,108916407,2399.0,0.6154979838102077,0,1,/hemanth171/xgbregressor-model,Feedback Prize - English Language Learning
9078,111329304,2406.0,,0,0,/bryannho/svr-baseline,Feedback Prize - English Language Learning
9079,104565394,2434.0,0.5807231713853863,0,6,/rexhaif/mcrmse-metric-in-numpy,Feedback Prize - English Language Learning
9080,104565394,2434.0,0.5807231713853863,0,6,/rexhaif/mcrmse-metric-in-numpy,Feedback Prize - English Language Learning
9081,126131150,2411.0,0.6308336432689021,1,16,/jocker3/feedback-prize-english-language-learning,Feedback Prize - English Language Learning
9082,104678260,2430.0,0.5899263932319428,0,3,/adewoleakorede/feedback-prize-baseline1,Feedback Prize - English Language Learning
9083,106219121,2472.0,0.602268500259156,0,1,/azisanw19/pos-tagging-lstm,Feedback Prize - English Language Learning
9084,106219121,2472.0,0.5999579475073383,0,1,/azisanw19/pos-tagging-lstm,Feedback Prize - English Language Learning
9085,105604812,2443.0,0.6075447379829092,0,2,/intrincantation/interpretable-baseline-no-nn-score-60,Feedback Prize - English Language Learning
9086,108666693,2470.0,0.6110424827447026,0,15,/essammohamed4320/essay-evaluation-with-lstm-vs-deberta-v-3,Feedback Prize - English Language Learning
9087,105889066,2479.0,,4,5,/hechtjp/feedback-prize-ell-eda-dimensionality-reduction,Feedback Prize - English Language Learning
9088,110477228,2480.0,0.6139515478789264,0,0,/yasirfalih/lab-1,Feedback Prize - English Language Learning
9089,105886759,2510.0,0.6450978605729135,1,11,/youktinathbhowmick/fpell-a-very-basic-and-weird-baseline,Feedback Prize - English Language Learning
9090,109976104,2518.0,0.6201398718752654,0,0,/estebangarciacarmona/kurrukukuis-submission,Feedback Prize - English Language Learning
9091,111443703,2577.0,0.7668048914464617,3,40,/kilogrand/graph-neural-network-in-nlp,Feedback Prize - English Language Learning
9092,106559354,2549.0,,0,4,/sadivamadaan/fastai-x-huggingface-starter,Feedback Prize - English Language Learning
9093,108990867,2570.0,,0,1,/bwallyn/feedback-prize-analyze-dataset,Feedback Prize - English Language Learning
9094,111567208,2571.0,,0,4,/luludragon/bert-relu-softmax-multihead-solution-8387eb,Feedback Prize - English Language Learning
9095,112937349,2532.0,0.6579881608329631,0,1,/robinrojowiec/lstm-word-embeddings-attention,Feedback Prize - English Language Learning
9096,104838643,2477.0,,5,22,/manishwahale/english-language-learning-eda,Feedback Prize - English Language Learning
9097,110956829,2601.0,,0,0,/vinitkp/feedbackprize-english-language-learning-vinitp,Feedback Prize - English Language Learning
9098,105958124,2596.0,,3,13,/ficklemaverick/starter-notebook-simple-modelling,Feedback Prize - English Language Learning
9099,110238935,2598.0,0.7102016506534875,0,4,/nesrineazaiez/feedback-prize-english-language-learning,Feedback Prize - English Language Learning
9100,110238935,2598.0,1.0743994398230008,0,4,/nesrineazaiez/feedback-prize-english-language-learning,Feedback Prize - English Language Learning
9101,108812410,2613.0,,0,0,/aimarz9/probamultitaskaimar,Feedback Prize - English Language Learning
9102,110971763,2618.0,0.8782183589802729,0,6,/anovayana/ell-tokenizer-logistic-regression,Feedback Prize - English Language Learning
9103,104673123,2628.0,1.2184825004413091,0,2,/omarelnahas/feedback-prize,Feedback Prize - English Language Learning
9104,106744309,2633.0,1.400250646307936,0,3,/chiennguyendev/english-language-learning-svm-smote,Feedback Prize - English Language Learning
9105,106523489,968.0,,15,132,/cdeotte/train-data-contains-mutations-like-test-data,Novozymes Enzyme Stability Prediction
9106,106514902,13.0,,13,149,/dschettler8845/novo-esp-eda-baseline,Novozymes Enzyme Stability Prediction
9107,113659662,56.0,,10,47,/jbomitchell/spearman-correlation-of-public-models,Novozymes Enzyme Stability Prediction
9108,113148819,918.0,,0,0,/aleron751/esmfold-prediction-by-api,Novozymes Enzyme Stability Prediction
9109,106448356,2.0,,1,10,/muhammad4hmed/nes-simple-gru-train,Novozymes Enzyme Stability Prediction
9110,107137898,1065.0,0.234071193638451,21,28,/kaggleqrdl/esm-quick-start-lb237,Novozymes Enzyme Stability Prediction
9111,106644668,940.0,,3,13,/starlighter/novozymes-eda-optimization,Novozymes Enzyme Stability Prediction
9112,111847081,27.0,0.3642740542410159,0,9,/viktorfairuschin/novozymes-deepddg,Novozymes Enzyme Stability Prediction
9113,163318123,334.0,,3,39,/onurrr90/why-novozymes-competition-data-is-updated,Novozymes Enzyme Stability Prediction
9114,116349045,3.0,0.4043596367079313,0,3,/zrongchu/6000-unique-mutation-with-dtm-and-ddg,Novozymes Enzyme Stability Prediction
9115,114493984,898.0,,18,61,/gehallak/nesp-3d-geometry-0-32-lb,Novozymes Enzyme Stability Prediction
9116,110475640,1.0,,2,42,/gyozzza/create-graph-data-from-pdb-files-for-gnn,Novozymes Enzyme Stability Prediction
9117,115983032,318.0,,4,69,/awater1223/fork-deletion-specific-ensemble-python,Novozymes Enzyme Stability Prediction
9118,107060390,268.0,0.4486684461281413,12,54,/oxzplvifi/novozymes-in-r-blosum-deepddg-demask,Novozymes Enzyme Stability Prediction
9119,109754465,271.0,,0,20,/aspiring/nesp-relaxed-rosetta-scores,Novozymes Enzyme Stability Prediction
9120,111337843,836.0,0.5777193233022462,1,3,/crownsss/plddt-ensemble,Novozymes Enzyme Stability Prediction
9121,107782584,273.0,,4,13,/shlomoron/train-wildtypes-af-files-exploration,Novozymes Enzyme Stability Prediction
9122,110040303,197.0,0.3827881238737852,1,13,/geokocha/diving-to-tuning,Novozymes Enzyme Stability Prediction
9123,115718715,253.0,0.6364766234930617,2,14,/songqizhou/private-lb-0-577-ensemble,Novozymes Enzyme Stability Prediction
9124,106604758,11.0,,2,13,/tilii7/prott5-xl-embedding,Novozymes Enzyme Stability Prediction
9125,107646200,921.0,,1,22,/geraseva/dynamut2,Novozymes Enzyme Stability Prediction
9126,114603356,403.0,,0,1,/ystsuji/prediction-by-mutation-information-of-test-data,Novozymes Enzyme Stability Prediction
9127,111696278,845.0,,0,12,/daehunbae/esm-2-pseudo-perplexity-ranking,Novozymes Enzyme Stability Prediction
9128,111557044,838.0,-0.0270211725055804,12,102,/hadeux/lgbm-regressor,Novozymes Enzyme Stability Prediction
9129,111203180,404.0,0.0996341082467878,0,2,/albertwang888/a-quick-use-of-automl,Novozymes Enzyme Stability Prediction
9130,113029525,312.0,0.143414852117766,0,1,/lililycai/fastai-thermonet2,Novozymes Enzyme Stability Prediction
9131,115504258,331.0,0.0254319656024798,0,0,/alekseiartemiev/nesp-scrape-protstab2,Novozymes Enzyme Stability Prediction
9132,137853036,686.0,,10,30,/satyaprakashshukl/novozymes-enzyme-stability-3deda,Novozymes Enzyme Stability Prediction
9133,110573963,553.0,,0,1,/nehapatil1905/xgboost,Novozymes Enzyme Stability Prediction
9134,129103587,515.0,,0,8,/konohayui/enzyme-topic-modeling-and-network-analysis,Novozymes Enzyme Stability Prediction
9135,106277114,575.0,0.0607213628134539,0,10,/hengzheng/nesp-tfidf-ridge-baseline,Novozymes Enzyme Stability Prediction
9136,110502073,569.0,,0,0,/vijurangannavar/novoenzyme-protbert-embedding-eda,Novozymes Enzyme Stability Prediction
9137,115121548,179.0,0.3692499535429211,0,0,/raniahelmy/novo-lgbm-tunning-v6,Novozymes Enzyme Stability Prediction
9138,110752526,597.0,,8,8,/dinowun/eda-simplified-nesp,Novozymes Enzyme Stability Prediction
9139,112872407,649.0,0.0335741107360101,0,5,/analyticsbiotech/simple-randomforestregressor-to-get-started,Novozymes Enzyme Stability Prediction
9140,108165288,685.0,,6,22,/tensorchoko/novozymes-eda-en-jp,Novozymes Enzyme Stability Prediction
9141,112741099,772.0,,1,8,/kunduruanil/nesp-eda,Novozymes Enzyme Stability Prediction
9142,110094657,803.0,0.1021247005240453,3,11,/iliazenin/nesp-fireprotdb-aminoacids-physchem-properties,Novozymes Enzyme Stability Prediction
9143,106395240,843.0,0.0801116104609337,8,48,,Novozymes Enzyme Stability Prediction
9144,106730248,416.0,,2,7,/pjt222/eda-vis-and-prep,Novozymes Enzyme Stability Prediction
9145,111219743,862.0,,0,3,/anuradhabaptagiri/notebook71bbed6701,Novozymes Enzyme Stability Prediction
9146,107043344,262.0,,16,12,/jinyuansun/eda-and-finetune-esm,Novozymes Enzyme Stability Prediction
9147,114901146,872.0,0.0148622426549279,4,21,/arunamenon/novozymes-eda-modelling-protbert-xgboost,Novozymes Enzyme Stability Prediction
9148,114419638,513.0,,4,24,/prachi13/lgbmboostregressor-rmse-score-r2,Novozymes Enzyme Stability Prediction
9149,109865869,531.0,,1,11,/docxian/novozymes-enzyme-stability-let-s-explore,Novozymes Enzyme Stability Prediction
9150,106277079,471.0,0.1067367684740638,6,31,/oscarm524/eda-lightgbm-cv-0-52,Novozymes Enzyme Stability Prediction
9151,114519640,484.0,,0,3,/piyushkushwaha/notebook6168516947,Novozymes Enzyme Stability Prediction
9152,115087595,369.0,0.4617387515924741,0,1,/philippschwarz/combine-all-datasets-nesp-xgboost,Novozymes Enzyme Stability Prediction
9153,115492119,206.0,0.5532299608758131,0,8,/ricopue/nesp-siamese-classification,Novozymes Enzyme Stability Prediction
9154,108939270,995.0,,0,5,/subachev/train-set-infer-99-wild-types-for-4334-rows,Novozymes Enzyme Stability Prediction
9155,109459006,26.0,-0.0375540411886319,2,6,/tanreinama/proteinbert-baseline,Novozymes Enzyme Stability Prediction
9156,106456402,66.0,0.2412245209666177,1,22,/kvigly55/fork-of-nesp-b-factor-nad-subsitutions,Novozymes Enzyme Stability Prediction
9157,106520989,76.0,0.291232137169199,5,13,/chinartist/fork-nesp-an-error-was-corrected,Novozymes Enzyme Stability Prediction
9158,111907670,106.0,-0.0999266990704921,8,33,/bennyfung/novozymes-esp-1-and-2-sequence-protein,Novozymes Enzyme Stability Prediction
9159,115581563,174.0,,1,1,/muhammadkamalabu/enzyme-prediction,Novozymes Enzyme Stability Prediction
9160,106570095,184.0,,18,127,/alejopaullier/nesp-eda-xgboost-baseline-0-025,Novozymes Enzyme Stability Prediction
9161,106661008,230.0,,5,38,/vslaykovsky/nesp-single-mutations-training-set,Novozymes Enzyme Stability Prediction
9162,108084933,990.0,0.139766874758669,1,10,/sgreiner/novo-esp-lstm,Novozymes Enzyme Stability Prediction
9163,106793505,982.0,,5,47,/sayedathar11/novo-esp-groupkfold-linear-regression-baseline,Novozymes Enzyme Stability Prediction
9164,106440908,1018.0,,11,32,/chazzer/eda-visualize-pdb-alphafold-3d-structure,Novozymes Enzyme Stability Prediction
9165,106733338,1301.0,,9,74,/hengck23/lb0-335-deepdgg-server-benchmark,Novozymes Enzyme Stability Prediction
9166,107376234,1089.0,,7,19,/mikhailtsybakov/modification-of-blosum-score-on-deletions,Novozymes Enzyme Stability Prediction
9167,106404734,1080.0,,6,24,/balabaskar/novo-esp-eda-base-model,Novozymes Enzyme Stability Prediction
9168,108262818,1081.0,,0,2,/tbhonest/enzyme-eda,Novozymes Enzyme Stability Prediction
9169,108532989,1164.0,,8,48,/homofaberus/novozymes-data-enrichement,Novozymes Enzyme Stability Prediction
9170,112659029,1161.0,,0,2,/ashokkumargarain/notebookc0c2a36838,Novozymes Enzyme Stability Prediction
9171,107141472,1277.0,,2,12,/tatamikenn/novozymes-eda-on-mutation-in-test-data,Novozymes Enzyme Stability Prediction
9172,113574237,1295.0,,0,6,/amudhagiridharan/r-bioseq-xgboost-kaggle-training-data,Novozymes Enzyme Stability Prediction
9173,107598052,1092.0,,2,6,/kuntalpal/eda-visualization,Novozymes Enzyme Stability Prediction
9174,106266587,1229.0,,4,12,/tscheung/frequency-matrix-lgbmregressor-quick-submission,Novozymes Enzyme Stability Prediction
9175,107130974,1250.0,,0,10,/ganeshborkar31/novo-esp-eli5-performant-approaches-lb-0-425,Novozymes Enzyme Stability Prediction
9176,106361713,1231.0,,2,6,/tayyabali55/enzymes-baseline-model-lightgbm,Novozymes Enzyme Stability Prediction
9177,130633993,1290.0,,0,0,/hiromuhoshina/lightgbm-model,Novozymes Enzyme Stability Prediction
9178,106283849,1395.0,-0.0110659709559228,0,14,/lucasmorin/bag-of-word-lgbm-ensemble,Novozymes Enzyme Stability Prediction
9179,114394915,1343.0,0.3204747054118562,0,3,/saraswatitiwari/novozymes-enzyme-stability-prediction,Novozymes Enzyme Stability Prediction
9180,115259878,1446.0,,0,0,/robbertvang/enzyme-stability,Novozymes Enzyme Stability Prediction
9181,111195387,1361.0,,0,2,/narendra/enzyme-highlevel-eda,Novozymes Enzyme Stability Prediction
9182,113569486,1495.0,,0,2,/llbbllbb2000/123-final,Novozymes Enzyme Stability Prediction
9183,106643161,2436.0,0.2105566581009792,1,11,/rajeshh/location-and-blosum90-substitution-score,Novozymes Enzyme Stability Prediction
9184,120157603,1498.0,,0,5,/acousticmusic/easy-understand-xgboost,Novozymes Enzyme Stability Prediction
9185,106568799,1671.0,0.0084635810148487,0,5,/ishaan45/nesp-domain-feature-engineering-baseline,Novozymes Enzyme Stability Prediction
9186,113596201,1571.0,-0.0325448756969943,4,19,/ris320/novoenzyme-protbert-xgboost,Novozymes Enzyme Stability Prediction
9187,108783824,1606.0,0.1652036202029501,1,7,/tarekferssiwi/enzyme-tm-prediction,Novozymes Enzyme Stability Prediction
9188,111923776,1758.0,0.1571592584505583,6,23,/pragyanbeuria/enzyme-stability-prediction-rand-forest-approch,Novozymes Enzyme Stability Prediction
9189,106964407,1780.0,,4,5,/vibhorsharma111/groupkfold-linear-regression-lb-0-15,Novozymes Enzyme Stability Prediction
9190,110768032,1728.0,,0,0,/leazerep/logarithmic-transformation-skew,Novozymes Enzyme Stability Prediction
9191,112736189,1574.0,,0,16,/darkcore/stability-prediction-w-xgb,Novozymes Enzyme Stability Prediction
9192,161650282,2030.0,,0,15,/aniruddhapa/enzyme-stability-xgboost-baseline-model-0-14,Novozymes Enzyme Stability Prediction
9193,137295138,2353.0,,25,67,/gkitchen/enzyme-stability-prediction,Novozymes Enzyme Stability Prediction
9194,115379413,1709.0,0.0418529728544699,0,0,/nirmalkondreddy/novozyme-enzyme-prediction-using-xgb-and-nn,Novozymes Enzyme Stability Prediction
9195,107129774,2279.0,0.0089782104849152,0,4,/ltrahul/novozymes-enzyme-beginner-approach,Novozymes Enzyme Stability Prediction
9196,115223340,1677.0,,0,0,/vafaknm/enzyme-stability-prediction-with-multi-headed-ann,Novozymes Enzyme Stability Prediction
9197,106422005,1561.0,-0.0855035800979579,0,6,/danofer/enzymes-baseline-with-k-mers,Novozymes Enzyme Stability Prediction
9198,110130771,1996.0,-0.0191883014797209,0,2,/bcantt/correlation-feature-engineering-open-to-improve,Novozymes Enzyme Stability Prediction
9199,109267376,2420.0,,0,0,/tonymathieux/eda-and-groups-of-variants-in-training-dataset,Novozymes Enzyme Stability Prediction
9200,106989229,2121.0,0.0969230421975733,0,5,/mahdeemushfiquekamal/enzyme-stability-prediction,Novozymes Enzyme Stability Prediction
9201,107601375,1538.0,,6,23,/ranamahmud/eda-feature-engineering-and-hyperparameter-tuning,Novozymes Enzyme Stability Prediction
9202,106365269,2169.0,,0,24,/neerajmohan/biological-sequence-modeling-with-k-mer-features,Novozymes Enzyme Stability Prediction
9203,106706856,1440.0,0.0814295721879928,0,2,/timurtalikbayev/novozymes-enzyme-stability-prediction-kaggle,Novozymes Enzyme Stability Prediction
9204,107700634,1909.0,,4,5,/dingyan/novozymes-transformer-encoder-with-tensorflow-tpu,Novozymes Enzyme Stability Prediction
9205,115557360,1626.0,,0,0,/brandontsai99/ai-assingment,Novozymes Enzyme Stability Prediction
9206,107652477,2292.0,0.0513174896657689,2,4,/riteshsinha/comprehensive-eda-on-protein-sequence,Novozymes Enzyme Stability Prediction
9207,106331832,2303.0,,1,5,/hiringfreeze/protein-sequence-encoding,Novozymes Enzyme Stability Prediction
9208,115546213,1674.0,,0,6,/ulrikthygepedersen/novozymes-enzyme-stability-prediction,Novozymes Enzyme Stability Prediction
9209,111831120,1562.0,-0.053076548514999,0,9,/tavoglc/linear-regression-for-enzyme-stability-prediction,Novozymes Enzyme Stability Prediction
9210,113896690,2270.0,,3,10,/truthisneverlinear/deep-eda-of-proteins,Novozymes Enzyme Stability Prediction
9211,109044315,1494.0,,6,24,/wanko123/novoemzime-eda-w-biopython,Novozymes Enzyme Stability Prediction
9212,112921157,1621.0,,0,0,/brachistochron/esp-v1,Novozymes Enzyme Stability Prediction
9213,106294735,2045.0,,0,2,/edwintyh/nesp-starter-eda,Novozymes Enzyme Stability Prediction
9214,107242744,2052.0,-0.0300058688117696,1,6,/xixihaha318/novozymes-enzyme-stability-prediction-with-pytorch,Novozymes Enzyme Stability Prediction
9215,107242744,2052.0,-0.0300058688117696,1,6,/xixihaha318/novozymes-enzyme-stability-prediction-with-pytorch,Novozymes Enzyme Stability Prediction
9216,112692896,2060.0,,0,0,/grantwiersum/protparam-only-baseline-predictions,Novozymes Enzyme Stability Prediction
9217,110410117,1425.0,,6,22,/ahmedmohsen2002/enzyme-stability-prediction-lstm,Novozymes Enzyme Stability Prediction
9218,107584463,2161.0,-0.2575799668221208,8,16,/venkatkumar001/nesp1-baseline-eda-xgb,Novozymes Enzyme Stability Prediction
9219,113559480,2124.0,0.0178753023854237,0,2,/nayerbasim/thermostability-2,Novozymes Enzyme Stability Prediction
9220,111476881,1990.0,0.0164898286530625,9,10,/lordxerxes/my-enzyme-stability-prediction-2,Novozymes Enzyme Stability Prediction
9221,106904341,1798.0,0.0132708258470865,0,0,/tracyporter/novonzymes-kernelridge,Novozymes Enzyme Stability Prediction
9222,118119072,2307.0,,0,7,/suhancho/predict-with-pretrained-embedding-model-by-meta,Novozymes Enzyme Stability Prediction
9223,113527255,2096.0,,0,2,/rachanabisht/novozyme-eda,Novozymes Enzyme Stability Prediction
9224,106310359,2401.0,,13,39,/mpwolke/novozymes-pdb-file,Novozymes Enzyme Stability Prediction
9225,112601280,1955.0,,1,2,/kariim/enzyms,Novozymes Enzyme Stability Prediction
9226,114180561,2380.0,-0.0782509859543546,1,3,/loousmane/pr-diction-de-la-stabilit-des-enzymes-novozymes,Novozymes Enzyme Stability Prediction
9227,108384118,2349.0,,0,1,/biswajit01/novozymes-enzyme-stability-prediction,Novozymes Enzyme Stability Prediction
9228,111431959,2151.0,,0,5,/talhaumar/predict-thermostability-of-enzymes,Novozymes Enzyme Stability Prediction
9229,108390281,3.0,,3,15,/fabianbong/tps-october-2022-keras-tf-neural-network,Tabular Playground Series - Oct 2022
9230,108904741,12.0,,0,5,/cristiansanabria/data-shuffled-and-split-in-10-feather-files,Tabular Playground Series - Oct 2022
9231,108683092,9.0,0.1892689517826241,26,77,/alexryzhkov/tps-2022-10-fastai-with-multistart-and-tta,Tabular Playground Series - Oct 2022
9232,107423842,10.0,0.1919852288582257,28,86,/paddykb/tps-2022-10-fastai,Tabular Playground Series - Oct 2022
9233,107417694,15.0,0.1977576043323927,3,13,/ahmedelfazouan/tabular-playground-catb-inference,Tabular Playground Series - Oct 2022
9234,108949694,44.0,,0,2,/ioanatiriac/oct-22-tabular-simple-lgbm-merge-train-sets,Tabular Playground Series - Oct 2022
9235,109885447,47.0,,49,66,/shariful07/tps-oct-2022-eda-and-ensemble-hybrid-model,Tabular Playground Series - Oct 2022
9236,106941749,40.0,1.7295296966518414,1,12,/kojimar/scoring-1st-submission,Tabular Playground Series - Oct 2022
9237,109502679,68.0,0.1897203776915228,15,31,/viktortaran/tps-oct-2022,Tabular Playground Series - Oct 2022
9238,107369429,80.0,,9,26,/aatiffraz/prediction-by-simulation-lets-play-rocket-league,Tabular Playground Series - Oct 2022
9239,109676191,83.0,,1,6,/arturogranados/dnn-for-tabular-playground-series-oct-2022,Tabular Playground Series - Oct 2022
9240,108548070,87.0,0.1977576043323927,0,3,/saraswatitiwari/tps-oct-2022,Tabular Playground Series - Oct 2022
9241,108911898,93.0,0.2028393346436374,10,24,/alvinleenh/tpsoct22-ctb-online-learning,Tabular Playground Series - Oct 2022
9242,106945919,94.0,1.7295296966518414,0,7,/akshaydattatraykhare/tabular-playground-series-submission,Tabular Playground Series - Oct 2022
9243,107366317,103.0,0.2039952609041004,6,23,/docxian/tps-2022-oct-detailed-exploration,Tabular Playground Series - Oct 2022
9244,107647652,102.0,,0,6,/slythe/tps-oct-22-eda-of-rocket-league,Tabular Playground Series - Oct 2022
9245,106992910,106.0,,0,1,/tueda80/loading-csv-files-by-pyarrow-3x-speedup,Tabular Playground Series - Oct 2022
9246,109676719,111.0,0.1956285248333392,0,0,/kipngetichv/xgboost-on-gpu,Tabular Playground Series - Oct 2022
9247,107595601,114.0,0.1987060237721804,22,90,/chazzer/rocket-league-xgboost-feat-engineering-cv,Tabular Playground Series - Oct 2022
9248,109640966,116.0,,0,3,/josmejagamarra/tps-oct-22-personal-datasets,Tabular Playground Series - Oct 2022
9249,106980945,131.0,,8,19,/cv13j0/tps-oct22-sequential-dataset-loader,Tabular Playground Series - Oct 2022
9250,107442131,140.0,,7,11,/ryancaldwell/cnn-predict-next-frame,Tabular Playground Series - Oct 2022
9251,107988788,144.0,,0,3,/shoooono/oct2022-feature-engineering,Tabular Playground Series - Oct 2022
9252,107107398,142.0,,14,45,,Tabular Playground Series - Oct 2022
9253,109565679,168.0,0.1983680294868277,1,14,/mukaseevru/tps-oct-22-lama-lightautoml-fe-sampling,Tabular Playground Series - Oct 2022
9254,108888273,146.0,,25,85,/infrarosso/tps-oct-2022-eda-hybrid-model-ensemble,Tabular Playground Series - Oct 2022
9255,108936181,147.0,,5,16,/mateuscco/voronoi-diagrams-computing-player-s-influence,Tabular Playground Series - Oct 2022
9256,108846322,152.0,0.1985033285443304,0,1,/kibares/fine-tuning-xgboost-feat-engineering-cv,Tabular Playground Series - Oct 2022
9257,107262352,149.0,,3,9,/wasshoiwasshoi/2022-tps-oct-interactive-graph-of-players-motion,Tabular Playground Series - Oct 2022
9258,108551145,156.0,,21,50,/donatoriccio/how-to-load-21m-rows-in-1-minute-using-2-lines,Tabular Playground Series - Oct 2022
9259,109681910,187.0,0.2051063769005611,3,10,/eavelardev/tps-oct-2022-simple-tf,Tabular Playground Series - Oct 2022
9260,107222300,181.0,,10,13,/princeneo/tabular-series-oct-2022,Tabular Playground Series - Oct 2022
9261,107641780,183.0,0.2630920292162313,22,31,/alexandershumilin/tps-oct-2022-simple-keras-nn,Tabular Playground Series - Oct 2022
9262,107540559,191.0,,0,2,/syedasimalishah/simple-approach,Tabular Playground Series - Oct 2022
9263,107289395,190.0,,1,6,/spyrow/playground-oct-2022-lgbmclassifier,Tabular Playground Series - Oct 2022
9264,107337203,193.0,,1,7,/bayremabdellaoui/xgboost-feat-engineering,Tabular Playground Series - Oct 2022
9265,107385013,224.0,0.2104842466401703,12,29,/sfktrkl/tps-oct-2022,Tabular Playground Series - Oct 2022
9266,106975554,219.0,,4,9,/stautxie/tabular-challenge-oct-2022-eda,Tabular Playground Series - Oct 2022
9267,109963967,222.0,,0,2,/jrreda/tps-oct-2022-21-million-rows-lightgbm,Tabular Playground Series - Oct 2022
9268,109599506,228.0,,1,3,/stark0509/tabular-oct,Tabular Playground Series - Oct 2022
9269,109505506,243.0,,0,0,/dariopaez/tps-oct22-dataset-first-impressions,Tabular Playground Series - Oct 2022
9270,111169982,265.0,,49,64,/landfallmotto/tps-oct-22-continue-training-method-lightgbm,Tabular Playground Series - Oct 2022
9271,107173803,262.0,,1,5,/itspavansatish/3-85gb-tps-oct-2022-pickle-dataset,Tabular Playground Series - Oct 2022
9272,107227484,259.0,0.2023412130137798,7,30,/aieducation/tps-oct-eda-lightgbm,Tabular Playground Series - Oct 2022
9273,108672678,261.0,,2,3,/davidhguerrero/tps1022-hgbregressor-with-optuna,Tabular Playground Series - Oct 2022
9274,109657962,271.0,0.2024771263009625,7,15,/imnaho/tps-oct,Tabular Playground Series - Oct 2022
9275,109245907,276.0,,0,3,/karimrd/tabular-oct-2022-my-second-attempt,Tabular Playground Series - Oct 2022
9276,106954671,285.0,1.723870176225785,0,6,/tracyporter/oct-22-tabular,Tabular Playground Series - Oct 2022
9277,107001288,278.0,,0,2,/gauravduttakiit/team-a-dataframe-creation,Tabular Playground Series - Oct 2022
9278,107341924,284.0,0.217868164129378,0,2,/llllllillllilll/notebookb1fd8f8150,Tabular Playground Series - Oct 2022
9279,108943552,291.0,,0,2,/momenamgad/lgbmclassifier-tps-oct2020,Tabular Playground Series - Oct 2022
9280,108699406,296.0,0.2045947211157922,10,10,/barbagrande007/bbg007-tps-oct,Tabular Playground Series - Oct 2022
9281,107868369,307.0,0.2062077712778042,7,16,/hosseinbehjat/simple-lgbm-for-beginners-tpsoct2022,Tabular Playground Series - Oct 2022
9282,109183804,311.0,,1,6,/majkaf/tbs-oct-2022-rocket-league,Tabular Playground Series - Oct 2022
9283,108933921,312.0,0.2069775400573996,0,1,/vasilikigeorgali/tps-oct22-data-exploration-and-simple-dnn,Tabular Playground Series - Oct 2022
9284,107180977,320.0,0.207699304681618,22,76,,Tabular Playground Series - Oct 2022
9285,108760051,318.0,0.2067567870708579,0,0,/toniju98/rocketleague,Tabular Playground Series - Oct 2022
9286,109227315,328.0,,0,1,/sebastiangonzaleza98/tps-oct-2022-dl,Tabular Playground Series - Oct 2022
9287,107132559,336.0,0.2108737291343755,0,3,/marcuspop/catboost-classifier-incremental-learning-feather,Tabular Playground Series - Oct 2022
9288,107025148,334.0,0.2102092475933449,3,12,/act18l/all-data-pca-mean-impute-logisticregression,Tabular Playground Series - Oct 2022
9289,108466837,339.0,,0,2,/hugolearn/tps-oct-practice,Tabular Playground Series - Oct 2022
9290,109628482,342.0,,5,22,/casati8/kaggle-tps-2022-oct-fastai,Tabular Playground Series - Oct 2022
9291,107438868,349.0,0.2146171805530413,3,10,/abhishek123maurya/score-prediction-using-neural-networks,Tabular Playground Series - Oct 2022
9292,108707071,350.0,0.2235366344590726,21,24,/msayak/tps-oct-22-lgbm-continuous-learning,Tabular Playground Series - Oct 2022
9293,106951797,357.0,0.2182116756021555,12,19,/nigelhenry/single-feature-baseline,Tabular Playground Series - Oct 2022
9294,108813597,360.0,0.2218975406844609,8,25,/tompaulat/can-a-graph-help-classify-player-data,Tabular Playground Series - Oct 2022
9295,106991372,368.0,,18,35,/mpwolke/rocket-loss-league-cosplay,Tabular Playground Series - Oct 2022
9296,107206920,367.0,0.2254492005322637,0,1,/michaeljosephholt/null-information-guess,Tabular Playground Series - Oct 2022
9297,108070430,371.0,0.3367663216100515,1,6,/sgduran/rocket-league,Tabular Playground Series - Oct 2022
9298,109336410,397.0,,1,1,/jebema/notebookedb34b052a,Tabular Playground Series - Oct 2022
9299,108843502,398.0,,0,0,/luisamnh27/tabular-2022-rocket-league,Tabular Playground Series - Oct 2022
9300,109087558,405.0,,2,5,/atrijtalgery/tps10-22-memory-frugal-eda-prediction,Tabular Playground Series - Oct 2022
9301,108937961,411.0,,0,2,/fernandocossio/tf-decision-trees,Tabular Playground Series - Oct 2022
9302,109684386,413.0,0.7028641922646297,1,3,/robertbarak/rocket-league,Tabular Playground Series - Oct 2022
9303,109595825,415.0,,2,10,/tobetek/tps-oct-22-eda-tensorflow-and-a-bit-of,Tabular Playground Series - Oct 2022
9304,107000487,419.0,,0,3,/justinauyeung/tab-challenge-oct22-pca-scree-plot,Tabular Playground Series - Oct 2022
9305,109314500,426.0,,0,6,/kesavsivakumar/select20best-features-stacked-catboost,Tabular Playground Series - Oct 2022
9306,108942584,1.0,0.5571819745895795,25,166,/junkoda/basic-spectrogram-image-classification,G2Net Detecting Continuous Gravitational Waves
9307,115544433,3.0,,0,8,/analokamus/fast-online-noise-generation-3rd-place,G2Net Detecting Continuous Gravitational Waves
9308,115456706,8.0,,0,4,/iiyamaiiyama/g2net-pyfstat-matched-filter,G2Net Detecting Continuous Gravitational Waves
9309,109129313,448.0,,0,2,/zollkron/basic-spectrogram-image-classification-cpu-only,G2Net Detecting Continuous Gravitational Waves
9310,109864907,16.0,,1,10,/josefslavicek/g2net-weird-behavior-of-std-spectrogram,G2Net Detecting Continuous Gravitational Waves
9311,115390667,10.0,0.7809036357619885,0,3,/anonamename/g2net2-sub-avg,G2Net Detecting Continuous Gravitational Waves
9312,111318360,432.0,0.6976551137533077,7,77,/myso1987/g2net-basic-audio-data-augmentation,G2Net Detecting Continuous Gravitational Waves
9313,108423501,21.0,,4,22,/ahmedelfazouan/g2net-prepare-features,G2Net Detecting Continuous Gravitational Waves
9314,112324992,67.0,,0,1,/ingffwe/g2-data-vis,G2Net Detecting Continuous Gravitational Waves
9315,110852871,351.0,0.6613219422722005,2,31,/dragonzhang/g2net-pytorch-with-generated-data,G2Net Detecting Continuous Gravitational Waves
9316,114831365,13.0,0.747076141427764,1,8,/assign/g2net-large-kernel-inference-fft-conv2d,G2Net Detecting Continuous Gravitational Waves
9317,112914671,80.0,,1,7,/igorlitvin/nn-training-of-l-and-h-distorted-g-wave,G2Net Detecting Continuous Gravitational Waves
9318,109514186,35.0,0.6089398148516664,10,29,/masterray/basic-spectrogram-image-classification-v3-gpu,G2Net Detecting Continuous Gravitational Waves
9319,110942933,44.0,,8,44,/yoyobar/a-simple-script-to-generate-gravitational-waves,G2Net Detecting Continuous Gravitational Waves
9320,110635136,104.0,,3,28,/morodertobias/g2net-record-generation,G2Net Detecting Continuous Gravitational Waves
9321,113123188,85.0,,8,31,/neerajanandcoder/g2net-train,G2Net Detecting Continuous Gravitational Waves
9322,112547544,197.0,,8,74,/vslaykovsky/g2net-winning-strategy-with-external-data,G2Net Detecting Continuous Gravitational Waves
9323,108865368,243.0,0.5013520536090962,0,21,/joey0201/g2net-xgb-with-smote-and-enn,G2Net Detecting Continuous Gravitational Waves
9324,112217616,114.0,,0,2,/tfukuda675/g2net-g2n,G2Net Detecting Continuous Gravitational Waves
9325,111191036,266.0,0.7163990798302939,17,41,/leolu1998/g2net-basic-audio-data-augmentation-inference,G2Net Detecting Continuous Gravitational Waves
9326,109369681,307.0,,2,10,/itsuki9180/g2net-create-tfr-spectrogram-datasets,G2Net Detecting Continuous Gravitational Waves
9327,130132738,308.0,,0,1,/pranavkuppa/g2net-image-recognition-final,G2Net Detecting Continuous Gravitational Waves
9328,113551594,249.0,,5,7,/dinowun/eda-simplified-g2net-gravitational-waves,G2Net Detecting Continuous Gravitational Waves
9329,113499277,441.0,,1,2,/kunihikofurugori/g2net-test-datasets-eda,G2Net Detecting Continuous Gravitational Waves
9330,112000383,344.0,0.7493970341242866,14,88,/tanreinama/eliminate-noise-using-signal-similarity,G2Net Detecting Continuous Gravitational Waves
9331,108289201,342.0,,4,18,/viktorcikojevic/waveform-from-sfft,G2Net Detecting Continuous Gravitational Waves
9332,110052152,324.0,,2,36,/kdmitrie/g2net-exporing-test-train-datasets,G2Net Detecting Continuous Gravitational Waves
9333,108312015,430.0,,1,20,/konomuabe/g2net-eda-data-size-span-time-gap,G2Net Detecting Continuous Gravitational Waves
9334,111267004,424.0,0.7485555541657238,31,106,/laeyoung/g2net-large-kernel-inference,G2Net Detecting Continuous Gravitational Waves
9335,108106490,460.0,,0,3,/crischir/giotto-tda-kaggle-adaptation,G2Net Detecting Continuous Gravitational Waves
9336,109083470,470.0,0.5133675914228175,6,32,/willrice/pytorch-lightning-starter,G2Net Detecting Continuous Gravitational Waves
9337,108994326,477.0,0.5127097587795356,0,8,/aspiring/g2net-lgbm-with-smote-and-enn,G2Net Detecting Continuous Gravitational Waves
9338,115043543,499.0,,0,4,/kirillka95/gen-grav-wave-sign,G2Net Detecting Continuous Gravitational Waves
9339,114309956,504.0,0.707030792480808,0,3,/namelessfairy/rules-of-nature,G2Net Detecting Continuous Gravitational Waves
9340,107337443,531.0,,0,17,/markwijkhuizen/g2net-eda-360x360-dataset-creation,G2Net Detecting Continuous Gravitational Waves
9341,108476058,513.0,,0,0,/duyanhphilippepham/getting-started-and-run-withou-ram-memory-overflow,G2Net Detecting Continuous Gravitational Waves
9342,110572402,500.0,,0,2,/bibhabasumohapatra/1-labeled-dataset-is-it-true,G2Net Detecting Continuous Gravitational Waves
9343,120744416,528.0,,1,1,/reboot2h/g2net,G2Net Detecting Continuous Gravitational Waves
9344,111676517,542.0,0.6838139055700287,0,1,/saraswatitiwari/g2net-detecting-continuous-gravitational-waves,G2Net Detecting Continuous Gravitational Waves
9345,110356598,651.0,,0,1,/robber19/g2net-efficeientnet-coatnet-train,G2Net Detecting Continuous Gravitational Waves
9346,112228946,667.0,,0,1,/fuchengdong1/g2net-record-generation,G2Net Detecting Continuous Gravitational Waves
9347,109472952,692.0,0.5966075849184048,0,5,/prem113/basic-spectrogram-image-classification-v2,G2Net Detecting Continuous Gravitational Waves
9348,115399396,757.0,,0,1,/albertozorzetto/g2net,G2Net Detecting Continuous Gravitational Waves
9349,115309918,795.0,0.503655320711892,0,1,/samanthahassal/continuous-gravitational-waves,G2Net Detecting Continuous Gravitational Waves
9350,111439976,781.0,,0,7,/mb16biswas/92-accuracy-end-to-end-implementation-by-sk-learn,G2Net Detecting Continuous Gravitational Waves
9351,115950407,832.0,,0,2,/sumamallapragada/gravdet,G2Net Detecting Continuous Gravitational Waves
9352,109339389,815.0,0.5013520536090962,2,6,/pollicio/gravitacion-chile-ale-cuevas-22,G2Net Detecting Continuous Gravitational Waves
9353,113683434,787.0,0.5005554904861593,1,4,/anantgupt/g2net-ensemble,G2Net Detecting Continuous Gravitational Waves
9354,107874459,826.0,0.5021349711110833,0,6,/opanichev/g2net-metadata-check,G2Net Detecting Continuous Gravitational Waves
9355,107467319,842.0,,15,151,/edwardcrookenden/g2net-getting-started-eda,G2Net Detecting Continuous Gravitational Waves
9356,107206784,829.0,,7,39,/chazzer/how-to-read-the-hdf5-files,G2Net Detecting Continuous Gravitational Waves
9357,108725478,886.0,,0,1,/panjisatria/g2net,G2Net Detecting Continuous Gravitational Waves
9358,110591827,895.0,,0,0,/sofyantandungan/g2net-continuous-gravitational-waves-detection,G2Net Detecting Continuous Gravitational Waves
9359,113881150,47.0,189.984886414822,5,10,/thomasdubail/scrabble-elo-pred,Scrabble Player Rating
9360,114907700,66.0,,0,0,/exuan102345/ntust-scrabble-player-rating,Scrabble Player Rating
9361,113658395,99.0,110.971084415916,0,0,/leesstephanie/kaggle-scrabble,Scrabble Player Rating
9362,113894154,97.0,112.42894288162432,0,1,/aitorporcel/autml-fe,Scrabble Player Rating
9363,113550967,101.0,,0,0,/suzusho/ds-ai-eda-sample,Scrabble Player Rating
9364,113945344,108.0,,2,5,/brunosoaresdossantos/lb-117-26-scrabble-player-rating,Scrabble Player Rating
9365,112965203,119.0,,0,1,/gahyun12j/scrabble-player-rating-xgboost,Scrabble Player Rating
9366,113360832,139.0,,0,1,/greegtitan/scribblebli-bubli,Scrabble Player Rating
9367,113679638,172.0,,0,1,/yyonakamura/ds-ai-scrabbling-with-baseline-models,Scrabble Player Rating
9368,112766023,188.0,,0,0,/jotarostar/xgboost-regressin-apprach,Scrabble Player Rating
9369,113827943,197.0,160.30146770327607,1,8,/elillaarcher/linear-regressor-with-pytorch,Scrabble Player Rating
9370,109920549,200.0,157.39259126203606,5,4,/fanwuuk/scrabble-rating-prediction-fe-evaluation,Scrabble Player Rating
9371,110796338,211.0,174.60622964026348,2,10,/mikepenkov/rating-scrabble-players-with-xgb-regression,Scrabble Player Rating
9372,112617728,212.0,,3,10,/dinowun/eda-simplified-scrabble-player-rating,Scrabble Player Rating
9373,113944198,221.0,,0,0,/zahrizhalali/scrabble-player-rating,Scrabble Player Rating
9374,112995109,229.0,172.25772893240966,0,6,/saraswatitiwari/scrabble-player-rating,Scrabble Player Rating
9375,113878378,241.0,180.58511433279736,0,0,/kavinsubramani/scrabble-player-rating-and-it-works,Scrabble Player Rating
9376,113856078,253.0,,0,1,/elwerno/linearregression,Scrabble Player Rating
9377,113486912,259.0,,0,0,/adrielnaranjo/scrabble-ratings-with-xgb,Scrabble Player Rating
9378,128309123,274.0,,10,21,/akershishukla/scrabble-player-rating-fe-eda,Scrabble Player Rating
9379,110444219,283.0,,16,31,/ahmedgeka/scrabble-game-prediction,Scrabble Player Rating
9380,110786454,286.0,,5,7,/venkatkumar001/scrabble-player-rating-baseline-xgb,Scrabble Player Rating
9381,112268814,80.0,,17,68,/sergiosaharovskiy/tps-nov-2022-in-automl-we-trust,Tabular Playground Series - Nov 2022
9382,109854536,334.0,,0,9,/satyaprakashshukl/fast-loading-high-compression-with-feather,Tabular Playground Series - Nov 2022
9383,109873749,1.0,,2,17,/samuelcortinhas/tps-nov-22-save-to-parquet,Tabular Playground Series - Nov 2022
9384,110235511,322.0,0.5150200530986392,12,28,/pourchot/stacking-with-scipy-minimize,Tabular Playground Series - Nov 2022
9385,110235511,322.0,0.5156849912361158,12,28,/pourchot/stacking-with-scipy-minimize,Tabular Playground Series - Nov 2022
9386,112104618,79.0,,17,76,/infrarosso/tps-nov-2022-eda-hybrid-stacking,Tabular Playground Series - Nov 2022
9387,110018550,31.0,,0,17,/phongnguyen1/analyze-visualize-submissions,Tabular Playground Series - Nov 2022
9388,112370671,13.0,0.5540490842154913,8,22,/mehrankazeminia/1-tps22nov-pseudo-genetic-algorithm,Tabular Playground Series - Nov 2022
9389,110493616,52.0,,0,1,/jaloeffe92/tps-nov-2022-lgb-pipeline,Tabular Playground Series - Nov 2022
9390,112467781,65.0,,2,0,/arturogranados/nn-for-tabularplaygroundseries-nov-2022,Tabular Playground Series - Nov 2022
9391,109764903,46.0,0.5174348279169558,6,17,/alexryzhkov/lightautoml-stacks-your-subs,Tabular Playground Series - Nov 2022
9392,109760783,86.0,0.5191574650037467,2,12,/craigmthomas/tps-nov-2022-catboost-starter,Tabular Playground Series - Nov 2022
9393,109760783,86.0,0.5191574650037467,2,12,/craigmthomas/tps-nov-2022-catboost-starter,Tabular Playground Series - Nov 2022
9394,111413612,70.0,,3,17,/lucasmorin/tps-nov-2022-umap-model-embedding,Tabular Playground Series - Nov 2022
9395,110027679,87.0,,0,7,/prajwalsood/keras-transformer,Tabular Playground Series - Nov 2022
9396,109806680,34.0,,4,25,/hasanbasriakcay/tpsnov22-mean-methods-comparisons,Tabular Playground Series - Nov 2022
9397,112439467,85.0,0.5139674944495188,17,61,/mikhailkuz/lightautoml-nn-happiness,Tabular Playground Series - Nov 2022
9398,110739937,102.0,,0,1,/carlosprez/tps-nov-2022-carlos-p-rez,Tabular Playground Series - Nov 2022
9399,111538212,7.0,,0,2,/mpware/tps-null-importances-fe,Tabular Playground Series - Nov 2022
9400,110187464,16.0,0.5186992377781292,1,18,/pietromaldini1/experiments-with-bias,Tabular Playground Series - Nov 2022
9401,109769209,100.0,0.5179754012204617,4,18,/oscarm524/tps-nov-2022-fs-baseline,Tabular Playground Series - Nov 2022
9402,112504779,128.0,0.5145451050894456,5,17,/viktortaran/tps-nov-2022,Tabular Playground Series - Nov 2022
9403,112504779,128.0,0.5145889969942495,5,17,/viktortaran/tps-nov-2022,Tabular Playground Series - Nov 2022
9404,111625849,97.0,,1,14,/slythe/lightgbm-template-meta-modelling,Tabular Playground Series - Nov 2022
9405,109943230,121.0,0.5180302763942614,1,5,/demko1/tps-nov-2022-handling-incorrect-values,Tabular Playground Series - Nov 2022
9406,109873764,141.0,,0,3,/robinbarbarino/linear-combinations-of-submissions,Tabular Playground Series - Nov 2022
9407,109892002,153.0,,0,4,/jasonczh/tps-nov22-lgbm-simple-feature-engineering-baseline,Tabular Playground Series - Nov 2022
9408,112936101,221.0,0.516156720014371,2,10,/adnanshikh/tps-nov22-hybrid-stacking,Tabular Playground Series - Nov 2022
9409,112934930,120.0,,16,38,/bennyfung/tps-nov-ensemble-by-voting,Tabular Playground Series - Nov 2022
9410,109709926,137.0,,4,15,/alexandershumilin/tps-nov-2022-simple-baseline,Tabular Playground Series - Nov 2022
9411,110765134,184.0,,7,19,/thierryneusius/tps-202211-pls-da-and-logisticregression-model,Tabular Playground Series - Nov 2022
9412,109907912,150.0,0.5173900239723375,0,12,/donatoriccio/tps-nov22-lgbm-w-binarized-features,Tabular Playground Series - Nov 2022
9413,109695810,131.0,0.6035303280579665,2,11,/ehekatlact/tps2211-use-top100,Tabular Playground Series - Nov 2022
9414,109878868,233.0,,0,9,/albertventura/tpsnov-l1-regularization-for-feature-selection,Tabular Playground Series - Nov 2022
9415,110399489,122.0,0.5177209329309451,4,9,/leonliur/automl-starter-baseline-0-51772,Tabular Playground Series - Nov 2022
9416,111736670,215.0,0.519139619458548,0,8,/giancarlomarcolin/tps-nov22-gm,Tabular Playground Series - Nov 2022
9417,110739132,274.0,,4,11,/mvortizr/nov-22-tps-eda-lightgbm,Tabular Playground Series - Nov 2022
9418,110330271,222.0,0.5270754882469058,0,3,/jamiedonaldmccann/icg-dsc-tbs1122,Tabular Playground Series - Nov 2022
9419,111740715,293.0,0.5173797078040291,0,3,/leehann/ds-baseline,Tabular Playground Series - Nov 2022
9420,110132325,229.0,0.5658114068320687,0,3,/stpeteishii/tps1122-select-2-optuna-blend,Tabular Playground Series - Nov 2022
9421,110267214,266.0,,0,3,/gauravduttakiit/tps-nov-2022-dataset-creation,Tabular Playground Series - Nov 2022
9422,109706210,251.0,,0,4,/sayantansadhu/blend-of-all-submission-file,Tabular Playground Series - Nov 2022
9423,112380052,166.0,0.5698936148357784,0,2,/simonedegasperis/ensemble-selection,Tabular Playground Series - Nov 2022
9424,112318329,316.0,,0,3,/parijatkumar2003/nov-22-playground,Tabular Playground Series - Nov 2022
9425,111757410,246.0,0.518350541608935,0,5,/barbagrande007/bbg-007-tp-nov,Tabular Playground Series - Nov 2022
9426,110618152,321.0,0.518367503765851,0,2,/eduus710/tps-nov22-saved-logit-shift-calibrations,Tabular Playground Series - Nov 2022
9427,111395959,273.0,0.5183928109725281,2,7,/askeeee/lgbm-base-line-tps-nov-2022,Tabular Playground Series - Nov 2022
9428,110490757,355.0,0.5286097317905983,1,6,/colemankrawczyk/explore-blending-data,Tabular Playground Series - Nov 2022
9429,110626123,283.0,0.52003268995738,2,25,/piyushjain16/november-challenge,Tabular Playground Series - Nov 2022
9430,115995153,344.0,,3,7,/viliuspstininkas/feature-selection-methods-pca,Tabular Playground Series - Nov 2022
9431,109714411,329.0,,1,8,/senkmp/tsne-umap-on-tps-nov22-interesting-data-viz,Tabular Playground Series - Nov 2022
9432,111121617,400.0,0.5202719802384131,1,13,/yuseidoi/simple-blending-with-xgboost-and-lightgbm,Tabular Playground Series - Nov 2022
9433,110340132,335.0,,0,1,/carolinamejamujica/playground-november,Tabular Playground Series - Nov 2022
9434,112362040,384.0,0.5275492727646196,2,10,/analyticsbiotech/simple-pca-logistic-random-forest,Tabular Playground Series - Nov 2022
9435,111376705,395.0,0.5537676638384826,2,9,/casati8/kaggle-tps-2022-nov-fastai,Tabular Playground Series - Nov 2022
9436,110708275,380.0,0.5236295726340225,1,6,/prem113/tps-nov-2022,Tabular Playground Series - Nov 2022
9437,111356670,386.0,0.5941507337910632,3,20,/matinkarimpour/tps-nov-2022-conv1d-keras-and-kfold,Tabular Playground Series - Nov 2022
9438,109935610,375.0,0.5239331135146007,1,8,/hosseinbehjat/simple-lgbm-for-beginners-tpsnov2022,Tabular Playground Series - Nov 2022
9439,110019755,411.0,0.5289124218921707,0,9,/chazzer/top-performers-pca-cv-xgb-stacking,Tabular Playground Series - Nov 2022
9440,110286701,403.0,0.5246952268092179,0,5,/nnjjpp/stacking-with-pca-and-a-logistic-regression,Tabular Playground Series - Nov 2022
9441,112206052,368.0,,0,1,/arslanemed/simple-blending-with-xgboost-1st-try,Tabular Playground Series - Nov 2022
9442,110874034,410.0,,0,3,/shudhatmajain/complete-data-collation-to-single-dataframe,Tabular Playground Series - Nov 2022
9443,111475753,443.0,,2,9,/hugolearn/tps-nov-practice-ensemble-learning,Tabular Playground Series - Nov 2022
9444,111813925,416.0,0.5538916411927364,11,22,/sanjaylalwani/tps-nov-22,Tabular Playground Series - Nov 2022
9445,110774610,457.0,,0,2,/rudeparkeet/simple-blending-example,Tabular Playground Series - Nov 2022
9446,110415602,447.0,0.5274885643488385,2,11,/georgedwatson/tabular-playground-series-nov-2022,Tabular Playground Series - Nov 2022
9447,110216498,490.0,,0,2,/afsheinkeshmiri/tabular-playground-nov-2022,Tabular Playground Series - Nov 2022
9448,110550062,446.0,,0,1,/ludelaire/dnn-with-outliers-preprocessing,Tabular Playground Series - Nov 2022
9449,110242436,469.0,,2,9,/cv13j0/tps-nov2022-beginner-lr-to-gdbt,Tabular Playground Series - Nov 2022
9450,110170937,481.0,0.5631211982062824,0,3,/abhishek123maurya/tpsnov-catboost-and-pca,Tabular Playground Series - Nov 2022
9451,110170937,481.0,0.6337314566502595,0,3,/abhishek123maurya/tpsnov-catboost-and-pca,Tabular Playground Series - Nov 2022
9452,110668300,484.0,0.529580874796366,0,1,/tracygranados/notebookbcc2d17e9b,Tabular Playground Series - Nov 2022
9453,110429720,480.0,0.5296241115325473,0,6,/sgduran/tps-nov-2022-simple-nn-for-blending-prediction,Tabular Playground Series - Nov 2022
9454,111005122,492.0,,1,1,/majkaf/tbs-nov22-pca-clf-models,Tabular Playground Series - Nov 2022
9455,112130067,524.0,,12,22,/francescoliveras/tps-nov-2022-en-es,Tabular Playground Series - Nov 2022
9456,110661884,517.0,,0,1,/mariangelreyes/kaggle-november-ipynb,Tabular Playground Series - Nov 2022
9457,110256273,530.0,0.5587972165462074,0,1,/tonantzinrealrojas/optuna-and-lightgbm,Tabular Playground Series - Nov 2022
9458,111878306,545.0,,4,9,/davidhguerrero/feature-importance-with-lgbmclassifier,Tabular Playground Series - Nov 2022
9459,110885599,551.0,0.5839043829712824,1,10,/jiprud/tps-nov-22-rookie-submission-xgboost,Tabular Playground Series - Nov 2022
9460,111933755,553.0,0.598417383962322,2,5,/pohzixiang/nov-playground-submission-zx,Tabular Playground Series - Nov 2022
9461,110002266,562.0,,0,1,/llllllillllilll/notebookf0ddc6e3c5,Tabular Playground Series - Nov 2022
9462,109724668,576.0,,0,3,/tracyporter/nov-22-blending,Tabular Playground Series - Nov 2022
9463,111067560,578.0,0.5984924484841233,2,13,/mridulsyed/tbs-nov-2022,Tabular Playground Series - Nov 2022
9464,111343606,616.0,0.8225214343673349,0,4,/minhduc123/simple-blending,Tabular Playground Series - Nov 2022
9465,109781812,647.0,,0,7,/griffenthoma/tps-nov-22-first-steps,Tabular Playground Series - Nov 2022
9466,111979057,663.0,0.7167558748969765,4,8,/baslealabera/blending-with-convolutional-neural-network,Tabular Playground Series - Nov 2022
9467,111979057,663.0,0.7167558748969765,4,8,/baslealabera/blending-with-convolutional-neural-network,Tabular Playground Series - Nov 2022
9468,112276416,676.0,1.498653708709157,1,7,/eduardschipatecua/tpsnov22,Tabular Playground Series - Nov 2022
9469,110626332,680.0,,0,1,/gabrielaholzel/xgboost-predictions,Tabular Playground Series - Nov 2022
9470,112477673,686.0,,0,0,/bhaktipatil25/tpsnov2022-e,Tabular Playground Series - Nov 2022
9471,113996838,3.0,,1,29,/titericz/dask-cudf-example,OTTO – Multi-Objective Recommender System
9472,110876199,4.0,0.5749183758705907,8,119,/carnozhao/otto-fast-cpu-end-to-end-pipeline,OTTO – Multi-Objective Recommender System
9473,117115540,18.0,,5,60,/greenwolf/lightgbm-fast-recall-20,OTTO – Multi-Objective Recommender System
9474,114378743,25.0,0.4967243030530965,15,106,/yamsam/recbole-gru4rec-sample-code,OTTO – Multi-Objective Recommender System
9475,110119841,28.0,,2,33,/gunesevitan/otto-multi-objective-recommender-system-pickle,OTTO – Multi-Objective Recommender System
9476,112900379,38.0,,0,1,/ranchantan/otto-train-test-event,OTTO – Multi-Objective Recommender System
9477,114136523,70.0,0.5716865828343206,8,66,/pietromaldini1/multiple-clicks-vs-latest-items,OTTO – Multi-Objective Recommender System
9478,111667650,114.0,,0,38,/parthpankajtiwary/otto-eda-understanding-users-and-events,OTTO – Multi-Objective Recommender System
9479,114107176,109.0,0.0635179505956061,0,0,/itong1900/similary-scores-baseline,OTTO – Multi-Objective Recommender System
9480,115647897,116.0,0.5749420239768224,0,9,/chaudharypriyanshu/pandarallel-speedup-chris-approach-4x-times,OTTO – Multi-Objective Recommender System
9481,119728860,163.0,,0,1,/huyduong7101/otto-eda-whole-set,OTTO – Multi-Objective Recommender System
9482,111479366,180.0,,1,2,/rayanaay/popularity-based-recommendation,OTTO – Multi-Objective Recommender System
9483,111211189,192.0,0.5468804431456551,0,3,/alexz0/fast-co-visitation-performance,OTTO – Multi-Objective Recommender System
9484,125120781,194.0,,0,0,/tashiget/pytorch,OTTO – Multi-Objective Recommender System
9485,117879737,201.0,,0,8,/himanshunayal/no-ml-public-lb-0-579-priv-lb-0-578,OTTO – Multi-Objective Recommender System
9486,116951969,225.0,,2,9,/balaganiarz0/word2vec-model-local-validation,OTTO – Multi-Objective Recommender System
9487,118209980,226.0,,0,1,/hoangnguyen719/otto-tr-matrixv2-tail40-top404050-w136,OTTO – Multi-Objective Recommender System
9488,109828359,321.0,,0,7,/takaito/otto-topic-model-tutorial,OTTO – Multi-Objective Recommender System
9489,112871515,255.0,0.5532877977893058,0,0,/jamesyiao/baseline,OTTO – Multi-Objective Recommender System
9490,117028705,245.0,0.4867776157773751,0,3,/cafelatte1/otto-re-rank-history-items,OTTO – Multi-Objective Recommender System
9491,116912128,421.0,,0,0,/ekity1002/word2vec-tsne,OTTO – Multi-Objective Recommender System
9492,115223999,511.0,0.5176566125434494,0,2,/kuangshiai/itemcf-with-original-data,OTTO – Multi-Objective Recommender System
9493,114320901,526.0,,0,2,/hokkey/candidate-rerank-model-add-eda-lb075,OTTO – Multi-Objective Recommender System
9494,110014083,305.0,,0,10,/satyaprakashshukl/json-to-csv-file,OTTO – Multi-Objective Recommender System
9495,111942635,396.0,,0,6,/kooaslansefat/proof-of-concept-catboost-ranker,OTTO – Multi-Objective Recommender System
9496,114645536,530.0,,0,5,/baladevdebasisjena/otto-polars-light-jsonl-to-paraquest-conversion,OTTO – Multi-Objective Recommender System
9497,110029333,732.0,,4,39,/snnclsr/transformers4rec-synthetic-data-example,OTTO – Multi-Objective Recommender System
9498,112470061,758.0,0.5767244392720404,8,95,/tuongkhang/otto-pipeline2-lb-0-576,OTTO – Multi-Objective Recommender System
9499,115130120,425.0,0.4829706407980085,0,8,/bechirkarmeni/otto-multi-objective-recommender-system,OTTO – Multi-Objective Recommender System
9500,113551650,651.0,,10,43,/alberteinsten/cudf-pandas-proof-of-concept-lgbm-ranker,OTTO – Multi-Objective Recommender System
9501,111570458,515.0,,0,3,/pyagoubi/behavioural-patterns,OTTO – Multi-Objective Recommender System
9502,115852321,699.0,,6,40,/alexlods/candidate-generation-lgbm-ranker-model,OTTO – Multi-Objective Recommender System
9503,114400645,617.0,,0,0,/guanghan/train-test-split-feature-generate,OTTO – Multi-Objective Recommender System
9504,115698017,477.0,,0,1,/muddywaters23/matrix-factorization-with-pytorch,OTTO – Multi-Objective Recommender System
9505,114923481,333.0,,0,13,/fooqoo/create-the-features-for-ranker-model,OTTO – Multi-Objective Recommender System
9506,115149514,863.0,0.5770257933286382,18,128,/utm529fg/otto-tuning-candidate-rerank-model-lb-0-577,OTTO – Multi-Objective Recommender System
9507,113992794,291.0,,1,5,/simonveitner/eda-find-promoted-products,OTTO – Multi-Objective Recommender System
9508,114190120,348.0,,1,7,/shunhiramatsu/otto-en,OTTO – Multi-Objective Recommender System
9509,113442840,584.0,,2,11,/seholee/memory-management-techniques-for-beginners,OTTO – Multi-Objective Recommender System
9510,111443065,355.0,0.4827266656979154,0,0,/realstay/otto-getting-started-eda-baseline,OTTO – Multi-Objective Recommender System
9511,115104771,1272.0,,3,20,/duuuscha/train-submit-word2vec-optimized-hparams,OTTO – Multi-Objective Recommender System
9512,111993342,586.0,,2,21,/adaubas/otto-interesting-times-series-eda-on-products,OTTO – Multi-Objective Recommender System
9513,113033387,824.0,,0,0,/biubiug/carts-and-orders-follow-clicks,OTTO – Multi-Objective Recommender System
9514,111242314,788.0,0.5753558839735017,1,3,/joydeep69/candidate-rerank-model-lb-0-574,OTTO – Multi-Objective Recommender System
9515,132920784,627.0,,0,3,/duyanhtran/candidate-rerank-model-lb-0-577-tuned,OTTO – Multi-Objective Recommender System
9516,112576521,861.0,,0,5,/ryumei/otto-eda,OTTO – Multi-Objective Recommender System
9517,118065119,1066.0,,0,0,/fotoizzet/proof-of-concept-markov-decision-process,OTTO – Multi-Objective Recommender System
9518,110403726,872.0,0.5635263885614815,1,9,/andreyzotov/way-to-blend-different-subs,OTTO – Multi-Objective Recommender System
9519,112875688,938.0,,2,5,/mizuny/otto-eda-notebook,OTTO – Multi-Objective Recommender System
9520,117126326,960.0,,0,0,/serjhenrique/otto-item-interaction-cupy-sparse-matrix,OTTO – Multi-Objective Recommender System
9521,115102324,1366.0,,0,0,/shotanakanokaggle/nakano-model4,OTTO – Multi-Objective Recommender System
9522,119253333,867.0,,0,0,/pavelmalykh/otto-fast-baseline-improved,OTTO – Multi-Objective Recommender System
9523,115579279,1053.0,,0,0,/yangchengchun/otto-pipeline2-lb-0-576-08ba9f,OTTO – Multi-Objective Recommender System
9524,112282523,1182.0,,1,6,/royalstag/data-preprocessing-with-pyspark,OTTO – Multi-Objective Recommender System
9525,113929873,1074.0,,0,0,/leloune/transformer,OTTO – Multi-Objective Recommender System
9526,113408034,1144.0,,0,0,/hdong5/eda-based-on-whole-dataset-continue-updating,OTTO – Multi-Objective Recommender System
9527,111331520,1151.0,,0,18,/cocoshe/itemcf-with-item-item-similarity-matrix,OTTO – Multi-Objective Recommender System
9528,109923828,1044.0,0.5230491739915949,2,41,/whitelily/co-occurrence-baseline,OTTO – Multi-Objective Recommender System
9529,109923828,1044.0,0.5230491739915949,2,41,/whitelily/co-occurrence-baseline,OTTO – Multi-Objective Recommender System
9530,111057363,1180.0,,0,7,/tatamikenn/otto-eda-over-sessions,OTTO – Multi-Objective Recommender System
9531,114219824,1202.0,0.5527133092624907,0,2,/shengzn/notebook-szn-otto,OTTO – Multi-Objective Recommender System
9532,112147295,1224.0,,2,28,/jsmithperera/chris-deotte-s-rr-suggest-carts-65-0-575,OTTO – Multi-Objective Recommender System
9533,113692888,1256.0,0.5756791762562372,0,5,/saraswatitiwari/otto-multi-objective-recommender-system,OTTO – Multi-Objective Recommender System
9534,110364232,1807.0,0.5582220877100071,7,30,/dpalbrecht/fast-co-visitation-matrix,OTTO – Multi-Objective Recommender System
9535,109791214,1782.0,,2,6,/hlgdatascience/reading-the-json-lines-input,OTTO – Multi-Objective Recommender System
9536,113275295,1548.0,,14,110,/cpmpml/matrix-factorization-with-gpu,OTTO – Multi-Objective Recommender System
9537,114782647,1373.0,,0,0,/chaoheng/notebook-szn-otto,OTTO – Multi-Objective Recommender System
9538,111059173,1722.0,,0,1,/kanygin/fast-way-to-convert-jsonl-parquet,OTTO – Multi-Objective Recommender System
9539,110507490,1290.0,,2,14,/growbigger/code-explanation-of-0-570-notebook,OTTO – Multi-Objective Recommender System
9540,113744096,1634.0,,4,20,/gabrielvinicius/otto-a-dip-in-the-data,OTTO – Multi-Objective Recommender System
9541,111143512,1572.0,0.5749183758705907,1,24,/rahanapa/otto-recommender,OTTO – Multi-Objective Recommender System
9542,111143512,1572.0,0.5749183758705907,1,24,/rahanapa/otto-recommender,OTTO – Multi-Objective Recommender System
9543,109851939,1579.0,,7,14,/xxxxyyyy80008/otto-multi-objective-recommender-system-eda,OTTO – Multi-Objective Recommender System
9544,112227398,1588.0,,0,9,/alexandershumilin/otto-baseline,OTTO – Multi-Objective Recommender System
9545,114135040,1612.0,0.5749183758705907,0,0,/siaoxie/otto-train-and-test,OTTO – Multi-Objective Recommender System
9546,115270182,1626.0,,0,0,/millak/understand-basic-merging,OTTO – Multi-Objective Recommender System
9547,114718327,1560.0,,0,1,/cabbage972/otto-fast-local-cv-score-with-polars,OTTO – Multi-Objective Recommender System
9548,109781928,1688.0,0.4829706407980085,1,58,/ttahara/otto-mors-aid-frequency-baseline,OTTO – Multi-Objective Recommender System
9549,110446007,1695.0,0.5706488024924574,4,56,/ingvarasgalinskas/item-type-vs-multiple-clicks-vs-latest-items,OTTO – Multi-Objective Recommender System
9550,110479556,1697.0,0.5706488024924574,1,11,/ashishmotwani/type-vs-clicks-vs-latest-items,OTTO – Multi-Objective Recommender System
9551,112933212,1749.0,,2,10,/enizzzz/otto-transformers,OTTO – Multi-Objective Recommender System
9552,112789058,1809.0,,0,2,/krivonogov/otto-generate-cv-split-dataset,OTTO – Multi-Objective Recommender System
9553,114308273,1834.0,0.5176566125434494,2,16,/s107304004/itemcf,OTTO – Multi-Objective Recommender System
9554,113338568,1832.0,0.5532416626512021,2,3,/littlezombie/otto-fast-baseline,OTTO – Multi-Objective Recommender System
9555,110008312,1890.0,0.5428271088018652,27,337,/vslaykovsky/co-visitation-matrix,OTTO – Multi-Objective Recommender System
9556,109919757,1896.0,,0,5,/nemo43/otto-is-it-sale-eda,OTTO – Multi-Objective Recommender System
9557,110006402,1901.0,0.5227619301099536,7,14,/tomooinubushi/test-dataset-is-all-we-need,OTTO – Multi-Objective Recommender System
9558,110006402,1901.0,0.5227619301099536,7,14,/tomooinubushi/test-dataset-is-all-we-need,OTTO – Multi-Objective Recommender System
9559,116464576,1961.0,,0,2,/vinitkp/otto-multi-objective-recommender-system,OTTO – Multi-Objective Recommender System
9560,113132893,1996.0,,0,0,/medmongibenyaiche/otto-word2vec-tutorial,OTTO – Multi-Objective Recommender System
9561,117881325,2007.0,,0,0,/corneliuskristianto/otto-fast-dataframe-loading-in-parquet-format,OTTO – Multi-Objective Recommender System
9562,115837738,2008.0,,0,0,/narendra/item2vec-gpu-train,OTTO – Multi-Objective Recommender System
9563,115418162,2032.0,0.5104731869730524,3,18,/francescoliveras/otto-mors,OTTO – Multi-Objective Recommender System
9564,114903915,2034.0,0.4863559027735662,0,1,/vitkishloh228/notebookec27a76de7,OTTO – Multi-Objective Recommender System
9565,114903915,2034.0,0.4863559027735662,0,1,/vitkishloh228/notebookec27a76de7,OTTO – Multi-Objective Recommender System
9566,109915462,2028.0,,7,29,/konradb/dataset-as-df,OTTO – Multi-Objective Recommender System
9567,114596202,2058.0,0.5012990331006866,1,26,/digvijayyadav/otto-collaborative-recommender-system,OTTO – Multi-Objective Recommender System
9568,113482114,2089.0,,0,1,/kevintakano/deep-matrix-factorization,OTTO – Multi-Objective Recommender System
9569,109793998,2096.0,,3,77,/columbia2131/otto-read-a-chunk-of-jsonl-to-manageable-df,OTTO – Multi-Objective Recommender System
9570,114315844,2104.0,,0,3,/ikogias/pre-process-with-pyspark-into-parquet,OTTO – Multi-Objective Recommender System
9571,115074519,2112.0,0.460945597070604,1,12,/sbunzini/user-item-collaborative-filtering-ensemble,OTTO – Multi-Objective Recommender System
9572,116237529,2142.0,0.4834913675375388,0,7,/sashanktalakola/multi-objective-recommender-system,OTTO – Multi-Objective Recommender System
9573,114905156,2231.0,0.4822370817061728,0,14,/noir3747/first-attempt-with-xgboost-variant,OTTO – Multi-Objective Recommender System
9574,110307646,2213.0,0.4829706407980085,0,11,/ridwanultanvir/otto-transformers4rec-recommender,OTTO – Multi-Objective Recommender System
9575,114346061,2143.0,,33,321,/edwardcrookenden/otto-getting-started-eda-baseline,OTTO – Multi-Objective Recommender System
9576,116172528,2230.0,,0,0,/yokoyamadayo/polars-proof-of-concept-lgbm-ranker,OTTO – Multi-Objective Recommender System
9577,113438871,2245.0,,0,4,/jaloeffe92/otto-baselinesubmission,OTTO – Multi-Objective Recommender System
9578,111210951,2283.0,,1,2,/nikolayvdovin/create-otto-data,OTTO – Multi-Objective Recommender System
9579,112653776,2299.0,,13,147,/andradaolteanu/otto-i-was-warned-this-one-is-complicated,OTTO – Multi-Objective Recommender System
9580,109904281,2305.0,,5,79,/simamumu/old-test-data-last-20-aid-get-lb0-947,OTTO – Multi-Objective Recommender System
9581,110180987,2313.0,,12,36,/tompaulat/otto-bidirectional-lstm,OTTO – Multi-Objective Recommender System
9582,113430301,2349.0,0.4102220214964278,26,121,/junjitakeshima/otto-easy-understanding-for-beginner-en,OTTO – Multi-Objective Recommender System
9583,115342565,2358.0,,0,0,/jpnewmenji/eda-first-step,OTTO – Multi-Objective Recommender System
9584,114019112,2415.0,,0,0,/kyrobc/otto-popular-items-benchmark,OTTO – Multi-Objective Recommender System
9585,117588716,2417.0,,0,0,/sunghyunjun/otto-etl-with-co-visitation,OTTO – Multi-Objective Recommender System
9586,113193035,2446.0,,0,0,/pavanbagli/otto-train-data-json-to-tfrecord,OTTO – Multi-Objective Recommender System
9587,117830169,2455.0,0.0625819386107639,0,1,/amandahuangamanda/otto-eda,OTTO – Multi-Objective Recommender System
9588,115012513,2462.0,,0,3,/philipmarszal/simple-embeddings-using-keras,OTTO – Multi-Objective Recommender System
9589,115814347,2498.0,,4,22,/taahasaleembajwa/baby-steps-better-start-dumb-then-never-start,OTTO – Multi-Objective Recommender System
9590,116869393,2507.0,,0,4,/ankur561999/otto-multi-objective-r-system-getting-sarted,OTTO – Multi-Objective Recommender System
9591,114355391,2531.0,,0,6,/dellalkhaled/shoppredict-v-0,OTTO – Multi-Objective Recommender System
9592,115146237,2550.0,,0,1,/circleofcare/exploartory-analysis-of-otto-data,OTTO – Multi-Objective Recommender System
9593,115012434,65.0,,0,2,/taruto1215/rsna-breast-cancer-dicom-1-resized2048-png-jpg,RSNA Screening Mammography Breast Cancer Detection
9594,114055937,26.0,,5,36,/snaker/easy-load-the-image-with-nvjpeg2000,RSNA Screening Mammography Breast Cancer Detection
9595,112648858,9.0,,39,145,/remekkinas/breast-cancer-roi-brest-extractor,RSNA Screening Mammography Breast Cancer Detection
9596,112537192,20.0,,20,204,/theoviel/dicom-resized-png-jpg,RSNA Screening Mammography Breast Cancer Detection
9597,115053097,72.0,,0,6,/fanyang99/rsna-roi-train-1024-512,RSNA Screening Mammography Breast Cancer Detection
9598,130534718,52.0,,9,58,/hengck23/experiment-results-for-rsna,RSNA Screening Mammography Breast Cancer Detection
9599,115446351,54.0,,2,22,/tmyok1984/rsna-stratifiedgroupkfold,RSNA Screening Mammography Breast Cancer Detection
9600,118824053,575.0,,0,2,/prmahdish/new-saver,RSNA Screening Mammography Breast Cancer Detection
9601,115154528,136.0,,3,20,/jamesphoward/pf1-testing-is-it-ever-better-not-to-threshold,RSNA Screening Mammography Breast Cancer Detection
9602,117927092,63.0,,0,1,/rasoulmojtahedzadeh/test-bug-out-of-memory,RSNA Screening Mammography Breast Cancer Detection
9603,118826263,563.0,,0,0,/hideyukizushi/rsna-pp-convert-jpg-x1024,RSNA Screening Mammography Breast Cancer Detection
9604,114208352,548.0,0.0489864864864864,0,0,/yueqhu/own-predict,RSNA Screening Mammography Breast Cancer Detection
9605,117049580,60.0,0.0653061224489796,0,0,/billqi/logistic-regression-tabular-data,RSNA Screening Mammography Breast Cancer Detection
9606,112459984,572.0,,0,12,/desalegngeb/rsna-beast-cancer-detection-exploring-the-data,RSNA Screening Mammography Breast Cancer Detection
9607,119012010,549.0,,1,1,/nicehzj/rsna-tensorrt-inference,RSNA Screening Mammography Breast Cancer Detection
9608,113191539,505.0,,0,0,/mikecho/rsna-breast-cancer-dicom-png-lanczos4,RSNA Screening Mammography Breast Cancer Detection
9609,116539760,172.0,,18,91,/paulbacher/eda-rsna-breast-cancer-detection,RSNA Screening Mammography Breast Cancer Detection
9610,112916146,221.0,,2,20,/fabiendaniel/dicom-cropped-resized-png-jpg,RSNA Screening Mammography Breast Cancer Detection
9611,112737876,134.0,0.0493506493506493,4,3,/ernnnn4u/lgb-learn-nothing-haha,RSNA Screening Mammography Breast Cancer Detection
9612,120474669,45.0,0.0,1,2,/protegototalum/rsna-multiple-model-inference-tensorflow,RSNA Screening Mammography Breast Cancer Detection
9613,117738819,140.0,0.0403274908746998,5,20,/jay2333/resnet50-baseline-in-tensorflow,RSNA Screening Mammography Breast Cancer Detection
9614,114727721,156.0,,2,9,/outwrest/weird-mammograms,RSNA Screening Mammography Breast Cancer Detection
9615,112801799,164.0,,0,2,/lau01b/rsna-train-png,RSNA Screening Mammography Breast Cancer Detection
9616,113466193,445.0,,15,84,/tivfrvqhs5/decode-jpeg2000-dicom-with-dali,RSNA Screening Mammography Breast Cancer Detection
9617,121839270,238.0,0.0412371134020618,1,4,/tuongkhang/infer-pytorch-effnetb4,RSNA Screening Mammography Breast Cancer Detection
9618,117073655,424.0,0.4275862068965518,0,5,/thiruloksundar/rsna-inf-2,RSNA Screening Mammography Breast Cancer Detection
9619,116430445,143.0,0.156326112418557,1,15,/dragonzhang/rsna-efficientnetv2-inference-tensorflow,RSNA Screening Mammography Breast Cancer Detection
9620,115128355,494.0,,3,4,/namansingh2803/pytorch-efficientnet-b4-fp16-training,RSNA Screening Mammography Breast Cancer Detection
9621,115620228,275.0,0.3393939393939393,0,0,/jitshil143/rsna-efficientnetv2-inference-tensorflow,RSNA Screening Mammography Breast Cancer Detection
9622,119159899,281.0,,0,3,/yoyobar/separated-normalization-make-image-clearer,RSNA Screening Mammography Breast Cancer Detection
9623,118067108,283.0,,0,0,/tanakatentyo/rsna-cropped-tfrecords-768x1344-dataset,RSNA Screening Mammography Breast Cancer Detection
9624,112684310,286.0,,9,25,/mikhaildonskoy/eda-with-observations-data-structure,RSNA Screening Mammography Breast Cancer Detection
9625,114942835,442.0,,2,34,/utm529fg/eng-rsna-eda-understanding-train-data,RSNA Screening Mammography Breast Cancer Detection
9626,119070761,332.0,,0,2,/lucasrr/rsna-generate-1024x1024-data,RSNA Screening Mammography Breast Cancer Detection
9627,112433298,358.0,,4,22,/imvision12/pytorch-efficientnet-training-1000-images,RSNA Screening Mammography Breast Cancer Detection
9628,116088761,367.0,,0,0,/kerrit/rsna-m-eda-v2,RSNA Screening Mammography Breast Cancer Detection
9629,113110025,370.0,,5,25,/datafan07/multi-channel-images-with-different-windows,RSNA Screening Mammography Breast Cancer Detection
9630,114998053,169.0,,0,12,/chaitanyagiri/rsna-breast-cancer-inference-with-2-t4,RSNA Screening Mammography Breast Cancer Detection
9631,117274673,401.0,,0,4,/ridheshgoti/data-featuring-of-dcm-images,RSNA Screening Mammography Breast Cancer Detection
9632,116105061,408.0,,0,15,/dinowun/eda-simplified-rsna-smbcd,RSNA Screening Mammography Breast Cancer Detection
9633,113055711,423.0,0.1002173425608943,2,10,/hlly34/effnet-b4-baseline,RSNA Screening Mammography Breast Cancer Detection
9634,116967140,436.0,,3,41,/gpreda/rsna-mammography-breast-cancer-eda,RSNA Screening Mammography Breast Cancer Detection
9635,114709630,610.0,,0,3,/beezus666/dicom-to-png-to-predict,RSNA Screening Mammography Breast Cancer Detection
9636,122344036,617.0,,0,1,/arushikabansal/yessssssssssssssss,RSNA Screening Mammography Breast Cancer Detection
9637,120434669,268.0,0.5190839694656488,0,0,/pranavkuppa/rsna-comp,RSNA Screening Mammography Breast Cancer Detection
9638,120719528,651.0,,0,1,/michaelschroter/h5-catsndogs,RSNA Screening Mammography Breast Cancer Detection
9639,115678766,658.0,,0,9,/shujaat91/tensorflow-basic-eda-and-training-vit,RSNA Screening Mammography Breast Cancer Detection
9640,121543146,661.0,,7,8,/tyeestudio/rsna-eda-pytorch-bl-without-wandb-dependency,RSNA Screening Mammography Breast Cancer Detection
9641,119620957,218.0,,2,9,/anlthms/rsna-mammogram-model-error-analysis,RSNA Screening Mammography Breast Cancer Detection
9642,116478539,105.0,,0,14,/raufmomin/roi-extractor-pre-processing-dicom-simple-way,RSNA Screening Mammography Breast Cancer Detection
9643,119445307,1101.0,,0,3,/lucario129/infer-pytorch-baseline,RSNA Screening Mammography Breast Cancer Detection
9644,114546109,161.0,0.0366804979139632,9,34,/tomooinubushi/some-lb-probing-results-to-share,RSNA Screening Mammography Breast Cancer Detection
9645,119761831,924.0,,0,0,/asimandia/fastpredictbaseline,RSNA Screening Mammography Breast Cancer Detection
9646,118913020,798.0,,0,1,/arijitdas2002/train-pytorch-rsna,RSNA Screening Mammography Breast Cancer Detection
9647,118517058,784.0,,28,63,/kevinmorgado/eda-breast-cancer-detection,RSNA Screening Mammography Breast Cancer Detection
9648,113529299,805.0,,34,296,/radek1/eda-training-a-fast-ai-model-submission,RSNA Screening Mammography Breast Cancer Detection
9649,112447205,807.0,,1,12,/satyaprakashshukl/eda-screening-detection,RSNA Screening Mammography Breast Cancer Detection
9650,112665531,808.0,,0,1,/michaelgartsbein/save-cropped-images,RSNA Screening Mammography Breast Cancer Detection
9651,114702637,842.0,,2,6,/alicew1800/rsna-fastai-simple-cnn-train-inference,RSNA Screening Mammography Breast Cancer Detection
9652,112566374,894.0,,7,15,/osmanf/weak-eda,RSNA Screening Mammography Breast Cancer Detection
9653,116185376,897.0,,0,0,/michaelscheinfeilda/first-submission-with-smaller-dataset,RSNA Screening Mammography Breast Cancer Detection
9654,116492847,906.0,,0,0,/oneobi/rsna-image-preprocessing,RSNA Screening Mammography Breast Cancer Detection
9655,117058079,1478.0,,0,13,/atshimamura/jpn-image-cropping,RSNA Screening Mammography Breast Cancer Detection
9656,113756478,752.0,0.3973509933774833,34,164,/vslaykovsky/infer-pytorch-aux-targets-weighted-loss-thres,RSNA Screening Mammography Breast Cancer Detection
9657,117334683,765.0,,0,2,/ycleonard/data-process-crop,RSNA Screening Mammography Breast Cancer Detection
9658,113585708,780.0,,1,4,/pranay1990/eda-rsna-breast-cancer,RSNA Screening Mammography Breast Cancer Detection
9659,115024001,716.0,,1,36,/awsaf49/metric-probabilistic-fscore-tf-torch-numpy,RSNA Screening Mammography Breast Cancer Detection
9660,112991068,742.0,,0,8,/lonnieqin/probabilistic-f1-score-tensorflow-implementation,RSNA Screening Mammography Breast Cancer Detection
9661,112583043,744.0,,0,10,/mohammaddehghan/rsna-breast-full-comprehension-and-eda,RSNA Screening Mammography Breast Cancer Detection
9662,116871930,709.0,,3,17,/olegbaryshnikov/rsna-tfrecods-resized-images-and-roi,RSNA Screening Mammography Breast Cancer Detection
9663,113780826,990.0,0.3024054982817869,0,8,/prachi13/rsna-cancer-detection,RSNA Screening Mammography Breast Cancer Detection
9664,113780826,990.0,0.3024054982817869,0,8,/prachi13/rsna-cancer-detection,RSNA Screening Mammography Breast Cancer Detection
9665,115905199,971.0,,2,1,/crischir/a-wavelet-layer-for-tensorflow-eda,RSNA Screening Mammography Breast Cancer Detection
9666,118684665,977.0,,1,5,/nikolagavranovic/rsna-exploratory-data-analysis,RSNA Screening Mammography Breast Cancer Detection
9667,117428971,1025.0,0.0869565217391304,0,2,/phamlequangnhat/fastai-version,RSNA Screening Mammography Breast Cancer Detection
9668,112430956,1061.0,,3,9,/paarthbhatnagar/rsna-annotated-explanation-of-evaluation-metric,RSNA Screening Mammography Breast Cancer Detection
9669,119749563,1034.0,,13,31,/asklepije/training-script-nextvit-with-patchgd,RSNA Screening Mammography Breast Cancer Detection
9670,112570473,1052.0,,5,13,/davidbroberts/mammography-pad-to-square,RSNA Screening Mammography Breast Cancer Detection
9671,117678797,1064.0,,0,12,/dingyan/rsna-eda-pca-logistic-regression,RSNA Screening Mammography Breast Cancer Detection
9672,115753946,1093.0,,0,1,/nikitaglazunov/breast-comp-eda,RSNA Screening Mammography Breast Cancer Detection
9673,113894087,1100.0,,11,25,/ssarkar445/rsna-eda-all-you-need,RSNA Screening Mammography Breast Cancer Detection
9674,114152943,1109.0,,0,2,/mujrush/train-pytorch-simple-baseline,RSNA Screening Mammography Breast Cancer Detection
9675,112499586,1104.0,,0,3,/miltiadesgeneral/exploring-the-data,RSNA Screening Mammography Breast Cancer Detection
9676,116640868,1105.0,,3,16,/kuntalpal/rsna-baseline,RSNA Screening Mammography Breast Cancer Detection
9677,114304753,1120.0,,9,30,/leventelippenszky/eda-baseline-submission-age-normalized,RSNA Screening Mammography Breast Cancer Detection
9678,113766941,1129.0,,0,2,/handsomeevy/rsna-infer,RSNA Screening Mammography Breast Cancer Detection
9679,118833994,1159.0,0.0458721506850836,0,0,/dog14230pp/rsna1-resnet50,RSNA Screening Mammography Breast Cancer Detection
9680,114165432,1171.0,,0,2,/rcsho0/rsna-breast-cancer-processing,RSNA Screening Mammography Breast Cancer Detection
9681,120223510,1172.0,,0,2,/salmasultan98/rsna2salma,RSNA Screening Mammography Breast Cancer Detection
9682,119774583,1547.0,,1,5,/leweisele/cancer-positive-case-oversampling,RSNA Screening Mammography Breast Cancer Detection
9683,113264707,1194.0,0.0661096318060783,0,0,/phamquochuy1101/rsna-breast-baseline-inference,RSNA Screening Mammography Breast Cancer Detection
9684,113227513,1176.0,,0,4,/kaggleqrdl/non-image-eda,RSNA Screening Mammography Breast Cancer Detection
9685,114944569,1213.0,,0,8,/jacoporepossi/deep-learning-basics-5-popular-pytorch-methods,RSNA Screening Mammography Breast Cancer Detection
9686,119613709,1209.0,0.0406402408763054,0,2,/dhruvkhatri/infer-simple-rsna-submission,RSNA Screening Mammography Breast Cancer Detection
9687,112644878,1178.0,,8,34,/vovinsa/new-train-pipeline,RSNA Screening Mammography Breast Cancer Detection
9688,112796337,1205.0,,20,34,/boydbigdatarpg/simple-start-with-tuned-lgbm,RSNA Screening Mammography Breast Cancer Detection
9689,113769940,1522.0,,0,6,/benfaraji/rsna-smbcd-model-training,RSNA Screening Mammography Breast Cancer Detection
9690,118404405,1219.0,0.0426382411725516,0,2,/maryiaznak/breast-cancer-detection-tf-cnn-test,RSNA Screening Mammography Breast Cancer Detection
9691,119591236,1520.0,,0,1,/azazaa/rsna-breast-cancer-detection-part-1-eda,RSNA Screening Mammography Breast Cancer Detection
9692,115190089,1275.0,,10,75,/javigallego/rsna-complete-eda-external-data,RSNA Screening Mammography Breast Cancer Detection
9693,120596902,1446.0,,1,3,/marcosgois07/breast-cancer-eda-prediction-with-resnet50,RSNA Screening Mammography Breast Cancer Detection
9694,118821799,1311.0,,1,12,/anttiisosalo/solt-based-image-augs-rsna-bc-detection,RSNA Screening Mammography Breast Cancer Detection
9695,114351164,1280.0,,0,0,/larsmadsen/convert-and-crop-training-images,RSNA Screening Mammography Breast Cancer Detection
9696,115086871,1270.0,,0,9,/shameinew/rsna-bc-prediction,RSNA Screening Mammography Breast Cancer Detection
9697,119669612,1445.0,,0,0,/conweezy/rsna-submission-test,RSNA Screening Mammography Breast Cancer Detection
9698,112599579,1278.0,0.0413992340651388,1,9,/dschettler8845/rsna-bcd-simple-age-baseline-submission,RSNA Screening Mammography Breast Cancer Detection
9699,112428013,1248.0,0.0392289655620207,1,7,/rsiva1104/eda-and-data-analysis,RSNA Screening Mammography Breast Cancer Detection
9700,120659114,1405.0,,0,0,/dankurland/rnsa-dk-and-npd-working-model-v2,RSNA Screening Mammography Breast Cancer Detection
9701,114503611,1482.0,,0,0,/bwallyn/rsna-breast-cancer-detection-eda,RSNA Screening Mammography Breast Cancer Detection
9702,112657557,1328.0,,1,2,/zarahshibli/eda-breast-cancer-detection,RSNA Screening Mammography Breast Cancer Detection
9703,115858665,1366.0,,0,0,/luizhemerly/augmented-cancer-data,RSNA Screening Mammography Breast Cancer Detection
9704,118226736,1358.0,0.0395489338230718,0,0,/ollyrennard/rsna-simple-baseline-predictions,RSNA Screening Mammography Breast Cancer Detection
9705,115413851,1470.0,,0,1,/dhinkris/eda-speculation-using-tensorflow-torchio,RSNA Screening Mammography Breast Cancer Detection
9706,117611003,1411.0,,0,1,/nizarhaytham/rsna-extraction-2,RSNA Screening Mammography Breast Cancer Detection
9707,125757233,1401.0,,0,5,/koubouratouidjaton/rsna-breast-cancer-dataset-exploration-insights,RSNA Screening Mammography Breast Cancer Detection
9708,120383133,1368.0,,0,1,/theodorospsarras/notebook5ec0873e1f,RSNA Screening Mammography Breast Cancer Detection
9709,117523518,1416.0,0.0368781796043413,1,5,/julianmacnamara/rsna-screening-mammography-breast-cancer-detection,RSNA Screening Mammography Breast Cancer Detection
9710,112670613,1251.0,,1,10,/gabrielbchacon/start-w-ensemble-xgboost-lgbm-catboost-tuned,RSNA Screening Mammography Breast Cancer Detection
9711,117630736,1321.0,0.0410223884435605,0,2,/cafelatte1/rsna-baseline-with-logistic-regression,RSNA Screening Mammography Breast Cancer Detection
9712,120128766,1419.0,0.0409939189886538,0,11,/joerobcia/detectando-cancer,RSNA Screening Mammography Breast Cancer Detection
9713,121495337,1281.0,,0,3,/allamamr/cancer-breast-detection-array-proj2,RSNA Screening Mammography Breast Cancer Detection
9714,115909103,1413.0,,2,3,/stpeteishii/mammography-conv2d-with-cropped-images,RSNA Screening Mammography Breast Cancer Detection
9715,112829715,1418.0,,0,0,/vivekprajapati2048/rsna-bc-baseline-pytorch-model-train-inference,RSNA Screening Mammography Breast Cancer Detection
9716,119238514,1441.0,0.0402892055897771,0,0,/uladzislaumitskevich/breast-cancer-detection-training,RSNA Screening Mammography Breast Cancer Detection
9717,120213562,1507.0,0.038635770564407,1,11,/sarashahin/rsna-screening-mammography-breast-cancer-detection,RSNA Screening Mammography Breast Cancer Detection
9718,115243529,1550.0,0.0393664566172059,2,5,/ahmedhossam666/rsna-breast,RSNA Screening Mammography Breast Cancer Detection
9719,112598184,1528.0,,0,5,/mmoore23/initial-eda-and-image-loading,RSNA Screening Mammography Breast Cancer Detection
9720,117139970,1540.0,,3,1,/ericwalterpefurayone/no-need-to-convert-dicom-to-png-for-training,RSNA Screening Mammography Breast Cancer Detection
9721,118902559,1551.0,,0,1,/jarvisai7/organize-dataset-per-label,RSNA Screening Mammography Breast Cancer Detection
9722,120592338,1539.0,,0,0,/yeemeitsang/breast-cancer-detection-pytorch,RSNA Screening Mammography Breast Cancer Detection
9723,123066987,1563.0,0.0409569951550871,2,4,/vatsalsivaratri/rsna-breast-cancer-detection-using-resnet101v2-cnn,RSNA Screening Mammography Breast Cancer Detection
9724,117436491,1567.0,,0,1,/rameshsimhadri/simple-deep-learning-strategy-slightly-improved,RSNA Screening Mammography Breast Cancer Detection
9725,114471284,1565.0,,3,34,/asimple/eda-rsna,RSNA Screening Mammography Breast Cancer Detection
9726,116302477,1573.0,0.0211649993453172,4,7,/toqitahamid/resnet26d-with-png-images-fast-ai,RSNA Screening Mammography Breast Cancer Detection
9727,115278330,1583.0,,0,0,/sakarilukkarinen/rsna-2022-dicom-data,RSNA Screening Mammography Breast Cancer Detection
9728,117855878,1587.0,,0,2,/prutsaowaprut/rsna-dicom-pytorch-dataloader-simple,RSNA Screening Mammography Breast Cancer Detection
9729,114856199,1588.0,,0,0,/hasangoni/create-smaller-dataset-for-faster-experimentation,RSNA Screening Mammography Breast Cancer Detection
9730,112733304,1596.0,0.0208492245105524,2,19,/jirkaborovec/mammography-eda-loading-dicom,RSNA Screening Mammography Breast Cancer Detection
9731,114644387,1606.0,,0,6,/slythe/rsna-keras-resnet-modelling,RSNA Screening Mammography Breast Cancer Detection
9732,148757963,1562.0,,15,84,/meeratif/rsna-breast-cancer-prediction-eda,RSNA Screening Mammography Breast Cancer Detection
9733,114134968,1615.0,,2,11,/yoshikuwano/rsna-eda-in-dicom-data,RSNA Screening Mammography Breast Cancer Detection
9734,117456664,1631.0,,0,0,/mourinho384/inference-rsna-bcd,RSNA Screening Mammography Breast Cancer Detection
9735,116052573,1654.0,,8,16,/aaron1288/very-simple-deep-learning-strategy,RSNA Screening Mammography Breast Cancer Detection
9736,119622067,1676.0,,0,0,/yuiceee/ddsm-test,RSNA Screening Mammography Breast Cancer Detection
9737,143879746,1679.0,,0,1,/rimzakhama/rsna-pytorch-baseline-training-for-beginners,RSNA Screening Mammography Breast Cancer Detection
9738,112815993,1.0,,3,73,/cnumber/lower-bound-using-minimum-spanning-tree,Santa 2022 - The Christmas Card Conundrum
9739,112920773,15.0,82106.64793831746,7,43,/nicupetridean/further-analysis-of-costs-points-ordering,Santa 2022 - The Christmas Card Conundrum
9740,116694061,18.0,,0,2,/fujiwararyo/santa2022-gif-visualization-of-a-submission-file,Santa 2022 - The Christmas Card Conundrum
9741,113403834,26.0,,6,42,/elvenmonk/santa-2022-lower-bound-approximation-73078,Santa 2022 - The Christmas Card Conundrum
9742,113408016,51.0,,1,6,/alyonamakarova/path-animation,Santa 2022 - The Christmas Card Conundrum
9743,116740479,57.0,74341.95184979815,1,2,/nyleve/soln-57-santa22-local-optimization-38ce16,Santa 2022 - The Christmas Card Conundrum
9744,116668618,60.0,74346.51772858638,2,12,/taanieluleksin/modified-standard-configuration-with-lkh-60th,Santa 2022 - The Christmas Card Conundrum
9745,116026607,64.0,,5,29,/vitalykudelya/simple-optimization-of-zigzag-moves-for-77200,Santa 2022 - The Christmas Card Conundrum
9746,112688082,101.0,,0,10,/saitodevel01/santa2022-submission-validation,Santa 2022 - The Christmas Card Conundrum
9747,115170164,102.0,,3,23,/thachhoang2410/first-try-on-reinforcement-learning-approach,Santa 2022 - The Christmas Card Conundrum
9748,113860940,133.0,,0,3,/taffeylewis/for-fun-average-color-costs,Santa 2022 - The Christmas Card Conundrum
9749,115216664,158.0,,5,25,/wkirgsn/fast-cost-function-calculation,Santa 2022 - The Christmas Card Conundrum
9750,113161205,163.0,81944.27924290164,4,50,/asalhi/tsp-cost-function-start-compress-path-split,Santa 2022 - The Christmas Card Conundrum
9751,112997142,186.0,82051.41110352284,0,17,/satyaprakashshukl/santa-december,Santa 2022 - The Christmas Card Conundrum
9752,115375557,202.0,,3,8,/fx6300/santa-2022-or-tools-k-means-and-cp-sat,Santa 2022 - The Christmas Card Conundrum
9753,112613286,301.0,,0,9,/rsiva1104/eda-data-analysis-of-santa-2022,Santa 2022 - The Christmas Card Conundrum
9754,114105342,452.0,80848.82776456386,15,80,/oxzplvifi/pixel-travel-map,Santa 2022 - The Christmas Card Conundrum
9755,114748683,461.0,79336.20775357333,0,35,/pkorobov/pixel-travel-map-rotate-more-links,Santa 2022 - The Christmas Card Conundrum
9756,112957369,546.0,82059.64937138639,5,24,/snufkin77/further-point-order-improvements-tsp-start,Santa 2022 - The Christmas Card Conundrum
9757,113236235,601.0,82019.95256012602,1,6,/sfktrkl/santa-2022,Santa 2022 - The Christmas Card Conundrum
9758,113986777,607.0,82019.95256012602,0,1,/saraswatitiwari/santa-2022-the-christmas-card-conundrum,Santa 2022 - The Christmas Card Conundrum
9759,113331026,622.0,,3,39,/jazivxt/tsp-cost-function-start,Santa 2022 - The Christmas Card Conundrum
9760,116808719,730.0,,2,3,/pavelvod/santa-circular-solution,Santa 2022 - The Christmas Card Conundrum
9761,113144227,785.0,,0,5,/stpeteishii/santa-2022-scatter-plot,Santa 2022 - The Christmas Card Conundrum
9762,113452483,868.0,,1,5,/griffh/santa-eda-about-color,Santa 2022 - The Christmas Card Conundrum
9763,121509792,19.0,,0,4,/tatamikenn/nfl-benchmark-of-loading-images,1st and Future - Player Contact Detection
9764,121135834,16.0,,0,2,/anyai28/load-image-benchmark,1st and Future - Player Contact Detection
9765,117694755,18.0,,0,1,/thomasdubail/nfl-all-videos-with-labels,1st and Future - Player Contact Detection
9766,118085207,41.0,0.6256645035468583,5,45,/stgkrtua/nfl-i-am-learing-polars-w-lgb,1st and Future - Player Contact Detection
9767,129860223,33.0,,0,2,/yiiino/load-image-benchmark-including-npy-and-pkl,1st and Future - Player Contact Detection
9768,115108919,48.0,0.6505189648188651,12,90,/ahmedelfazouan/nfl-player-contact-detection-helmet-track-ftrs,1st and Future - Player Contact Detection
9769,115796551,67.0,,0,4,/kyosaikyo/understand-table-data-japanese,1st and Future - Player Contact Detection
9770,119564471,66.0,0.6699643951678167,11,62,/royalacecat/nfl-2-5d-cnn,1st and Future - Player Contact Detection
9771,120609000,89.0,,0,0,/ryotasueyoshi/inference-fclayer-table-data-image,1st and Future - Player Contact Detection
9772,117851535,692.0,,2,0,/jesperandersson/nflpcd-join-dataframes,1st and Future - Player Contact Detection
9773,113150303,707.0,0.5830879618777356,10,109,/columbia2131/nfl-player-contact-detection-simple-xgb-baseline,1st and Future - Player Contact Detection
9774,113106417,663.0,,6,13,/erenakbulut/eda-using-sweetviz-and-pandasprofiling,1st and Future - Player Contact Detection
9775,115655054,426.0,0.6710642803434764,0,10,/saraswatitiwari/1st-and-future-player-contact-detection,1st and Future - Player Contact Detection
9776,116743329,442.0,,1,10,/dinowun/eda-simplified-nfl-1st-and-future-pcd,1st and Future - Player Contact Detection
9777,118186275,164.0,,0,0,/shashankijeri/nfl-player-contact-detection-home-step-lr,1st and Future - Player Contact Detection
9778,117723725,532.0,0.6710642803434764,0,1,/greg90/lb-0-670-2-5d-cnn-baseline-part-tta-trick,1st and Future - Player Contact Detection
9779,118748904,556.0,0.670062455145572,3,1,/bhargavchirumamilla/lb-0-670-2-5d-cnn-baseline-part-tta-trick,1st and Future - Player Contact Detection
9780,120677428,559.0,,1,0,/sailohitakshreddyd/training-notebook,1st and Future - Player Contact Detection
9781,119696916,584.0,0.6710642803434764,0,0,/chinnamsasidharreddy/1st-and-future-player-contact-detection,1st and Future - Player Contact Detection
9782,119704863,344.0,0.6699735884408908,0,0,/puranjay14/nfl-1-purjaysin,1st and Future - Player Contact Detection
9783,113166761,249.0,,1,19,/satyaprakashshukl/player-detection-segmentation,1st and Future - Player Contact Detection
9784,118909539,863.0,,0,2,/nadhirhasan/player-detection-assigning-infer,1st and Future - Player Contact Detection
9785,114688835,137.0,0.6678535372506794,56,134,/zzy990106/nfl-2-5d-cnn-baseline-inference,1st and Future - Player Contact Detection
9786,114369924,671.0,0.6652617542487389,0,3,/sanandachowdhury/player-contact-detection,1st and Future - Player Contact Detection
9787,114369924,671.0,0.6652617542487389,0,3,/sanandachowdhury/player-contact-detection,1st and Future - Player Contact Detection
9788,147936062,746.0,,0,0,/archiecarpenter/our-best-submission,1st and Future - Player Contact Detection
9789,119867176,758.0,,2,3,/vinitkp/player-contact,1st and Future - Player Contact Detection
9790,113840853,777.0,,1,8,/dqhdqmcttdqx/nfl-2022-eda-player-contact-detection,1st and Future - Player Contact Detection
9791,113398811,788.0,,0,7,/louisbunuel/yolov7-nfl-contact,1st and Future - Player Contact Detection
9792,114529118,786.0,0.5171379796286881,0,10,/ricardfos/player-contact-detection,1st and Future - Player Contact Detection
9793,113927847,801.0,,0,1,/ryancaldwell/xgboost-model,1st and Future - Player Contact Detection
9794,113614157,823.0,0.5830879618777356,0,0,/josephkibira/nfl-player-contact-detection-simple-xgb-baseline,1st and Future - Player Contact Detection
9795,113697327,825.0,,1,4,/dlogical/nfl-player-detection-tracking,1st and Future - Player Contact Detection
9796,119987938,828.0,,9,23,/mdriponmiah/nfl-player-contact-detection,1st and Future - Player Contact Detection
9797,121863467,1.0,0.6196562389592797,0,2,/aerdem4/lecr-efficiency-nobert,Learning Equality - Curriculum Recommendations
9798,115128438,3.0,0.2358994652246513,0,12,/hengzheng/lecr-sbert-recall-on-language,Learning Equality - Curriculum Recommendations
9799,115740835,9.0,,12,71,/thedrcat/lecr-100-experiments-to-improve-recall,Learning Equality - Curriculum Recommendations
9800,122753677,26.0,0.6481776258169444,0,2,/goldenlock/stage1-single-model-1fold,Learning Equality - Curriculum Recommendations
9801,122165689,31.0,0.6425925702455498,1,9,/nlztrk/lecr-st-cross-encoders-cv-0-6461-50-pp,Learning Equality - Curriculum Recommendations
9802,116912379,39.0,,0,1,/calpis10000/lecr-pre-embedding-xlmrobertabase-title,Learning Equality - Curriculum Recommendations
9803,119790501,105.0,0.459997033070828,26,67,/karakasatarik/0-459-single-model-inference-w-postprocessing,Learning Equality - Curriculum Recommendations
9804,115795902,95.0,,0,2,/kkkkkkc/lecr-eda,Learning Equality - Curriculum Recommendations
9805,113959951,109.0,,5,25,/columbia2131/lecr-example-of-f2-score,Learning Equality - Curriculum Recommendations
9806,120496515,121.0,,0,0,/qcqced/lecr-eda-preprocess,Learning Equality - Curriculum Recommendations
9807,114149853,104.0,,0,19,/tubotubo/lecr-tfidf-inference,Learning Equality - Curriculum Recommendations
9808,117049652,154.0,0.444006275243149,43,81,/kojimar/retriever-ensemble,Learning Equality - Curriculum Recommendations
9809,117683798,226.0,0.2328293001498662,0,18,/leehann/inference-using-hnswlib-ds,Learning Equality - Curriculum Recommendations
9810,117273673,213.0,,2,8,/sinchir0/lecr-simple-eda,Learning Equality - Curriculum Recommendations
9811,120058421,155.0,,0,1,/xiezejian/polars-f2-score,Learning Equality - Curriculum Recommendations
9812,113945516,428.0,,1,15,/desalegngeb/short-eda,Learning Equality - Curriculum Recommendations
9813,114605760,426.0,,0,4,/lau01b/lecr-eda,Learning Equality - Curriculum Recommendations
9814,116694960,231.0,,1,9,/danofer/lecr-multiling-sentencetransformers-mnr-finetune,Learning Equality - Curriculum Recommendations
9815,116482331,440.0,0.2501880393656406,0,5,/bulivington/lecr-sbert-infer,Learning Equality - Curriculum Recommendations
9816,118375325,342.0,,0,9,/tfukuda675/lecr-polars-pandas-eda,Learning Equality - Curriculum Recommendations
9817,116724476,439.0,,0,6,/gomaki/observation-of-correlations-csv,Learning Equality - Curriculum Recommendations
9818,114109998,457.0,,10,50,/satyaprakashshukl/le-curriculum-recommendations,Learning Equality - Curriculum Recommendations
9819,120555250,477.0,0.459997033070828,2,28,/masterofdeception/0-459-single-model-inference-w-postprocessing,Learning Equality - Curriculum Recommendations
9820,118028704,483.0,,0,3,/rahultriv5/curriculum-recommendations-eda-for-everyone,Learning Equality - Curriculum Recommendations
9821,116612080,545.0,0.2677061021765959,0,17,/sayantankirtaniya/infer-with-paraphrase-multilingual-mpnet-base-v2,Learning Equality - Curriculum Recommendations
9822,114455949,561.0,,0,6,/jjinho/learning-equality-eda,Learning Equality - Curriculum Recommendations
9823,117553705,567.0,,0,1,/vonewman/galsenai-notebook-eda-curriculum-recommendations,Learning Equality - Curriculum Recommendations
9824,124344386,575.0,,5,6,/dinowun/eda-simplified-learning-equality-cr,Learning Equality - Curriculum Recommendations
9825,120364232,580.0,,0,0,/duuuscha/lecr-infer-sbert-crossbert,Learning Equality - Curriculum Recommendations
9826,117425848,656.0,0.444006275243149,0,0,/anhngtvoxter/retriever-ensemble,Learning Equality - Curriculum Recommendations
9827,120826321,679.0,,0,2,/nicyscaria22/exploratory-data-analysis,Learning Equality - Curriculum Recommendations
9828,118306492,687.0,,0,1,/whitelily/polars-f2-score,Learning Equality - Curriculum Recommendations
9829,119845472,710.0,,1,0,/yilinl1u/inference,Learning Equality - Curriculum Recommendations
9830,115989957,726.0,,1,6,/riadalmadani/sentence-transformers,Learning Equality - Curriculum Recommendations
9831,114014839,739.0,,1,5,/erenakbulut/eda-and-visualization-seaborn-msno,Learning Equality - Curriculum Recommendations
9832,116166245,750.0,,2,4,/andtaichi/lecr-inference-p-finetuning,Learning Equality - Curriculum Recommendations
9833,114294360,760.0,0.1703156383208989,9,32,/ssarkar445/le-curriculum-sbert-baseline,Learning Equality - Curriculum Recommendations
9834,122349268,873.0,,0,3,/joviis/end-to-end-approach,Learning Equality - Curriculum Recommendations
9835,118259726,808.0,,2,6,/vishwasgpai/basic-lec-eda,Learning Equality - Curriculum Recommendations
9836,119309645,874.0,,0,1,/yitaoyu/lecr-inference-notebook0,Learning Equality - Curriculum Recommendations
9837,114655214,825.0,,3,17,/kaizen97/learning-equality-data-analysis,Learning Equality - Curriculum Recommendations
9838,114893160,845.0,0.2359281815119598,6,111,/takamichitoda/lecr-simple-unsupervised-baseline,Learning Equality - Curriculum Recommendations
9839,115799169,849.0,0.2359281815119598,0,2,/corneliuskristianto/lecr-baseline,Learning Equality - Curriculum Recommendations
9840,115319099,878.0,,10,33,/hetarthchopra/explore-k12-with-me-eda,Learning Equality - Curriculum Recommendations
9841,114603736,902.0,,0,10,/zacchaeus/lecr-cv,Learning Equality - Curriculum Recommendations
9842,117942553,887.0,5.542377014654045e-05,0,0,/asiamr/deep-retrieval-model-with-tf-recommenders,Learning Equality - Curriculum Recommendations
9843,120695382,951.0,,0,0,/saansd2003/lecr-sentence-transformer-data-prep,Learning Equality - Curriculum Recommendations
9844,117726539,937.0,0.2087729567827322,0,1,/shivamtarte/sbert-topic-tree-lecr-recommendation111,Learning Equality - Curriculum Recommendations
9845,118354864,922.0,,3,4,/rachanabisht/comprehensive-eda,Learning Equality - Curriculum Recommendations
9846,122038177,942.0,,0,0,/sunghyunjun/lecr-train-lgbmclassifier,Learning Equality - Curriculum Recommendations
9847,118821608,941.0,0.0077429933335074,0,0,/cafelatte1/lecr-xlm-roberta-embedding-nearest-neighbor,Learning Equality - Curriculum Recommendations
9848,116937065,948.0,0.1975847568313474,2,13,/nesrineazaiez/equality-curriculum-recommendations,Learning Equality - Curriculum Recommendations
9849,114240593,968.0,,1,2,/nqbinh17/hover-nodes-edges-tooltips,Learning Equality - Curriculum Recommendations
9850,115249305,992.0,0.0169002600751191,0,7,/bechirkarmeni/learning-equality-curriculum-recommendations-2,Learning Equality - Curriculum Recommendations
9851,121161212,995.0,,0,1,/ekanshtrivedi09/learning-equality-eda,Learning Equality - Curriculum Recommendations
9852,115827360,997.0,,1,7,/bradhammond/tensorflow-hugging-face-unsupervised-baseline,Learning Equality - Curriculum Recommendations
9853,114111754,1010.0,0.0169002600751191,1,8,/jazivxt/on-topic,Learning Equality - Curriculum Recommendations
9854,113943813,1015.0,0.0072847032172484,0,6,/ttahara/le-cr-same-channel-contents-baseline,Learning Equality - Curriculum Recommendations
9855,119789123,1018.0,0.0006669375690775,1,8,/grzaini/understanding-data-and-modeling,Learning Equality - Curriculum Recommendations
9856,113988498,1029.0,0.0,0,5,/rsiva1104/curriculum-recommendations-eda,Learning Equality - Curriculum Recommendations
9857,115009924,1.0,,1,19,/kaggleqrdl/parse-code-bls-emp-data,GoDaddy - Microbusiness Density Forecasting
9858,114576763,3.0,,56,256,/cdeotte/linear-regression-baseline-lb-1-092,GoDaddy - Microbusiness Density Forecasting
9859,118386216,109.0,,0,8,/petersorensen360/better-xgb-with-census-data-and-feature-importance,GoDaddy - Microbusiness Density Forecasting
9860,121158878,4.0,,15,73,/vitalykudelya/simple-baseline-with-eda-and-smape-behaviour,GoDaddy - Microbusiness Density Forecasting
9861,115077952,50.0,,4,34,/vadimkamaev/first-submission-1-089,GoDaddy - Microbusiness Density Forecasting
9862,115359784,753.0,,8,26,/werus23/create-rnn-model,GoDaddy - Microbusiness Density Forecasting
9863,126255253,2995.0,,3,60,/gpreda/godaddy-data-cleaning-and-eda,GoDaddy - Microbusiness Density Forecasting
9864,117156135,2736.0,,1,15,/yoyobar/godaddy-with-autogluon-automl-lb-1-0944,GoDaddy - Microbusiness Density Forecasting
9865,148601907,537.0,,0,2,/seshurajup/godaddy-eda,GoDaddy - Microbusiness Density Forecasting
9866,121017124,2959.0,,10,43,/dangnguyen97/lb-1-3803-simple-baseline-with-eda-and-smape,GoDaddy - Microbusiness Density Forecasting
9867,114249580,2929.0,,6,19,/shrutisaxena/godaddy-density-forecasting-starter-code,GoDaddy - Microbusiness Density Forecasting
9868,118112217,339.0,,0,10,/abdualimov/elasticnet-simple,GoDaddy - Microbusiness Density Forecasting
9869,114800610,248.0,,0,4,/namanmehta1/godaddy-1-33-randomforestregressor,GoDaddy - Microbusiness Density Forecasting
9870,116765932,2842.0,,2,38,/eishkaran/godaddy-better-eda-xgb-baseline,GoDaddy - Microbusiness Density Forecasting
9871,115061043,472.0,,0,16,/devashishbhake01/better-version-density-forcasting,GoDaddy - Microbusiness Density Forecasting
9872,121097619,3252.0,,0,2,/kitnick/godaddy-tune-catboost-by-jst,GoDaddy - Microbusiness Density Forecasting
9873,120595448,3178.0,,20,69,/tetsutani/catboost-only-tune-score-lb1-3827,GoDaddy - Microbusiness Density Forecasting
9874,121675924,297.0,,5,32,/judith007/model-ensemble-tuning,GoDaddy - Microbusiness Density Forecasting
9875,118014590,28.0,,17,90,/greysky/lightgbm-starter-with-us-map-lb-1-0871,GoDaddy - Microbusiness Density Forecasting
9876,120321109,2742.0,,0,2,/samuraikaggle/pycaret-automl-for-beginner,GoDaddy - Microbusiness Density Forecasting
9877,115673522,620.0,,0,5,/batprem/svr-baseline,GoDaddy - Microbusiness Density Forecasting
9878,118992229,1589.0,,0,11,/suhancho/tabnet-with-geo-point-data,GoDaddy - Microbusiness Density Forecasting
9879,115053384,2643.0,,4,8,/mohamedbakrey/the-best-way-for-model-random-forest-regression,GoDaddy - Microbusiness Density Forecasting
9880,115811614,2933.0,,3,31,/songqizhou/sample-voting-lb-17,GoDaddy - Microbusiness Density Forecasting
9881,121611418,2062.0,,11,44,/kevinmorgado/godaddy-data-analysis,GoDaddy - Microbusiness Density Forecasting
9882,114167253,112.0,,0,5,/ryanirl/gd-mdf-altair-choropleth-maps,GoDaddy - Microbusiness Density Forecasting
9883,114520211,1664.0,,0,0,/shahidmandal/godaddy-census-data-plots-with-plotly,GoDaddy - Microbusiness Density Forecasting
9884,116408539,20.0,,1,16,/tomkkk/xgb-baseline-in-r,GoDaddy - Microbusiness Density Forecasting
9885,115347303,325.0,,4,14,/maheshak04/understanding-data-godaddy-microbusiness-forecas,GoDaddy - Microbusiness Density Forecasting
9886,120354552,346.0,,5,15,/abinsingh/school-guy-approach-score-3-8-exe-time-30-sec,GoDaddy - Microbusiness Density Forecasting
9887,120558519,374.0,3.9665929709573575,7,8,/lianxinwu/better-xgb-baseline-understanding-for-chatgpt,GoDaddy - Microbusiness Density Forecasting
9888,119457504,415.0,,0,9,/rzatemizel/a-better-baseline-cnn-gru,GoDaddy - Microbusiness Density Forecasting
9889,116994595,445.0,,0,3,/muskem/quick-easy-checks,GoDaddy - Microbusiness Density Forecasting
9890,119860521,491.0,,0,2,/toya18/godaddy-eda,GoDaddy - Microbusiness Density Forecasting
9891,121106234,301.0,,0,2,/harelrom/new-last-value-baseline-1-5738,GoDaddy - Microbusiness Density Forecasting
9892,116446302,521.0,,6,22,/mikhailkhomenko1/spatial-regression-analysis-approach,GoDaddy - Microbusiness Density Forecasting
9893,119876801,38.0,,1,11,/jaewook704/godaddy-last-value-prediction,GoDaddy - Microbusiness Density Forecasting
9894,121921920,523.0,,0,0,/smarisolsanchez/notebook-model-randomforestregressor,GoDaddy - Microbusiness Density Forecasting
9895,120179789,76.0,,0,7,/asimadnan/darts-catboost-beginner-friendly-1-577-pl,GoDaddy - Microbusiness Density Forecasting
9896,122096490,145.0,,1,0,/tigersong2021/encoder-decoder,GoDaddy - Microbusiness Density Forecasting
9897,119873702,296.0,,11,58,/jasonczh/new-census-knn-xgb-lgbm-cat-lb-1-4121,GoDaddy - Microbusiness Density Forecasting
9898,116846620,551.0,,0,2,/narendra/godaddy-eda,GoDaddy - Microbusiness Density Forecasting
9899,114029989,32.0,,12,71,/titericz/giba-xgb-baseline-v1,GoDaddy - Microbusiness Density Forecasting
9900,114255440,273.0,,0,5,/konradb/starter-with-validation,GoDaddy - Microbusiness Density Forecasting
9901,118669119,566.0,,1,1,/ryo1993/godaddy-eda002-tscluster,GoDaddy - Microbusiness Density Forecasting
9902,133885026,19.0,,0,6,/librauee/3-8991-19th-train-and-infer-code,GoDaddy - Microbusiness Density Forecasting
9903,129641945,581.0,,0,1,/vinitkp/eda-r-arima-others,GoDaddy - Microbusiness Density Forecasting
9904,118789903,130.0,,0,2,/namgalielei/godaddy-seq-models,GoDaddy - Microbusiness Density Forecasting
9905,121294441,81.0,,0,0,/ramkapil/gd-mbd-6-0,GoDaddy - Microbusiness Density Forecasting
9906,114290967,626.0,,2,4,/lonnieqin/microbusiness-density-forecasting-with-prophet,GoDaddy - Microbusiness Density Forecasting
9907,114263408,179.0,,2,3,/andreierofeev/exponentional-smoothing-baseline-statsforecast,GoDaddy - Microbusiness Density Forecasting
9908,114745339,536.0,,1,14,/bibanh/baseline-with-lstm,GoDaddy - Microbusiness Density Forecasting
9909,114821570,810.0,,0,9,/indranilbhattacharya/optimizing-arima-and-last-value,GoDaddy - Microbusiness Density Forecasting
9910,120399598,507.0,,1,2,/avivlevi815/simple-model-per-county,GoDaddy - Microbusiness Density Forecasting
9911,119154169,607.0,,0,3,/shionmatsuoka/improve-state-i-and-latitude-and-longitude,GoDaddy - Microbusiness Density Forecasting
9912,130229017,648.0,,4,26,/gkitchen/godaddy-active-linear-model,GoDaddy - Microbusiness Density Forecasting
9913,120217540,662.0,,0,1,/jacekpardyak/godaddy-animated-microbusiness-density-map,GoDaddy - Microbusiness Density Forecasting
9914,121482280,680.0,,0,5,/lordxerxes/godaddy-basic-prediction-with-xgboost,GoDaddy - Microbusiness Density Forecasting
9915,117407626,747.0,,0,7,/kittlein/validation-on-4-last-months-smape-2-36,GoDaddy - Microbusiness Density Forecasting
9916,130706854,639.0,,0,0,/annabujniewicz/godaddyxgboost,GoDaddy - Microbusiness Density Forecasting
9917,121098887,706.0,,0,0,/rolerik/godaddy-data-preparation-and-base-model,GoDaddy - Microbusiness Density Forecasting
9918,118592866,743.0,,3,1,/sireesh/vanilla-xgboost-featureextraction-lb2-34,GoDaddy - Microbusiness Density Forecasting
9919,119837475,132.0,,4,38,/nin7a1/new-better-xgb-baseline-1-4308,GoDaddy - Microbusiness Density Forecasting
9920,121124907,745.0,,1,9,/rickpack/r-version-new-last-value-baseline-1-4631,GoDaddy - Microbusiness Density Forecasting
9921,116139455,628.0,,0,0,/toma0624/eda-of-train-data,GoDaddy - Microbusiness Density Forecasting
9922,118291673,629.0,,4,31,/brendanartley/6-external-datasets,GoDaddy - Microbusiness Density Forecasting
9923,121885397,794.0,,0,3,/renatoreggiani/prophet-hptunning,GoDaddy - Microbusiness Density Forecasting
9924,114926729,772.0,,4,16,/xxbxyae/auto-arima-model-baseline-with-r,GoDaddy - Microbusiness Density Forecasting
9925,114868106,822.0,,0,4,/bhushanborude/godaddy-data-analysis,GoDaddy - Microbusiness Density Forecasting
9926,135442750,836.0,,1,2,/senseiwhocodes/godaddy-microbusiness-forecasting-top-24,GoDaddy - Microbusiness Density Forecasting
9927,122128440,876.0,,3,17,/egorphysics/auto-arima-baseline-model,GoDaddy - Microbusiness Density Forecasting
9928,114941947,1040.0,,0,3,/mohamedmagdy11/microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
9929,115597139,903.0,,0,0,/jaloeffe92/go-daddy-datapreparation,GoDaddy - Microbusiness Density Forecasting
9930,114724521,990.0,,5,32,/oumouhouh/first-submission-1-09-seasonal-model,GoDaddy - Microbusiness Density Forecasting
9931,120738300,964.0,,11,60,/alejopaullier/clustering-time-series-with-tsne,GoDaddy - Microbusiness Density Forecasting
9932,115051128,996.0,,5,21,/cv13j0/micro-business-density-forecasting-starter-gbdt,GoDaddy - Microbusiness Density Forecasting
9933,115568591,993.0,3.9740659824936353,0,4,/ashokkumargarain/notebookc9cdcf0867,GoDaddy - Microbusiness Density Forecasting
9934,121087757,858.0,,0,2,/sidiest/go-daddy,GoDaddy - Microbusiness Density Forecasting
9935,117134197,1024.0,,3,24,/peopletrees/univariate-times-series-analysis,GoDaddy - Microbusiness Density Forecasting
9936,116978593,1528.0,,0,2,/lalitchudal/theta-model-lb1-36,GoDaddy - Microbusiness Density Forecasting
9937,115307704,1123.0,,0,9,/pyaephyoaung/godaddy-competition,GoDaddy - Microbusiness Density Forecasting
9938,121246686,1086.0,,0,0,/joylulu3/logtarget,GoDaddy - Microbusiness Density Forecasting
9939,119294871,1139.0,,0,9,/sijovm/visualization-abnormal-densities-blacklists,GoDaddy - Microbusiness Density Forecasting
9940,115522370,1132.0,,0,1,/redbear2014/an-xgb-baseline,GoDaddy - Microbusiness Density Forecasting
9941,115205604,1140.0,,2,3,/andreaschandra/godaddy-exploratory-on-geo-ts-and-census-data,GoDaddy - Microbusiness Density Forecasting
9942,114059768,1161.0,,0,15,/prabhanjanjadhav/gd-mdf-randomforest-baseline,GoDaddy - Microbusiness Density Forecasting
9943,116423534,1166.0,,9,50,/byungeunhwang/better-xgb-baseline-with-comments-added,GoDaddy - Microbusiness Density Forecasting
9944,114051780,1171.0,,0,4,/erenakbulut/eda-pandasprofiling-missingno,GoDaddy - Microbusiness Density Forecasting
9945,114894638,1187.0,,1,4,/matheusdias1996/xgboost-cv-1-56-external-data,GoDaddy - Microbusiness Density Forecasting
9946,115069846,1193.0,,4,18,/prachi13/micro-business-forecasting,GoDaddy - Microbusiness Density Forecasting
9947,117310862,1277.0,,13,141,/datark1/detailed-eda-problem-decomposition-gis,GoDaddy - Microbusiness Density Forecasting
9948,118718703,1315.0,,0,3,/tomonorisasaki/simple-eda-without-prediction,GoDaddy - Microbusiness Density Forecasting
9949,116592276,1317.0,7.832761449678366,0,1,/saraswatitiwari/godaddy-microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
9950,115615866,932.0,,1,4,/xiaolizi123/double-exponential-smooth,GoDaddy - Microbusiness Density Forecasting
9951,121166002,1442.0,3.9665929709573575,0,18,/masterofdeception/better-xgb-baseline,GoDaddy - Microbusiness Density Forecasting
9952,118575319,1452.0,,0,23,/finlay/godaddy-muti-step-method,GoDaddy - Microbusiness Density Forecasting
9953,114964154,1619.0,,0,4,/josipvrdoljak/ema-test,GoDaddy - Microbusiness Density Forecasting
9954,119188606,1037.0,,0,1,/drenns/gd01-godaddy-basic-eda-and-simplest-model,GoDaddy - Microbusiness Density Forecasting
9955,114557290,1874.0,,0,8,/maximeperez/go-daddy-xgboost,GoDaddy - Microbusiness Density Forecasting
9956,114023262,1718.0,7.6008532974009615,2,15,/ttahara/gd-mdf-simple-lgbm-baseline,GoDaddy - Microbusiness Density Forecasting
9957,114947785,1762.0,,0,5,/pranay20485/county-neighbors,GoDaddy - Microbusiness Density Forecasting
9958,115088797,1768.0,,2,15,/sathyakrishnan12/timeseriessplit-separate-models-lb-1-092,GoDaddy - Microbusiness Density Forecasting
9959,115703688,1775.0,,35,151,/kimtaehun/complete-baseline-code-with-various-ml-model,GoDaddy - Microbusiness Density Forecasting
9960,115518204,1784.0,,0,11,/rdboyes/understanding-the-task-and-simple-sub-r,GoDaddy - Microbusiness Density Forecasting
9961,115498177,1787.0,3.9740659824936353,0,5,/rishabhiitbhu/the-godaddy-eda-storyline,GoDaddy - Microbusiness Density Forecasting
9962,119297460,2397.0,,0,12,/mertkra/godaddy-randomforest-census,GoDaddy - Microbusiness Density Forecasting
9963,115908430,1824.0,,0,3,/azizullah444/godaddy-microbusiness-density-forecasting-sktime,GoDaddy - Microbusiness Density Forecasting
9964,118036178,1849.0,,0,1,/ozmendelsohn/d-school-ts,GoDaddy - Microbusiness Density Forecasting
9965,118086749,1852.0,,0,16,/jiayii1/godaddy-density-forecasting,GoDaddy - Microbusiness Density Forecasting
9966,118853233,1867.0,,6,22,/ch124uec/visualizing-micro-businesses-trends-with-plotly,GoDaddy - Microbusiness Density Forecasting
9967,119949108,1883.0,3.9740659824936353,0,6,/chandanarprasad/microbusiness-density-forecasting-eda-plots-naive,GoDaddy - Microbusiness Density Forecasting
9968,131507013,1715.0,,0,2,/yangkenwu/ml-ts-forecast-stats-go-daddy-micro-business,GoDaddy - Microbusiness Density Forecasting
9969,115284723,1636.0,,0,6,/dann12/check-missing-and-plot-as-calendar,GoDaddy - Microbusiness Density Forecasting
9970,115163371,1903.0,,7,39,/jackwen6/svm-prediction,GoDaddy - Microbusiness Density Forecasting
9971,120224305,1008.0,,0,4,/maciejkrl/n-hits-1-0945-acc-working-godaddycomp,GoDaddy - Microbusiness Density Forecasting
9972,118308809,1918.0,,0,7,/raimohaikari/linear-regression-baseline-using-r,GoDaddy - Microbusiness Density Forecasting
9973,142589690,1905.0,,5,28,/arunklenin/godaddy-census-data-extrapolation-2022-2023,GoDaddy - Microbusiness Density Forecasting
9974,114837262,1692.0,,0,10,/noir3747/micro-business-forecasting,GoDaddy - Microbusiness Density Forecasting
9975,115443141,1921.0,,0,2,/shannontan/cluster-with-dtw-distance,GoDaddy - Microbusiness Density Forecasting
9976,115585732,1963.0,,0,0,/omxpress/stark-ver,GoDaddy - Microbusiness Density Forecasting
9977,131981908,1974.0,,0,5,/shamikrana/microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
9978,117962896,1626.0,,3,28,/jth3000/eda-for-godaddy-microbusiness-forecasting,GoDaddy - Microbusiness Density Forecasting
9979,115356775,1646.0,7.597981367421434,1,9,/senapatirajesh/go-daddy-eda-timeseriesforecasting,GoDaddy - Microbusiness Density Forecasting
9980,115424387,2026.0,,0,16,/masahiroichigo/godaddy-microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
9981,118372839,1005.0,,6,28,/snnclsr/gluonts-deepar-model-with-validation,GoDaddy - Microbusiness Density Forecasting
9982,118022850,2044.0,,1,12,/chitresh62001/time-series-using-arima-for-beginners,GoDaddy - Microbusiness Density Forecasting
9983,115706115,2075.0,,0,1,/tejaswar/godaddy-sma,GoDaddy - Microbusiness Density Forecasting
9984,115527422,2004.0,,1,6,/brassmonkey381/godaddy-mdf-starter,GoDaddy - Microbusiness Density Forecasting
9985,115138040,2089.0,,1,2,/sumandey/autots-exponential-smoothing-forecast,GoDaddy - Microbusiness Density Forecasting
9986,118335386,2085.0,4.248357759423335,0,5,/anvdeikoptsev/microbusiness-forecasting-randomforest,GoDaddy - Microbusiness Density Forecasting
9987,115110476,2096.0,,0,2,/stpeteishii/microbusiness-density-histplot,GoDaddy - Microbusiness Density Forecasting
9988,121827702,2116.0,4.321993128869252,0,1,/cheekati1/godaddy-microbusiness-rfregressor-census,GoDaddy - Microbusiness Density Forecasting
9989,114867684,2152.0,4.352442300537575,0,5,/danielbion/auto-arima-starter,GoDaddy - Microbusiness Density Forecasting
9990,114867684,2152.0,4.352442300537575,0,5,/danielbion/auto-arima-starter,GoDaddy - Microbusiness Density Forecasting
9991,121849884,2102.0,4.615226737485995,0,8,/yuriao/microbusiness-density-prediction-with-var,GoDaddy - Microbusiness Density Forecasting
9992,116908874,2167.0,,1,14,/takafumitakizawa/godaddy-1st-eda,GoDaddy - Microbusiness Density Forecasting
9993,120470780,2081.0,,0,7,/fuad0857/forecasting-with-tensorflow,GoDaddy - Microbusiness Density Forecasting
9994,114670817,2182.0,4.524239564911883,1,10,/osamurai/baseline-kalman-filter-bayesian-optimization,GoDaddy - Microbusiness Density Forecasting
9995,120124352,987.0,4.618879393385074,0,0,/brayanarturonava/micro-business-forecasting-v-2,GoDaddy - Microbusiness Density Forecasting
9996,118705302,2148.0,,0,0,/bcruise/godaddy-mbd-state-by-state-eda,GoDaddy - Microbusiness Density Forecasting
9997,116725430,2181.0,4.711787289798612,1,3,/hscosta/dask-distributed-prophet-linear,GoDaddy - Microbusiness Density Forecasting
9998,115728522,2168.0,,0,2,/mohammedmunshif/go-daddy-forecasting,GoDaddy - Microbusiness Density Forecasting
9999,114214787,2210.0,4.919572241895128,1,5,/antonbushuiev/sarima-baseline,GoDaddy - Microbusiness Density Forecasting
10000,120774189,2229.0,,0,0,/rjconstable/prophet-pyspark-time-series-forecasting-godaddy,GoDaddy - Microbusiness Density Forecasting
10001,114684921,2257.0,5.308022398801449,1,4,/kavinsubramani/a-mad-way,GoDaddy - Microbusiness Density Forecasting
10002,114980847,2279.0,,2,13,/justinmustaine/spatiotemporal-analysis,GoDaddy - Microbusiness Density Forecasting
10003,122940540,2212.0,,0,5,/heinzsch/time-series-analysis-godaddycompetition,GoDaddy - Microbusiness Density Forecasting
10004,119178462,2283.0,,1,4,/serkanoral/ridge,GoDaddy - Microbusiness Density Forecasting
10005,115144837,2342.0,,0,0,/navinseab/basic-analysis,GoDaddy - Microbusiness Density Forecasting
10006,120686962,2414.0,,0,3,/saadelkouari/godaddy-transformer,GoDaddy - Microbusiness Density Forecasting
10007,117072916,2267.0,,33,91,/imnaho/eda-predict,GoDaddy - Microbusiness Density Forecasting
10008,114202987,2277.0,7.597981367421434,8,31,/nasere/go-daddy-time-series-model-techniques,GoDaddy - Microbusiness Density Forecasting
10009,114727191,2308.0,7.627177450096152,0,1,/maxjul/randomforestregressor-maiko-beats-0-997,GoDaddy - Microbusiness Density Forecasting
10010,119628714,2315.0,7.92840181996359,0,12,/piyushm28/go-daddy-vif-basic-regression,GoDaddy - Microbusiness Density Forecasting
10011,116495283,2319.0,,0,1,/tangelus/godaddy-competition-regression-baseline,GoDaddy - Microbusiness Density Forecasting
10012,116914308,2382.0,,2,8,/rcbhatt/godaddy-microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
10013,118300846,2345.0,8.390001032173384,0,1,/shahalthayyil/godaddy,GoDaddy - Microbusiness Density Forecasting
10014,120635753,2464.0,,1,0,/bubbleup/basic-eda-competition-data,GoDaddy - Microbusiness Density Forecasting
10015,121371470,2440.0,9.496832203961729,0,2,/rohitdileep/godaddy-micro-business-forecasting-using-tf-linear,GoDaddy - Microbusiness Density Forecasting
10016,121407599,2423.0,,0,3,/loycelorenzo/go-daddy-using-fast-ai,GoDaddy - Microbusiness Density Forecasting
10017,144908159,2494.0,,0,1,/mehmetutkubala/godaddy-microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
10018,118378524,2477.0,10.419891774235056,0,3,/devanshu12122/godaddy-xgboost-baseline,GoDaddy - Microbusiness Density Forecasting
10019,120798498,2532.0,,0,0,/billykoech/godaddy-comp,GoDaddy - Microbusiness Density Forecasting
10020,121737440,2530.0,14.657090518783727,0,5,/muhriddinmalik/microbusiness-density-prediction,GoDaddy - Microbusiness Density Forecasting
10021,116544168,2524.0,,0,11,/refat094/godaddy-microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
10022,118638618,2542.0,,4,5,/rohithmahadevan/predicting-microdensity-using-random-forest,GoDaddy - Microbusiness Density Forecasting
10023,125493085,2555.0,,0,3,/yuujapan/ver2-godaddy-microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
10024,120648884,2595.0,18.620541338279327,0,5,/mahmoudatef94/godaddy-microbusiness-density-forecasting,GoDaddy - Microbusiness Density Forecasting
10025,122732363,2666.0,,0,1,/olgashevtsova/microbusiness-forecasting-rf-log-last-value,GoDaddy - Microbusiness Density Forecasting
10026,114552255,3313.0,42.42558235560311,0,4,/nikhilsharma24/quick-r-submission,GoDaddy - Microbusiness Density Forecasting
10027,115338712,2706.0,51.76883863146714,2,2,/foocheechuan/lgbm-bayessearch-baselinemodel,GoDaddy - Microbusiness Density Forecasting
10028,119516935,2708.0,52.25536640423052,0,0,/zizh3ngzhang/godaddy-ml-analysis,GoDaddy - Microbusiness Density Forecasting
10029,115572269,2774.0,59.91174735654429,0,2,/sanandachowdhury/godaddy,GoDaddy - Microbusiness Density Forecasting
10030,115572269,2774.0,59.91174735654429,0,2,/sanandachowdhury/godaddy,GoDaddy - Microbusiness Density Forecasting
10031,125046889,2794.0,,0,6,/younaniskander/12345go,GoDaddy - Microbusiness Density Forecasting
10032,122587727,2802.0,,0,4,/bukolaajayi/go-daddy-competition-project,GoDaddy - Microbusiness Density Forecasting
10033,116743285,2828.0,,0,0,/simmonsbeds/eda-on-training-dataset,GoDaddy - Microbusiness Density Forecasting
10034,118637738,2830.0,,1,5,/rahulmagar33/microbusiness-density-prediction,GoDaddy - Microbusiness Density Forecasting
10035,129609349,2873.0,,0,4,/arjuna111/godaddy-nn,GoDaddy - Microbusiness Density Forecasting
10036,121211145,2882.0,71.24411504275072,0,0,/jessicarrr/notebook34663c112f,GoDaddy - Microbusiness Density Forecasting
10037,118184528,3335.0,,0,9,/shuvojitdas/eda-7-different-models,GoDaddy - Microbusiness Density Forecasting
10038,115396227,11.0,0.56211179823562,1,20,/samuelcortinhas/ps-s3e1-house-price-prediction,Regression with a Tabular California Housing Dataset
10039,115521280,14.0,0.5585252708108457,1,5,/cyrilbourgeois/autogluon,Regression with a Tabular California Housing Dataset
10040,115521280,14.0,0.5585252708108457,1,5,/cyrilbourgeois/autogluon,Regression with a Tabular California Housing Dataset
10041,115770756,9.0,,0,7,/imeintanis/playground-2023-01-lofo-feature-importance,Regression with a Tabular California Housing Dataset
10042,119065941,26.0,,26,91,/phongnguyen1/feature-engineering-with-coordinates,Regression with a Tabular California Housing Dataset
10043,115931959,25.0,,17,48,/alexandershumilin/playground-series-s3-e1-catboost-xgboost-lgbm,Regression with a Tabular California Housing Dataset
10044,115829924,28.0,0.5589446400754446,50,77,/khashayarrahimi94/pse1-most-simple-approach-just-3-functions,Regression with a Tabular California Housing Dataset
10045,115730388,29.0,0.5665483044196709,4,11,/erenakbulut/eda-catboost-predictions-data-balancing,Regression with a Tabular California Housing Dataset
10046,115737986,16.0,0.5657988671328832,0,3,/omarvivas/lgbm-pgs-v1,Regression with a Tabular California Housing Dataset
10047,115911101,39.0,,4,14,/directt/playground-s03e01-top-5-catboost-lgbm,Regression with a Tabular California Housing Dataset
10048,115529904,41.0,,23,44,/mattop/playground-series-s3-e1-eda-pca,Regression with a Tabular California Housing Dataset
10049,115778851,13.0,,1,8,/craigmthomas/plays1e1-eda-models,Regression with a Tabular California Housing Dataset
10050,117513177,87.0,,5,11,/chunweishen/eda-simple-model-original-data-submission,Regression with a Tabular California Housing Dataset
10051,138938855,99.0,,0,3,/cid007/california-house-price-prediction,Regression with a Tabular California Housing Dataset
10052,115954607,100.0,0.5655031467539042,2,6,/samu2505/histgradient-baseline,Regression with a Tabular California Housing Dataset
10053,115627307,59.0,,0,2,/realtimshady/lgbm-baseline,Regression with a Tabular California Housing Dataset
10054,115726237,63.0,,0,1,/vitaliyshpak/ps-s3e1-xgb-lgmb-catboost-eda,Regression with a Tabular California Housing Dataset
10055,115468090,64.0,,0,9,/prabhanjanjadhav/pss3e1-all-regression-models,Regression with a Tabular California Housing Dataset
10056,115345810,65.0,0.5690459316324697,0,2,/kojimar/lightgbm-baseline,Regression with a Tabular California Housing Dataset
10057,115839699,35.0,,1,3,/dimitriosfoteinos/feature-engineering-distance-from-the-sea,Regression with a Tabular California Housing Dataset
10058,119250638,90.0,,6,29,/oscarm524/ps-s3-ep1-eda-fe-modeling,Regression with a Tabular California Housing Dataset
10059,121283802,125.0,,0,3,/tmleyncodes/distance-to-key-locations,Regression with a Tabular California Housing Dataset
10060,117085066,137.0,,1,12,/nishantborkar/xgbboost-for-best-accuracy,Regression with a Tabular California Housing Dataset
10061,115635302,70.0,,1,2,/janniklasottow/simple-catboost-model-s3e01,Regression with a Tabular California Housing Dataset
10062,115738156,132.0,0.5543646912854934,8,10,/danielliao/eda-training-a-first-model-submission,Regression with a Tabular California Housing Dataset
10063,121206191,104.0,,19,68,/soumendraprasad/eda-handling-skewness-outlier-baseline,Regression with a Tabular California Housing Dataset
10064,115664223,97.0,0.7021051844515038,2,13,/asimple/eda-baseline-playground-series,Regression with a Tabular California Housing Dataset
10065,115641014,107.0,,2,5,/anurag629/tabular-regression-with-different-model,Regression with a Tabular California Housing Dataset
10066,115585771,116.0,0.5683333931182084,4,8,/docxian/pg-season-3-ep-1-visual-starter,Regression with a Tabular California Housing Dataset
10067,115878041,109.0,,3,5,/tharunnayak14/ps-s3-e1-eda-training,Regression with a Tabular California Housing Dataset
10068,115541545,144.0,,0,0,/shubhamkumarvaish/ps-s3e1-coordinates-small-change,Regression with a Tabular California Housing Dataset
10069,115829689,105.0,0.5550623589288034,6,14,/satoshiss/ps-s3e1-simple-solution-original-data,Regression with a Tabular California Housing Dataset
10070,115545399,158.0,0.5603630721218977,10,45,/soupmonster/simple-lightgbm-baseline,Regression with a Tabular California Housing Dataset
10071,115518518,130.0,,0,2,/sejoongkim/s03e01-linear-and-non-linear-regression,Regression with a Tabular California Housing Dataset
10072,115365897,164.0,0.5613297326542931,9,17,/wuzimu/adding-sklearn-data-helps-a-lot,Regression with a Tabular California Housing Dataset
10073,116141542,168.0,0.5624622845050259,2,10,/sharvalishinde/pss3e1-histgradientboost-lbgm-xgboost-ensembling,Regression with a Tabular California Housing Dataset
10074,118137206,154.0,,0,4,/sukantabasu/prediction-of-california-housing-prices-by-flaml,Regression with a Tabular California Housing Dataset
10075,115731255,163.0,0.5596857519815703,3,5,/bernhardklinger/automl-baseline,Regression with a Tabular California Housing Dataset
10076,115497837,204.0,,2,5,/alexeylyamzin/playground-s3e1-ridge-baseline-deepchecks-eda,Regression with a Tabular California Housing Dataset
10077,115935978,176.0,,0,21,/predaddict/conformal-predictive-distributions-pss3-e1,Regression with a Tabular California Housing Dataset
10078,115456098,183.0,,55,121,/radek1/eda-training-a-first-model-submission,Regression with a Tabular California Housing Dataset
10079,116641022,194.0,,1,0,/oenvespa/playground-series-s3-ep1,Regression with a Tabular California Housing Dataset
10080,115365482,169.0,,1,11,/ashvanths/eda-fe-basics-tps-2k23,Regression with a Tabular California Housing Dataset
10081,115971805,140.0,0.5580646428125365,2,3,/jackysywk/my-first-participation-ever,Regression with a Tabular California Housing Dataset
10082,115838302,197.0,,0,6,/kirillka95/ps-s3e01-checking-how-original-data-helps,Regression with a Tabular California Housing Dataset
10083,115852600,224.0,0.5580044015126585,4,7,/cv13j0/pss-3-episode-1-a-weekend-model,Regression with a Tabular California Housing Dataset
10084,115423068,282.0,0.5581890557334754,3,9,/mukaseevru/ps-s3e1-lama-lightautoml-extra-data,Regression with a Tabular California Housing Dataset
10085,115423068,282.0,0.5581890557334754,3,9,/mukaseevru/ps-s3e1-lama-lightautoml-extra-data,Regression with a Tabular California Housing Dataset
10086,115365253,162.0,0.5676959206176287,0,7,/shrutisaxena/ps-s3-e1-california-house-price-prediction,Regression with a Tabular California Housing Dataset
10087,115365253,162.0,0.5676959206176287,0,7,/shrutisaxena/ps-s3-e1-california-house-price-prediction,Regression with a Tabular California Housing Dataset
10088,115675807,174.0,,0,2,/extremesarova/0-concise-eda-ps-s3e1,Regression with a Tabular California Housing Dataset
10089,115854809,177.0,,0,1,/cchia3/syntheticdata,Regression with a Tabular California Housing Dataset
10090,115925086,232.0,,3,2,/edouardo/mirando-al-mar,Regression with a Tabular California Housing Dataset
10091,115563067,178.0,,0,3,/stevesimons/pss3e1-regression-housing-pycaret,Regression with a Tabular California Housing Dataset
10092,115598658,213.0,0.5773315153618803,0,1,/priyanagda/tps-jan-23-xgboost-baseline-external-data,Regression with a Tabular California Housing Dataset
10093,115738404,159.0,0.6363200019656774,13,34,/jacoporepossi/fastai-baseline-ensembling,Regression with a Tabular California Housing Dataset
10094,115619718,219.0,,0,3,/jonblanchard/tpsjan23-1-folium-lat-lon-plot,Regression with a Tabular California Housing Dataset
10095,115790347,228.0,0.5595552567313491,10,27,/anubhavgoyal10/ps-season-3-e1-california-housing-price,Regression with a Tabular California Housing Dataset
10096,115617411,234.0,0.5618882065952285,1,8,/shiv7080/finally-i-started,Regression with a Tabular California Housing Dataset
10097,115440162,240.0,,0,4,/gauravmalik26/lightgbm-baseline-submission-cv-score-0-564,Regression with a Tabular California Housing Dataset
10098,115557632,242.0,,1,6,/killswitch10/playground-s3-e1-lgbmregressor,Regression with a Tabular California Housing Dataset
10099,115749977,206.0,,6,7,/khawajaabaidullah/a-simple-yet-effective-xgboost-baseline,Regression with a Tabular California Housing Dataset
10100,115626431,248.0,,2,2,/trushatalati/playground-s3e1-linear-regression-lgbm,Regression with a Tabular California Housing Dataset
10101,115536823,271.0,0.5903851105383359,0,6,/belati/psse1-complete-eda-and-feature-engineering,Regression with a Tabular California Housing Dataset
10102,115795225,278.0,,6,11,/donjoeml/catboost-hyperparameter-tuning,Regression with a Tabular California Housing Dataset
10103,115608051,327.0,0.5634803345373447,1,6,/sfktrkl/tps-jan-2023,Regression with a Tabular California Housing Dataset
10104,117238969,214.0,,0,7,/inaciobr/ps-s03e01-geopandas-eda-knn-catboost,Regression with a Tabular California Housing Dataset
10105,115935165,398.0,0.5760425705421068,9,8,/casati8/kaggle-s3exp1-fastai,Regression with a Tabular California Housing Dataset
10106,115469041,339.0,,5,6,/faelk8/eda-lgbmregressor,Regression with a Tabular California Housing Dataset
10107,115406087,286.0,0.5777785426534308,2,31,/furkannakdagg/pycaret-detailed-eda-first-submission,Regression with a Tabular California Housing Dataset
10108,115894733,268.0,,0,6,/nnjjpp/eda-and-baseline-playground-series-s3e1,Regression with a Tabular California Housing Dataset
10109,115428838,399.0,0.5667128665442065,2,33,/kimtaehun/simple-lgbm-with-sklearn-pipeline-randomcv,Regression with a Tabular California Housing Dataset
10110,115446306,292.0,0.5672678376947093,4,15,/hasanbasriakcay/pss3-1-insightful-eda-new-lib-featdist,Regression with a Tabular California Housing Dataset
10111,115446306,292.0,0.5672692308403011,4,15,/hasanbasriakcay/pss3-1-insightful-eda-new-lib-featdist,Regression with a Tabular California Housing Dataset
10112,115446306,292.0,0.5672667764924219,4,15,/hasanbasriakcay/pss3-1-insightful-eda-new-lib-featdist,Regression with a Tabular California Housing Dataset
10113,115496598,295.0,,6,5,/abdoulayebalde/eda-model-score-0-56837,Regression with a Tabular California Housing Dataset
10114,115945609,302.0,0.5680346858463948,1,3,/barbagrande007/bbg007-s3e1,Regression with a Tabular California Housing Dataset
10115,115566321,357.0,0.603230206462238,2,5,/datascientistsohail/ps-s03ep01-randomforestreg,Regression with a Tabular California Housing Dataset
10116,115555104,333.0,0.5704122032227148,1,3,/ashokkumargarain/notebookec300f7062,Regression with a Tabular California Housing Dataset
10117,115646827,352.0,0.568934602926226,3,11,/agorinenko/s3e01-stack-catboost-lightgbm-xgboost-and-more,Regression with a Tabular California Housing Dataset
10118,115813733,356.0,,0,0,/nhopet/playgroundss3e1-map,Regression with a Tabular California Housing Dataset
10119,115338770,359.0,,0,6,/gauravduttakiit/pss3e1-autoviz,Regression with a Tabular California Housing Dataset
10120,115813659,326.0,,10,33,/gracehephzibahm/25-base-models-ensemble-techniques-beginners,Regression with a Tabular California Housing Dataset
10121,118474459,441.0,,13,27,/vshantam/playground-s03e01-eda-geospatial-fe-xgboost,Regression with a Tabular California Housing Dataset
10122,115398359,371.0,0.5713254706219191,1,8,/takshpanchal/ps-s3-e1-simple-baseline,Regression with a Tabular California Housing Dataset
10123,116257751,369.0,,1,8,/kajubadaam/simple-housing-catboost,Regression with a Tabular California Housing Dataset
10124,115357564,386.0,0.572985600229009,4,8,/mohammadkashifunique/eda-training-predictions-xgb,Regression with a Tabular California Housing Dataset
10125,115787792,425.0,0.5759883299255689,5,10,/kaushalkrishna2000/playground-competition-notebook,Regression with a Tabular California Housing Dataset
10126,115787792,425.0,0.5748902045196214,5,10,/kaushalkrishna2000/playground-competition-notebook,Regression with a Tabular California Housing Dataset
10127,115787792,425.0,0.5757270592201689,5,10,/kaushalkrishna2000/playground-competition-notebook,Regression with a Tabular California Housing Dataset
10128,115481316,415.0,,3,4,/minaxiwadgure/ps-s3-e1-eda,Regression with a Tabular California Housing Dataset
10129,115821913,430.0,,0,0,/mikhailzemskov/california-housing-eda-and-simple-model,Regression with a Tabular California Housing Dataset
10130,115886110,497.0,,11,20,/hikmatullahmohammadi/playground-s3e1-california-house,Regression with a Tabular California Housing Dataset
10131,116857446,439.0,,0,0,/mirmozavr/dataframe-size-reducer,Regression with a Tabular California Housing Dataset
10132,115484780,442.0,,0,4,/badice/playground-series-s3-e1,Regression with a Tabular California Housing Dataset
10133,115602190,411.0,,0,1,/escasinas/eda-ps-season-3-episode-1,Regression with a Tabular California Housing Dataset
10134,115422178,478.0,,0,2,/arslankas/histgradientboostingregressor,Regression with a Tabular California Housing Dataset
10135,115841004,472.0,0.5779810647551589,2,5,/reymaster/playground-s3e1-xgboost-reverse-geocoding,Regression with a Tabular California Housing Dataset
10136,115399751,454.0,,0,1,/shubhambedi/playground-series-s03e01,Regression with a Tabular California Housing Dataset
10137,116038010,465.0,,5,21,/tylerjthomas9/julia-xgboost-baseline-tps-s3e1,Regression with a Tabular California Housing Dataset
10138,115924243,484.0,0.5787550907426787,3,5,/aassie/s3e1-r-my-very-first-kaggle-notebook-final,Regression with a Tabular California Housing Dataset
10139,115920162,451.0,0.581090400785348,1,1,/alessandrozanette/playground-series-s3e1-xgboost-cv,Regression with a Tabular California Housing Dataset
10140,115850883,462.0,,1,6,/lucabasa/tpc-season-3-episode-1,Regression with a Tabular California Housing Dataset
10141,115419539,463.0,,11,28,/mpwolke/california-playground-ep-1,Regression with a Tabular California Housing Dataset
10142,115874503,461.0,,0,1,/shivam2111/catboost-pgs-s3e1,Regression with a Tabular California Housing Dataset
10143,115445833,475.0,0.7003852974014482,0,2,/ananyasingh008/playground-series-season-3-episode-1,Regression with a Tabular California Housing Dataset
10144,115766469,509.0,,6,10,/kim145/eda-all-regressors,Regression with a Tabular California Housing Dataset
10145,115511311,510.0,0.5842848784405501,0,0,/djwerterrichmond/parameter-tuning,Regression with a Tabular California Housing Dataset
10146,115659458,513.0,0.5862799779662009,2,5,/amoghgarg20/playground-s3e1-eda-ensemble,Regression with a Tabular California Housing Dataset
10147,116002153,523.0,,0,10,/mkr9395/eda-xgboost-californiahousing,Regression with a Tabular California Housing Dataset
10148,115496696,530.0,,0,5,/sarthak333/tps-jan-baseline,Regression with a Tabular California Housing Dataset
10149,115804191,552.0,0.5941756255887006,0,2,/ted0071/ps3e1-eda-models,Regression with a Tabular California Housing Dataset
10150,115497616,561.0,0.7250669709060769,0,5,/tracyporter/play-3-1-lin-reg,Regression with a Tabular California Housing Dataset
10151,115466158,546.0,0.6078156135949674,2,4,/manahid/1st-notebook-trying-a-random-forest-model,Regression with a Tabular California Housing Dataset
10152,116556541,576.0,,0,1,/sagar2168616/california-house-predictions-xgboost-regressor,Regression with a Tabular California Housing Dataset
10153,115830840,575.0,0.6272625519002025,0,3,/mukeshrajm/understanding-the-regression-problem,Regression with a Tabular California Housing Dataset
10154,115487427,580.0,,0,5,/choisoonsin/eda-handling-outlier-randomforest,Regression with a Tabular California Housing Dataset
10155,115493666,584.0,0.6228365083471553,0,2,/aaronjones32/predicting-house-valuation-with-neural-networks,Regression with a Tabular California Housing Dataset
10156,115946265,582.0,,6,15,/behroozsohrabi/playground-nn-estimator-jan-2023,Regression with a Tabular California Housing Dataset
10157,115888644,627.0,,0,1,/pranayrishith16/playground-series-s3e1-how-not-to-code,Regression with a Tabular California Housing Dataset
10158,115497008,660.0,0.7941622875647381,0,5,/telahe/playground-s03e01,Regression with a Tabular California Housing Dataset
10159,115497008,660.0,0.7941622875647381,0,5,/telahe/playground-s03e01,Regression with a Tabular California Housing Dataset
10160,115416379,633.0,,0,0,/rajsengo/s3-e1-r-for-beginners,Regression with a Tabular California Housing Dataset
10161,115451821,634.0,0.7248821589695498,2,3,/ramendrachaudhary/playground-series-season-3-episode-1,Regression with a Tabular California Housing Dataset
10162,115737462,687.0,2.363789988659573,1,1,/sanjaylalwani/chd-eda,Regression with a Tabular California Housing Dataset
10163,120955433,1.0,,6,20,/eamini/firstplacenb-wids-2023,WiDS Datathon 2023
10164,119697510,2.0,,0,0,/lhagiimn/wids-2023-datathon-datapreprocessing,WiDS Datathon 2023
10165,140988125,5.0,,11,80,/usharengaraju/wids2023-tabnetregressor,WiDS Datathon 2023
10166,121580250,6.0,0.6295760782749642,0,0,/bablos/6th-place-solution,WiDS Datathon 2023
10167,121580250,6.0,0.6295760782749642,0,0,/bablos/6th-place-solution,WiDS Datathon 2023
10168,121782698,7.0,,0,6,/doleh23/7th-place-code,WiDS Datathon 2023
10169,117694582,162.0,,2,21,/ducnh279/find-x-correctly-impute-7-8-missing-value-columns,WiDS Datathon 2023
10170,120504649,24.0,0.8311315250414886,0,0,/hoa18020575/catboost-s-linh,WiDS Datathon 2023
10171,116025846,37.0,,9,51,/flaviafelicioni/wids-2023-different-locations-train-test-solved,WiDS Datathon 2023
10172,115663421,35.0,,0,7,/unilageni/getting-started-catboost-baseline-score-1-356,WiDS Datathon 2023
10173,118492404,43.0,,1,6,/kinakomochi/visualization-of-elevation-and-coordinates,WiDS Datathon 2023
10174,118294222,39.0,,0,4,/anupamabidargaddi/wids-2023-eda-visualization,WiDS Datathon 2023
10175,115678568,47.0,1.180742986016394,11,53,/shrutisaxena/wids-2023-xgboost-catboost-sc-1-18,WiDS Datathon 2023
10176,115678568,47.0,1.1896073994941556,11,53,/shrutisaxena/wids-2023-xgboost-catboost-sc-1-18,WiDS Datathon 2023
10177,115678568,47.0,1.3071504728855283,11,53,/shrutisaxena/wids-2023-xgboost-catboost-sc-1-18,WiDS Datathon 2023
10178,118785460,60.0,,0,2,/yomatsu1215/wids2023-eda-correlations,WiDS Datathon 2023
10179,128348401,66.0,,0,0,/ariannebaliramsingh/wids-2023-pandalytics,WiDS Datathon 2023
10180,118281421,69.0,,2,6,/kooaslansefat/wids-2023-h2o-automl-xai,WiDS Datathon 2023
10181,116601163,262.0,1.3787483310365762,0,14,/masterofdeception/kh-nh-template-eda,WiDS Datathon 2023
10182,118487030,127.0,,0,12,/linhnguyn555/eda-time-series-and-climate-regions-analysis,WiDS Datathon 2023
10183,120150163,137.0,2.4801475559385,0,4,/kimnganngng/usingpython,WiDS Datathon 2023
10184,118335780,144.0,,0,0,/shavilyarajput/wids-datathon-2023,WiDS Datathon 2023
10185,120555485,141.0,,0,0,/hngcclth/bo-catboost,WiDS Datathon 2023
10186,119129397,157.0,1.180742986016394,0,4,/elhamalbaroudi/ds-final,WiDS Datathon 2023
10187,120300019,177.0,0.8496802607413362,1,28,/ducanger/wids-2023-catboost-regression,WiDS Datathon 2023
10188,119678295,183.0,,6,38,/nicholasdominic/wids2023-data-buddies,WiDS Datathon 2023
10189,118286175,217.0,5.321208145812281,0,4,/kuntalpal/datathon-baseline,WiDS Datathon 2023
10190,120530507,245.0,,0,0,/chengdorothy/wids2023-eda-lightgbm-rfecv-rmse-1-04,WiDS Datathon 2023
10191,115586446,277.0,,0,10,/nasere/wids2023-welcome-starter-pack,WiDS Datathon 2023
10192,119991762,302.0,,0,0,/faithnchifor/wids-datathon-2023,WiDS Datathon 2023
10193,120583898,352.0,1.222939979570712,0,0,/tianyimasf/wids-datathon-tianyi-yukyung-and-irsa,WiDS Datathon 2023
10194,116458266,358.0,,0,14,/farazrahman/combating-climate-change,WiDS Datathon 2023
10195,120761898,356.0,,0,2,/roshitab/wids-datathon-2023-catboost-regression,WiDS Datathon 2023
10196,118207124,362.0,,0,2,/kaggle7171/mstrcht-fab,WiDS Datathon 2023
10197,118357799,387.0,1.4284068356305877,3,8,/trushatalati/wids-2023-lgbm,WiDS Datathon 2023
10198,119929969,408.0,,0,0,/siddharthapant1982/weka1-wids-0dc35d,WiDS Datathon 2023
10199,121714385,430.0,,0,0,/whirleywrigs/wids-datavis,WiDS Datathon 2023
10200,117455739,419.0,1.40806863179317,15,98,/iamleonie/wids-datathon-2023-forecasting-with-lgbm,WiDS Datathon 2023
10201,120866717,452.0,1.5462153931613292,1,4,/vaishnavipatil4848/wids-datathon-lightgbm-optuna,WiDS Datathon 2023
10202,118050698,458.0,,0,4,/hamnaqaseem/data-detectives,WiDS Datathon 2023
10203,117819497,478.0,1.51116192015394,6,10,/shadowhat/join-live-predict-climate-in-wids,WiDS Datathon 2023
10204,115755974,495.0,,0,24,/mpwolke/improving-weather-forecasts-wids-2023,WiDS Datathon 2023
10205,115946698,498.0,,0,5,/stpeteishii/wids-data-predict-and-visualize-importance,WiDS Datathon 2023
10206,119486406,518.0,4.407379933153523,0,0,/patchizzymba/wids-2023-datathon,WiDS Datathon 2023
10207,119486406,518.0,4.63927807087717,0,0,/patchizzymba/wids-2023-datathon,WiDS Datathon 2023
10208,119486406,518.0,5.127176490746872,0,0,/patchizzymba/wids-2023-datathon,WiDS Datathon 2023
10209,119486406,518.0,5.56652410685953,0,0,/patchizzymba/wids-2023-datathon,WiDS Datathon 2023
10210,115578359,531.0,,1,21,/gauravduttakiit/wids-datathon-2023-lazypredict,WiDS Datathon 2023
10211,119591281,568.0,,0,0,/kir0ul/wids-datathon-2023,WiDS Datathon 2023
10212,120610241,584.0,,0,0,/ashioyajotham/wids-2023-part-1-data-cleaning,WiDS Datathon 2023
10213,119927583,603.0,,0,5,/pumpim/wids2023-dodosolutions,WiDS Datathon 2023
10214,120615599,631.0,,0,0,/malabika21guha/final-code,WiDS Datathon 2023
10215,120747822,663.0,,0,6,/aryaharde/wids-2023-data-pirates,WiDS Datathon 2023
10216,143641899,671.0,,0,0,/veronicahchege/wids-datathon-final-2aefaa,WiDS Datathon 2023
10217,119900419,697.0,,0,3,/lucialagenial/wids-23-predictions,WiDS Datathon 2023
10218,116558629,477.0,,15,69,/sergiosaharovskiy/ps-s3e2-2023-eda-and-base-pytorch-model,Binary Classification with a Tabular Stroke Prediction Dataset
10219,116390245,303.0,,3,14,/satyaprakashshukl/playground-series-s-3-e-2-eda,Binary Classification with a Tabular Stroke Prediction Dataset
10220,116324130,315.0,,16,93,/usharengaraju/tfdf-rf-proximities-projections-w-b,Binary Classification with a Tabular Stroke Prediction Dataset
10221,120302185,321.0,,7,65,/javohirtoshqorgonov/stroke-prediction-in-high-resolution,Binary Classification with a Tabular Stroke Prediction Dataset
10222,116339669,328.0,0.8836435621786588,11,21,/maazkarim/tuning-neural-networks-with-keras-tuner,Binary Classification with a Tabular Stroke Prediction Dataset
10223,116434335,63.0,,0,6,/omarvivas/lgbm-tpgs-s3e2-v1,Binary Classification with a Tabular Stroke Prediction Dataset
10224,116039261,254.0,0.8853001017293998,41,78,/tilii7/modeling-stroke-dataset-with-lasso-regression,Binary Classification with a Tabular Stroke Prediction Dataset
10225,116411692,309.0,,2,28,/samuelcortinhas/ps-s3e2-stroke-prediction-tensorflow,Binary Classification with a Tabular Stroke Prediction Dataset
10226,115972104,353.0,0.8727763877814743,2,12,/erenakbulut/catboost-score-0-87277,Binary Classification with a Tabular Stroke Prediction Dataset
10227,116305069,465.0,,1,4,/pauloalvaro/playground-s3e2-ptbr,Binary Classification with a Tabular Stroke Prediction Dataset
10228,116510396,373.0,,2,5,/leehaeseung01/playgr-3-2,Binary Classification with a Tabular Stroke Prediction Dataset
10229,116153843,241.0,,4,21,/tharunnayak14/ps-s03e02-eda-data-visualization-training,Binary Classification with a Tabular Stroke Prediction Dataset
10230,116012287,341.0,0.877209865002337,4,20,/kirillka95/ps-s03e02-lgbm-catboost-logisticregression,Binary Classification with a Tabular Stroke Prediction Dataset
10231,116501781,211.0,0.8882626268180693,35,34,/alexandershumilin/ps-s3-e2-ensemble-model-addition-data,Binary Classification with a Tabular Stroke Prediction Dataset
10232,116267466,400.0,,3,3,/kdmitrie/pgs32-baseline,Binary Classification with a Tabular Stroke Prediction Dataset
10233,116595925,116.0,,1,13,/amrelsayeh/ps-s3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10234,124725485,191.0,,19,39,/hikmatullahmohammadi/stroke-prediction-ps-s3-ep2-modeling-eda,Binary Classification with a Tabular Stroke Prediction Dataset
10235,116185199,192.0,,8,16,/ananyasingh008/playground-series-ep-2,Binary Classification with a Tabular Stroke Prediction Dataset
10236,116533457,479.0,0.8846608561766243,9,28,/edouardo/my-stroke-of-insight,Binary Classification with a Tabular Stroke Prediction Dataset
10237,116320524,207.0,0.8857056446069671,15,32,/samir95/stroke-prediction-ensemble-baseline,Binary Classification with a Tabular Stroke Prediction Dataset
10238,115949239,432.0,,0,8,/bechirkarmeni/ps3e1-automl-h2o,Binary Classification with a Tabular Stroke Prediction Dataset
10239,116440356,431.0,,8,15,/kanberburak/s3-ep2-ps-analysis,Binary Classification with a Tabular Stroke Prediction Dataset
10240,116022061,220.0,,1,13,/lavagod/pc-s0302-minimum-code-0-81996,Binary Classification with a Tabular Stroke Prediction Dataset
10241,116013465,120.0,,0,7,/ryanirl/s03e02-eda-catboost-baseline,Binary Classification with a Tabular Stroke Prediction Dataset
10242,116384121,543.0,,6,15,/behroozsohrabi/ps-s3-e2-data-preparation,Binary Classification with a Tabular Stroke Prediction Dataset
10243,116400869,527.0,,22,55,/ashishkumarak/heart-stroke-prediction-by-nn-model-tensorflow,Binary Classification with a Tabular Stroke Prediction Dataset
10244,116103389,97.0,0.849742927057271,0,12,/mozattt/baseline-lightgbm-with-feature-importance,Binary Classification with a Tabular Stroke Prediction Dataset
10245,116492756,88.0,0.8733537708614005,0,2,/vjpkaggle/stroke-prediction-playground-s3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10246,116509664,206.0,0.8802342525638558,10,29,/satoshiss/stroke-prediction-ps3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10247,116267585,454.0,0.864713645486789,2,10,/demko1/a-simple-pytorch-nn-baseline,Binary Classification with a Tabular Stroke Prediction Dataset
10248,116467621,376.0,,0,0,/ashest/stroke,Binary Classification with a Tabular Stroke Prediction Dataset
10249,116018310,284.0,0.8640125374611641,0,6,/khawajaabaidullah/ensemble-catboost-lgbm-xgboost,Binary Classification with a Tabular Stroke Prediction Dataset
10250,116639333,1.0,,13,35,/kirkdco/xgboost-plays03e02-first-place,Binary Classification with a Tabular Stroke Prediction Dataset
10251,116432171,553.0,,7,10,/tonychirilus/stroke-prediction-using-sklearn,Binary Classification with a Tabular Stroke Prediction Dataset
10252,116135869,415.0,,3,13,/gauravmalik26/catboost-baseline-submission,Binary Classification with a Tabular Stroke Prediction Dataset
10253,116430526,100.0,0.8792341425861263,0,8,/kholmogorovaaa/lustering-upsample-or-without-upsample,Binary Classification with a Tabular Stroke Prediction Dataset
10254,117418652,8.0,,9,15,/k0takahashi/ps-s3e2-2023-stroke-prediction-8th-place,Binary Classification with a Tabular Stroke Prediction Dataset
10255,116015190,14.0,,1,18,/jacoporepossi/optimizing-ensemble-weights-with-gradient-descent,Binary Classification with a Tabular Stroke Prediction Dataset
10256,118092019,91.0,,0,3,/forbo7/ensembling-a-rf-gbm-and-nn-to-reach-91-position,Binary Classification with a Tabular Stroke Prediction Dataset
10257,116353443,258.0,,0,0,/manaidu/playground-series-s3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10258,118595922,379.0,,0,3,/ericdeuber/stroke-predictions-ps-s3-e2,Binary Classification with a Tabular Stroke Prediction Dataset
10259,116434091,420.0,0.7628880151769267,0,3,/ebrahimghantiwala/neural-model,Binary Classification with a Tabular Stroke Prediction Dataset
10260,116764585,369.0,0.8690027769376701,7,19,/abraamadamidis/stroke-prediction-nn-model-tensorflow,Binary Classification with a Tabular Stroke Prediction Dataset
10261,116240866,535.0,0.875457094938275,1,12,/kim145/extended-eda-seaborne-baseline-models,Binary Classification with a Tabular Stroke Prediction Dataset
10262,116355205,371.0,0.875436474113992,0,6,/marwanyasser/stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10263,117325599,34.0,,0,1,/mahyararani/playground3-e2-top-5,Binary Classification with a Tabular Stroke Prediction Dataset
10264,116169964,352.0,0.8729757224162107,0,9,/rishabh15virgo/eda-xgb-reg-tunev1,Binary Classification with a Tabular Stroke Prediction Dataset
10265,116457769,387.0,,6,10,/darkmatter2222/susman-viz-feature-distribution-cyberpunk,Binary Classification with a Tabular Stroke Prediction Dataset
10266,116394428,492.0,0.8737868081713454,1,7,/zarahshibli/stroke-prediction-eda,Binary Classification with a Tabular Stroke Prediction Dataset
10267,116294035,72.0,0.8696901377471062,3,6,/mukaseevru/ps-s3e2-lama-lightautoml-extra-data,Binary Classification with a Tabular Stroke Prediction Dataset
10268,116461187,17.0,0.8678823788182893,1,13,/akioonodera/ps-3-02-lgbm-bin,Binary Classification with a Tabular Stroke Prediction Dataset
10269,116480880,188.0,0.867078166671249,2,6,/pranjalrathore/stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10270,116071341,346.0,,2,9,/poushalimukherjee/eda-pg-series-s03e02,Binary Classification with a Tabular Stroke Prediction Dataset
10271,116466179,94.0,0.8709102031838553,0,6,/barbagrande007/bbg007-s3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10272,115954671,55.0,,0,11,/gauravduttakiit/pss3e2-smote-lazypredict,Binary Classification with a Tabular Stroke Prediction Dataset
10273,116331532,224.0,0.8637307195292954,0,3,/prem00/stroke-prediction-beginner-friendly,Binary Classification with a Tabular Stroke Prediction Dataset
10274,117239169,83.0,,4,7,/inaciobr/ps-s03e02-eda-model-ensemble,Binary Classification with a Tabular Stroke Prediction Dataset
10275,116410946,429.0,,9,16,/donjoeml/calibrated-stacking-classifier-auc-0-895,Binary Classification with a Tabular Stroke Prediction Dataset
10276,116534600,384.0,0.8685216243710648,1,4,/nightwolfbrooks/linear-svm-with-hyperparameter-tuning,Binary Classification with a Tabular Stroke Prediction Dataset
10277,116308267,268.0,,0,7,/kmskojim/pgs230102-strokeprediction,Binary Classification with a Tabular Stroke Prediction Dataset
10278,115980007,121.0,,0,6,/yururoi/lightgbm-simple-baseline,Binary Classification with a Tabular Stroke Prediction Dataset
10279,116294095,77.0,,0,2,/spattni97/ps-s03e02-eda,Binary Classification with a Tabular Stroke Prediction Dataset
10280,116164036,233.0,0.870886145555525,1,6,/datascientistsohail/ps-se01ep02-randomforestclassifier,Binary Classification with a Tabular Stroke Prediction Dataset
10281,116474196,263.0,,5,7,/sathyakrishnan12/strokeprediction-base-nb,Binary Classification with a Tabular Stroke Prediction Dataset
10282,116347821,541.0,0.8696351488823513,0,3,/debopomsutradhar/stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10283,116578963,24.0,,1,1,/likai97/top-25-notebook-xgboost-optuna,Binary Classification with a Tabular Stroke Prediction Dataset
10284,116763076,173.0,,1,8,/predaddict/conformal-prediction-pss3-e2,Binary Classification with a Tabular Stroke Prediction Dataset
10285,116421698,348.0,,4,9,/starkandroid/begginer-s-approach-to-pss3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10286,116533832,471.0,,5,9,/skashperova/stroke-prediction-xgboost,Binary Classification with a Tabular Stroke Prediction Dataset
10287,116163866,591.0,,12,25,/hasanbasriakcay/pss3-2-eda-fe-modeling,Binary Classification with a Tabular Stroke Prediction Dataset
10288,116061687,29.0,0.8668994528607957,0,17,/soupmonster/lgbm-starter,Binary Classification with a Tabular Stroke Prediction Dataset
10289,116016409,102.0,,22,64,/burhanuddinlatsaheb/fast-eda,Binary Classification with a Tabular Stroke Prediction Dataset
10290,115993940,46.0,,1,9,/ahmedhammad01/lb-0-86-logistic-regression-vs-other-models,Binary Classification with a Tabular Stroke Prediction Dataset
10291,115995293,177.0,0.86873470622199,3,14,/desalegngeb/pss-3-episode-2-stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10292,115995293,177.0,0.8593316103489044,3,14,/desalegngeb/pss-3-episode-2-stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10293,116112020,486.0,0.8686728437491408,0,7,/yarribryn/baseline-logistic-regression-w-resample,Binary Classification with a Tabular Stroke Prediction Dataset
10294,116579499,38.0,,0,5,/lonnieqin/stroke-prediction-with-catboost,Binary Classification with a Tabular Stroke Prediction Dataset
10295,116104575,351.0,,0,16,/chunweishen/ps-s03e02-eda-baseline-submission,Binary Classification with a Tabular Stroke Prediction Dataset
10296,116565683,175.0,,0,0,/osoomin/stroke-prediction-sue,Binary Classification with a Tabular Stroke Prediction Dataset
10297,116233248,331.0,0.8676143081026092,0,4,/sujaykapadnis/model1-lr,Binary Classification with a Tabular Stroke Prediction Dataset
10298,115978889,250.0,0.8675386984135712,0,7,/tracyporter/play-3-2,Binary Classification with a Tabular Stroke Prediction Dataset
10299,136270368,193.0,,0,5,/faelk8/ps-3-2-umap-catboost-tensorflow,Binary Classification with a Tabular Stroke Prediction Dataset
10300,116043484,255.0,,0,4,/abdoulayebalde/pss3-episode-2-eda-catboost-score-0-8669,Binary Classification with a Tabular Stroke Prediction Dataset
10301,115985536,455.0,0.8617957988507328,0,6,/priyanagda/ps-3-02-baseline-lightgbm-external-data,Binary Classification with a Tabular Stroke Prediction Dataset
10302,116337676,90.0,0.8657515603090374,2,6,/amoghgarg20/playground-s3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10303,116143137,295.0,,0,5,/shivam2111/eda-xgboost-catboost,Binary Classification with a Tabular Stroke Prediction Dataset
10304,116509805,608.0,0.8658065491737923,0,2,/sharvalishinde/ps-s3e2-feature-engg-xgb,Binary Classification with a Tabular Stroke Prediction Dataset
10305,116260287,232.0,0.8523342773088449,0,2,/semjinwu/stroke-prediction-use-mlp,Binary Classification with a Tabular Stroke Prediction Dataset
10306,116039587,144.0,0.8641018943663908,0,7,/arunpurakkatt/lgbm-catboost-logisticregression,Binary Classification with a Tabular Stroke Prediction Dataset
10307,116610428,246.0,,2,1,/leesstephanie/stroke-prediction-playground-s3e2-2023,Binary Classification with a Tabular Stroke Prediction Dataset
10308,116529292,560.0,0.8494954771658739,0,4,/sharansmenon/stroke-prediction-with-catboost,Binary Classification with a Tabular Stroke Prediction Dataset
10309,116523045,375.0,0.8542554507712188,2,4,/prutsaowaprut/playground-s3e2-extra-dataset-xgboost,Binary Classification with a Tabular Stroke Prediction Dataset
10310,116863322,614.0,,0,0,/priyam8210/playgrnd-series1,Binary Classification with a Tabular Stroke Prediction Dataset
10311,116204036,502.0,,2,9,/badice/tabular-classification-with-a-stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10312,116006773,507.0,0.8538258502653213,0,9,/rajsengo/kmeans-smote-xgboost-and-optuna,Binary Classification with a Tabular Stroke Prediction Dataset
10313,131584696,459.0,0.8564653157735559,0,3,/osmanf/stroke-prediction-using-machine-learning,Binary Classification with a Tabular Stroke Prediction Dataset
10314,116538590,508.0,0.8531109950235077,0,0,/mecsico92/playground-series-season-3-episode-2,Binary Classification with a Tabular Stroke Prediction Dataset
10315,116428548,563.0,,0,9,/ahana09/ps-s3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10316,116046294,512.0,,2,8,/tylerjthomas9/julia-stacking-with-mlj-tps-jan2023-2,Binary Classification with a Tabular Stroke Prediction Dataset
10317,116535926,524.0,,3,10,/mkr9395/eda-base-model-catboost,Binary Classification with a Tabular Stroke Prediction Dataset
10318,116103935,578.0,,7,40,/soumendraprasad/eda-baseline-xgb,Binary Classification with a Tabular Stroke Prediction Dataset
10319,116511718,568.0,,2,12,/nityampareek/ps-s3-ep2-data-augmentation-lightgbm,Binary Classification with a Tabular Stroke Prediction Dataset
10320,116162783,624.0,0.8469041269142998,2,19,/agorinenko/s3e2-born-to-win,Binary Classification with a Tabular Stroke Prediction Dataset
10321,116677321,419.0,,1,7,/stpeteishii/pss3-ep2-visualize-importance,Binary Classification with a Tabular Stroke Prediction Dataset
10322,116555443,650.0,0.8211968326413901,0,3,/sagar2168616/tabular-playground-3-2-keras,Binary Classification with a Tabular Stroke Prediction Dataset
10323,116515300,625.0,0.8179971680734651,0,0,/vision6/stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10324,116486707,648.0,,8,17,/dhirajkumar612/multiple-models-comparison,Binary Classification with a Tabular Stroke Prediction Dataset
10325,116718652,663.0,,1,1,/kajubadaam/simple-predict-stroke-gradient-boosting,Binary Classification with a Tabular Stroke Prediction Dataset
10326,116460715,673.0,0.745085370212532,0,8,/boydoimmanuel/stroke-prediction-eda-modelling,Binary Classification with a Tabular Stroke Prediction Dataset
10327,116454151,661.0,0.6080668664595419,1,1,/marciamaa/beginner-s-approach-suggestions-are-appreciated,Binary Classification with a Tabular Stroke Prediction Dataset
10328,116432350,688.0,0.721295812597949,10,21,/jonbown/tabular-ml-pipeline-speedml-tpot,Binary Classification with a Tabular Stroke Prediction Dataset
10329,116474891,693.0,,5,9,/natchimuthun/stroke-prediction-eda-models,Binary Classification with a Tabular Stroke Prediction Dataset
10330,116164334,727.0,,0,5,/praneeel/pss3e2,Binary Classification with a Tabular Stroke Prediction Dataset
10331,116135648,720.0,,0,4,/n3n77i/1d-mean,Binary Classification with a Tabular Stroke Prediction Dataset
10332,116050771,726.0,0.5184900057738308,3,7,/sanjaylalwani/ps-classification,Binary Classification with a Tabular Stroke Prediction Dataset
10333,116580230,740.0,0.8681641967501581,0,0,/bouchenemehdi/stroke-prediction-atogluon-magic,Binary Classification with a Tabular Stroke Prediction Dataset
10334,118332208,757.0,,1,1,/sameekshanomula/playground,Binary Classification with a Tabular Stroke Prediction Dataset
10335,116562659,759.0,,0,0,/simranksaluja/stroke,Binary Classification with a Tabular Stroke Prediction Dataset
10336,116084163,764.0,0.416959940612026,2,8,/kaushalkrishna2000/playground-s03e02,Binary Classification with a Tabular Stroke Prediction Dataset
10337,116084163,764.0,0.416959940612026,2,8,/kaushalkrishna2000/playground-s03e02,Binary Classification with a Tabular Stroke Prediction Dataset
10338,116542470,765.0,,0,3,/itsmegood/playground-series-season-3-2-stroke-prediction,Binary Classification with a Tabular Stroke Prediction Dataset
10339,116188721,768.0,0.1342965549476231,4,10,/mukeshrajm/stroke-classification-using-various-techniques,Binary Classification with a Tabular Stroke Prediction Dataset
10340,116494686,769.0,,1,5,/knedliky/ps-s3-e2-exploratory-data-analysis,Binary Classification with a Tabular Stroke Prediction Dataset
10341,116590914,111.0,,7,15,/satyaprakashshukl/playground-series-s-3-e-3-eda,Binary Classification with a Tabular Employee Attrition Dataset
10342,117113813,157.0,0.940865234982882,0,7,/omarvivas/lgbm-tpgs-s3e3-v1,Binary Classification with a Tabular Employee Attrition Dataset
10343,116570685,176.0,,0,2,/erenakbulut/playground-s3e3-simple-baseline-horriblescore-d,Binary Classification with a Tabular Employee Attrition Dataset
10344,117186722,224.0,,8,25,/jillanisofttech/tabular-classification-with-an-employee-attrition,Binary Classification with a Tabular Employee Attrition Dataset
10345,116693218,241.0,0.91005291005291,2,2,/mshadfar/linear-discriminant-analysis-lda-score-0-91005,Binary Classification with a Tabular Employee Attrition Dataset
10346,116983185,158.0,,0,10,/lonnieqin/employee-attrition-prediction-logistic-regression,Binary Classification with a Tabular Employee Attrition Dataset
10347,116939142,219.0,,10,42,/burhanuddinlatsaheb/fast-eda-ensembling-4-models,Binary Classification with a Tabular Employee Attrition Dataset
10348,116983335,192.0,,1,3,/leehaeseung01/ps-s3-e3-practice,Binary Classification with a Tabular Employee Attrition Dataset
10349,116877747,93.0,,0,3,/eliotlacroix/ps-s3e3-exploration-via-random-forest,Binary Classification with a Tabular Employee Attrition Dataset
10350,116859119,44.0,0.896358543417367,0,2,/ashokkumargarain/notebook5d5f1b2507,Binary Classification with a Tabular Employee Attrition Dataset
10351,116674268,254.0,0.9122315592903828,0,10,/manishwahale/ps-s3-e3-eda-ensemble,Binary Classification with a Tabular Employee Attrition Dataset
10352,117138202,24.0,,0,8,/mohammednabil98/hello,Binary Classification with a Tabular Employee Attrition Dataset
10353,148536247,244.0,,27,80,/javohirtoshqorgonov/employee-attrition-prediction-eda-roc-auc-0-88,Binary Classification with a Tabular Employee Attrition Dataset
10354,116956466,314.0,,0,0,/manaidu/playground-series-s3e3,Binary Classification with a Tabular Employee Attrition Dataset
10355,116622662,94.0,,2,7,/kirillka95/ps-s03e03-eda,Binary Classification with a Tabular Employee Attrition Dataset
10356,116684215,17.0,,1,6,/lavagod/pc-s03e03-minimum-code-0-86235,Binary Classification with a Tabular Employee Attrition Dataset
10357,117085014,112.0,0.9474011826953004,6,24,/ducanger/ps-s3e3-woe-catboost,Binary Classification with a Tabular Employee Attrition Dataset
10358,116921171,55.0,0.9340180516651104,5,10,/mukaseevru/ps-s3e3-lama-lightautoml-extra-data,Binary Classification with a Tabular Employee Attrition Dataset
10359,117041888,233.0,,7,25,/paddykb/ps-s3e3-gam-adversarial-checks,Binary Classification with a Tabular Employee Attrition Dataset
10360,155909476,7.0,,5,35,/ashishkumarak/employee-retention-workforce-reduction-prediction,Binary Classification with a Tabular Employee Attrition Dataset
10361,116696576,29.0,,1,5,/faelk8/playground-s-3-e-3-eda-model,Binary Classification with a Tabular Employee Attrition Dataset
10362,117081440,32.0,0.6579520697167756,12,75,/usharengaraju/integratedgradients-tensorflow-w-b,Binary Classification with a Tabular Employee Attrition Dataset
10363,117140287,77.0,0.9461562402738872,2,6,/edouardo/scalded-catboost,Binary Classification with a Tabular Employee Attrition Dataset
10364,116633393,288.0,,1,3,/nnjjpp/eda-and-xgboost-baseline-ps3-3,Binary Classification with a Tabular Employee Attrition Dataset
10365,117086313,48.0,0.9453781512605042,4,10,/belati/pss3e3-xgb-with-optuna,Binary Classification with a Tabular Employee Attrition Dataset
10366,116788321,12.0,,1,4,/kaggleqrdl/example-using-pl-metric,Binary Classification with a Tabular Employee Attrition Dataset
10367,116788674,27.0,0.924214130096483,4,15,/maniceet/eda-xgboost-catboost-with-encodings-0-94,Binary Classification with a Tabular Employee Attrition Dataset
10368,117036253,11.0,0.9299719887955182,4,10,/tharunnayak14/ps-s03e03-eda-training,Binary Classification with a Tabular Employee Attrition Dataset
10369,117513568,58.0,,1,11,/chunweishen/ps-s03e03-eda-baseline-model-submission,Binary Classification with a Tabular Employee Attrition Dataset
10370,116815920,59.0,0.8737939620292562,3,7,/maazkarim/eda-feature-engineering-tensorflow-keras,Binary Classification with a Tabular Employee Attrition Dataset
10371,116985544,8.0,0.94234360410831,0,4,/kirkdco/xgboost-s03e03,Binary Classification with a Tabular Employee Attrition Dataset
10372,116985544,8.0,0.9399315281668222,0,4,/kirkdco/xgboost-s03e03,Binary Classification with a Tabular Employee Attrition Dataset
10373,116985544,8.0,0.9400871459694988,0,4,/kirkdco/xgboost-s03e03,Binary Classification with a Tabular Employee Attrition Dataset
10374,116575536,50.0,0.942110177404295,30,61,/khawajaabaidullah/starting-strong-xgboost-lightgbm-catboost,Binary Classification with a Tabular Employee Attrition Dataset
10375,116980175,63.0,0.9282601929660752,1,7,/oldjerry/happy-new-year-9-kinds-of-models-ensemble,Binary Classification with a Tabular Employee Attrition Dataset
10376,116559393,119.0,0.8843759726112668,2,14,/tilii7/modeling-attrition-dataset-with-keras,Binary Classification with a Tabular Employee Attrition Dataset
10377,117324802,67.0,,0,6,/mahyararani/playground3-e3-top-11,Binary Classification with a Tabular Employee Attrition Dataset
10378,117005375,201.0,0.9410208527855588,4,16,/kdmitrie/pgs33-eda-basic-test-of-models-blending,Binary Classification with a Tabular Employee Attrition Dataset
10379,117058188,186.0,0.9401649548708372,5,12,/krviswanathan/employee-attrition-eda-catboost-0-94,Binary Classification with a Tabular Employee Attrition Dataset
10380,117112715,57.0,0.9393090569561158,1,0,/sunilgautam/playground-series-s03e03,Binary Classification with a Tabular Employee Attrition Dataset
10381,116834556,117.0,,3,8,/gauravmalik26/eda-for-feature-engineering,Binary Classification with a Tabular Employee Attrition Dataset
10382,117047873,225.0,0.9340180516651104,4,12,/shoabahamed/employee-attrition-eda-gridsearchcv-stacking,Binary Classification with a Tabular Employee Attrition Dataset
10383,117047873,225.0,0.921490818549642,4,12,/shoabahamed/employee-attrition-eda-gridsearchcv-stacking,Binary Classification with a Tabular Employee Attrition Dataset
10384,117047873,225.0,0.925692499221911,4,12,/shoabahamed/employee-attrition-eda-gridsearchcv-stacking,Binary Classification with a Tabular Employee Attrition Dataset
10385,116847251,79.0,,0,3,/kmskojim/pgs230103-ensemble-lgbm-cb-rf,Binary Classification with a Tabular Employee Attrition Dataset
10386,117007213,56.0,0.9366635543106132,0,1,/masayakawamata/top9-catboost-xgboost-lightgbm-ensemble,Binary Classification with a Tabular Employee Attrition Dataset
10387,116620200,2.0,,2,4,/vaidyaprasad84/single-and-ready-to-mingle,Binary Classification with a Tabular Employee Attrition Dataset
10388,116965815,82.0,0.9365079365079364,22,78,/samuelcortinhas/ps-s3e3-hill-climbing-like-a-gm,Binary Classification with a Tabular Employee Attrition Dataset
10389,117005444,215.0,0.9287270463741052,10,18,/mkr9395/catboost-classification-with-optuna-ps-s3e3,Binary Classification with a Tabular Employee Attrition Dataset
10390,117149844,113.0,0.9273264861500156,1,6,/kholmogorovaaa/unwanted-features-eda-submission,Binary Classification with a Tabular Employee Attrition Dataset
10391,117046547,141.0,,0,5,/mobenmo/simple-xgboost-0-935-score,Binary Classification with a Tabular Employee Attrition Dataset
10392,116997915,120.0,0.9273264861500156,10,18,/ifuurh/squeezing-ensembles-with-optuna,Binary Classification with a Tabular Employee Attrition Dataset
10393,116621427,395.0,,4,6,/poushalimukherjee/eda-pg-series-s03e03,Binary Classification with a Tabular Employee Attrition Dataset
10394,117017754,38.0,0.9340180516651104,11,16,/satoshiss/employee-attrition-prediction-ps3e3,Binary Classification with a Tabular Employee Attrition Dataset
10395,116557902,131.0,,36,111,/radek1/eda-training-a-1st-model-submission,Binary Classification with a Tabular Employee Attrition Dataset
10396,117056716,137.0,,0,0,/danielliao/build-up-from-radek,Binary Classification with a Tabular Employee Attrition Dataset
10397,117059288,339.0,0.9338624338624338,12,21,/hikmatullahmohammadi/employee-attrition-modeling-eda-ps-s3-ep3,Binary Classification with a Tabular Employee Attrition Dataset
10398,116793981,166.0,,2,4,/fahaddalwai/s3e3-eda-and-testing-models,Binary Classification with a Tabular Employee Attrition Dataset
10399,116564621,205.0,0.9323062558356676,8,36,/anubhavgoyal10/ps-season-3-e3-eda-catboost,Binary Classification with a Tabular Employee Attrition Dataset
10400,117140056,258.0,0.9253034547152196,3,7,/pranav07/playground-s3e3-submission,Binary Classification with a Tabular Employee Attrition Dataset
10401,117033532,26.0,,0,1,/maheswarareddyp/pl-series-s3e3-mahesh,Binary Classification with a Tabular Employee Attrition Dataset
10402,117131925,114.0,0.9315281668222845,0,2,/rossfriscia/pgs3e3-employee-attrition,Binary Classification with a Tabular Employee Attrition Dataset
10403,120863166,217.0,0.8485838779956427,3,11,/amrelsayeh/pgs-s3e3-eda-beginner,Binary Classification with a Tabular Employee Attrition Dataset
10404,116904107,150.0,,25,78,/jacoporepossi/how-to-use-chatgpt-in-a-competition-eda-part-1,Binary Classification with a Tabular Employee Attrition Dataset
10405,117168272,249.0,,0,6,/valentindefour/tps-s03e03-eda-automl-fun-explainable-ai,Binary Classification with a Tabular Employee Attrition Dataset
10406,116783502,268.0,0.9257703081232492,6,8,/alexryzhkov/autowoe-starter-tps-january-23,Binary Classification with a Tabular Employee Attrition Dataset
10407,117136042,380.0,0.9277933395580454,10,22,/khaledgamal1/ep3-3-model,Binary Classification with a Tabular Employee Attrition Dataset
10408,116605074,272.0,,9,6,/abdoulayebalde/eda-catboost-baseline-model-with-good-score,Binary Classification with a Tabular Employee Attrition Dataset
10409,116969571,346.0,0.9116090880796764,3,6,/ryancaldwell/initial-lassocv,Binary Classification with a Tabular Employee Attrition Dataset
10410,117102611,127.0,0.925925925925926,2,7,/ahana09/ps-s3e3,Binary Classification with a Tabular Employee Attrition Dataset
10411,117128844,426.0,,0,0,/manojkumarsmk/playground-s3-e3-mk-s,Binary Classification with a Tabular Employee Attrition Dataset
10412,116557354,305.0,,0,3,/gauravduttakiit/pss3e3-lazypredict,Binary Classification with a Tabular Employee Attrition Dataset
10413,116604791,440.0,0.8482726423902894,2,7,/snorfyang/easy-randomforest-approach,Binary Classification with a Tabular Employee Attrition Dataset
10414,116996423,253.0,0.91005291005291,2,3,/smackia/boosting-algos,Binary Classification with a Tabular Employee Attrition Dataset
10415,117752955,357.0,0.9165888577653284,0,11,/francescoliveras/playground-series-s3-ep3,Binary Classification with a Tabular Employee Attrition Dataset
10416,116941463,309.0,,3,17,/nishantborkar/playground-ensembling,Binary Classification with a Tabular Employee Attrition Dataset
10417,118672267,301.0,0.9375972611266729,10,15,/inaciobr/ps-s03e03-original-df-models-exploration,Binary Classification with a Tabular Employee Attrition Dataset
10418,117034567,286.0,,0,1,/jimgruman/attrition-season-3-episode3-with-tidymodels,Binary Classification with a Tabular Employee Attrition Dataset
10419,116602427,394.0,,2,2,/macroponix/easy-but-good-start-with-lgbm,Binary Classification with a Tabular Employee Attrition Dataset
10420,116927390,330.0,,0,4,/stpeteishii/pss3-ep3-visualize-importance,Binary Classification with a Tabular Employee Attrition Dataset
10421,117069880,417.0,,4,9,/manujosephv/ps3e3-pytorch-tabular-gate,Binary Classification with a Tabular Employee Attrition Dataset
10422,117149418,410.0,,0,15,/akioonodera/ps-3-03-lgbm-bin,Binary Classification with a Tabular Employee Attrition Dataset
10423,124152184,415.0,,15,39,/validmodel/playground-s-3-e-3-eda-fe-fs-modeling,Binary Classification with a Tabular Employee Attrition Dataset
10424,116710842,306.0,,0,7,/piyushm28/kaggle-playground-series-s3e3-lgbm-using-optuna,Binary Classification with a Tabular Employee Attrition Dataset
10425,116870634,336.0,0.883442265795207,0,1,/datascientistsohail/just-a-simple-approach-rfc,Binary Classification with a Tabular Employee Attrition Dataset
10426,116955636,318.0,0.9074074074074074,1,9,/solomonteng/simpleensemble-90-196,Binary Classification with a Tabular Employee Attrition Dataset
10427,116955636,318.0,0.9074074074074074,1,9,/solomonteng/simpleensemble-90-196,Binary Classification with a Tabular Employee Attrition Dataset
10428,116944988,530.0,,2,4,/chanukauk/playground-s0303-smote-gradient-boost,Binary Classification with a Tabular Employee Attrition Dataset
10429,117035330,358.0,,1,5,/manavd22/catboost-bayesian-tuning-cv,Binary Classification with a Tabular Employee Attrition Dataset
10430,116825603,526.0,,0,2,/badice/playground-series-season-3-keras-preprocessing,Binary Classification with a Tabular Employee Attrition Dataset
10431,117025288,289.0,,2,9,/docxian/ps-s3-e3-eda-and-autogluon,Binary Classification with a Tabular Employee Attrition Dataset
10432,116664924,470.0,0.9019607843137256,2,6,/nightwolfbrooks/linear-and-weighted-svm-with-hyperparameter-tuning,Binary Classification with a Tabular Employee Attrition Dataset
10433,116879816,546.0,,0,7,/eshraqsaeed/emp-attrition-version1,Binary Classification with a Tabular Employee Attrition Dataset
10434,116554139,341.0,,1,7,/rishabh15virgo/eda-with-pandas-profiling-baseline-all-you-need,Binary Classification with a Tabular Employee Attrition Dataset
10435,117083153,480.0,,3,7,/ch124uec/eda-with-plotly-ensembling,Binary Classification with a Tabular Employee Attrition Dataset
10436,116655510,539.0,0.8969810146280734,10,10,/kaushalkrishna2000/playground-s03e03,Binary Classification with a Tabular Employee Attrition Dataset
10437,116710463,349.0,,2,7,/natchimuthun/ps3-s3-e3-attrition-prediction-eda,Binary Classification with a Tabular Employee Attrition Dataset
10438,116918985,453.0,0.8901338313103019,3,5,/amoghgarg20/playground-s3e3-eda-ensemble,Binary Classification with a Tabular Employee Attrition Dataset
10439,117140361,378.0,0.8899782135076253,4,2,/magnussesodia/ps-s3-e3-final,Binary Classification with a Tabular Employee Attrition Dataset
10440,116553036,404.0,0.8924680983504513,5,11,/mozattt/automated-eda-with-catboost-baseline,Binary Classification with a Tabular Employee Attrition Dataset
10441,117487336,390.0,,0,1,/iamnotashutosh/playground-s3-e3-eda-and-baisc-model,Binary Classification with a Tabular Employee Attrition Dataset
10442,117020355,559.0,0.8671023965141612,1,11,/abraamadamidis/attrition-prediction-friendly-nn-tensorflow,Binary Classification with a Tabular Employee Attrition Dataset
10443,116596837,386.0,,18,68,/odins0n/playground-s-3-e-3-eda-modelling,Binary Classification with a Tabular Employee Attrition Dataset
10444,117133944,468.0,0.8534080298786181,4,6,/barbagrande007/bbg007-s1e3,Binary Classification with a Tabular Employee Attrition Dataset
10445,116895609,400.0,0.8809523809523809,0,4,/ankitladva/eda-modelling,Binary Classification with a Tabular Employee Attrition Dataset
10446,116782372,416.0,,1,3,/jhotor/datasets-profile-simple-eda,Binary Classification with a Tabular Employee Attrition Dataset
10447,116933280,372.0,,1,7,/vlad15lav/ps-s03e03-eda-for-all-columns,Binary Classification with a Tabular Employee Attrition Dataset
10448,116576082,412.0,0.8741051976346094,0,1,/zarahshibli/employees-attrition-prediction-eda-model,Binary Classification with a Tabular Employee Attrition Dataset
10449,117117599,502.0,,13,22,/samir95/i-suck-at-eda-help-me,Binary Classification with a Tabular Employee Attrition Dataset
10450,116776917,544.0,0.8359788359788359,2,5,/rajeevctrl/ps-s3-e3-eda-modeling-submission,Binary Classification with a Tabular Employee Attrition Dataset
10451,117014182,489.0,,4,9,/prem00/eda-using-correlation-keep-it-or-drop-it,Binary Classification with a Tabular Employee Attrition Dataset
10452,116657186,478.0,0.856364768129474,2,8,/rohan8771/playground-s3e3-comprehensive-eda-modelling,Binary Classification with a Tabular Employee Attrition Dataset
10453,116584035,568.0,0.8126361655773421,1,3,/tracyporter/play-3-3,Binary Classification with a Tabular Employee Attrition Dataset
10454,116893722,393.0,0.8535636476812948,2,3,/muhammadumairab/playground-series-first-time-ever,Binary Classification with a Tabular Employee Attrition Dataset
10455,117065816,598.0,0.7671179582944289,0,0,/fuad0857/playground-series-with-tensorflow,Binary Classification with a Tabular Employee Attrition Dataset
10456,116742751,600.0,0.7535792094615624,0,3,/n3n77i/1d-mean-geometric,Binary Classification with a Tabular Employee Attrition Dataset
10457,116736890,603.0,0.5,0,1,/ksqrt9/keras-nn-written-by-korean,Binary Classification with a Tabular Employee Attrition Dataset
10458,117075504,629.0,,0,4,/azazali/playground-series-ensemble-learning,Binary Classification with a Tabular Employee Attrition Dataset
10459,117033297,626.0,0.6564737005913477,6,8,/mukeshrajm/beginner-pipeline-submission,Binary Classification with a Tabular Employee Attrition Dataset
10460,116898193,620.0,0.6529723000311236,0,2,/ericdeuber/playground-series-s3e3-eda-baseline-models,Binary Classification with a Tabular Employee Attrition Dataset
10461,123957124,2.0,,15,43,/iafoss/chunk-based-data-loading-with-caching,IceCube - Neutrinos in Deep Ice
10462,120879761,11.0,,2,15,/synset/icecube-qudata-line-fit-method,IceCube - Neutrinos in Deep Ice
10463,117505752,12.0,1.2142961693033147,7,52,/solverworld/icecube-neutrino-path-least-squares-1-214,IceCube - Neutrinos in Deep Ice
10464,117409767,19.0,,0,6,/mohammadrahmati/cnn-architecture,IceCube - Neutrinos in Deep Ice
10465,119196179,21.0,,0,1,/shadowshuo/icecube-create-db-528,IceCube - Neutrinos in Deep Ice
10466,118189429,24.0,,12,114,/shlomoron/icecube-eda-pca-baseline-cv-1-23-lb-1-218,IceCube - Neutrinos in Deep Ice
10467,122574848,26.0,1.0173841156623278,25,117,/rsmits/tensorflow-lstm-model-inference,IceCube - Neutrinos in Deep Ice
10468,123636648,29.0,,1,25,/roger92/gnnmodel-of-pytorchlightning-version-with-comments,IceCube - Neutrinos in Deep Ice
10469,126564184,35.0,,0,1,/emanuelruzak/ensemble2,IceCube - Neutrinos in Deep Ice
10470,123479881,44.0,,0,0,/peirenc/process-data-pc-2,IceCube - Neutrinos in Deep Ice
10471,117409895,55.0,,2,6,/ymatioun/icecube-plots-of-predictions,IceCube - Neutrinos in Deep Ice
10472,118016314,76.0,,0,31,/seungmoklee/lstm-preprocessing-point-picker,IceCube - Neutrinos in Deep Ice
10473,126473917,85.0,,0,3,/hideyukizushi/ice-inf-1-016-lstm-gru-transformer,IceCube - Neutrinos in Deep Ice
10474,117501489,105.0,1.2505274106662692,2,31,/utm529fg/eng-icecube-eda-understanding-train-data,IceCube - Neutrinos in Deep Ice
10475,118819907,114.0,,1,9,/dinowun/eda-simplified-icecube-neutrinos-in-deep-ice,IceCube - Neutrinos in Deep Ice
10476,134298137,168.0,,4,12,/ayrgthonsoraca/neutrinos-s-telescope-principal-component,IceCube - Neutrinos in Deep Ice
10477,121993128,176.0,,0,3,/machengyuan/graphnet-baseline,IceCube - Neutrinos in Deep Ice
10478,121024277,216.0,1.5551591511199592,16,18,/hechtjp/icecube-quick-eda-with-polars,IceCube - Neutrinos in Deep Ice
10479,123475737,237.0,1.0173841156623278,0,12,/vishakkbhat/tensorflow-lstm-model-inference,IceCube - Neutrinos in Deep Ice
10480,123923142,251.0,,0,2,/kaitokusumoto/icecube-eda-pca-eng,IceCube - Neutrinos in Deep Ice
10481,117019959,381.0,1.5180125337089874,2,13,/munumbutt/icecube-3d-linear-regression-extended,IceCube - Neutrinos in Deep Ice
10482,122072424,520.0,,0,0,/pilgrimv/graphnet-baseline-submission,IceCube - Neutrinos in Deep Ice
10483,125310112,462.0,,0,2,/subhasishsahu22/fly-like-duck-icecube,IceCube - Neutrinos in Deep Ice
10484,124969813,501.0,,2,13,/sofiamatias/icecube-eda-and-models-study,IceCube - Neutrinos in Deep Ice
10485,119854208,450.0,1.01821574552856,3,22,/prachi13/icecube-baseline-submission,IceCube - Neutrinos in Deep Ice
10486,117018783,461.0,,1,19,/satyaprakashshukl/neutrinos-in-deep-ice-simple-pred-eda,IceCube - Neutrinos in Deep Ice
10487,117298815,458.0,1.5689050322616744,0,2,/ashokkumargarain/notebook8354297f83,IceCube - Neutrinos in Deep Ice
10488,126656806,373.0,,1,6,/tyeestudio/gpt-based-prediction-no-chatgpt,IceCube - Neutrinos in Deep Ice
10489,117919462,478.0,,13,107,/mvvppp/icecube-neutrinos-domain-eda-for-ds-folks,IceCube - Neutrinos in Deep Ice
10490,117184501,527.0,,1,8,/faelk8/neutrinos-in-deep-ice-3d-xgbregressor,IceCube - Neutrinos in Deep Ice
10491,118875689,487.0,,0,5,/antonsevostianov/preliminary-eda-for-icecube-competition,IceCube - Neutrinos in Deep Ice
10492,117699957,387.0,1.5661772774139189,2,11,/oldjerry/is-machine-learning-method-work-lgb-lr,IceCube - Neutrinos in Deep Ice
10493,117654048,494.0,,0,2,/geokocha/eda-zero-of-icecube-neutrino-doms-array-online,IceCube - Neutrinos in Deep Ice
10494,125404116,537.0,,1,2,/atamazian/icecube-convert-train-data-to-sqlite,IceCube - Neutrinos in Deep Ice
10495,120540487,563.0,,0,22,/viktorcikojevic/very-simple-eda-neutrino-trajectories,IceCube - Neutrinos in Deep Ice
10496,122487053,565.0,,1,4,/aphysict/batch-52-56,IceCube - Neutrinos in Deep Ice
10497,117631452,569.0,,2,11,/maciek97x/3d-line-fitting-chosing-dir-lb-1-26-1-193,IceCube - Neutrinos in Deep Ice
10498,121427805,572.0,1.2231863613185328,0,0,/louisstefanuto/inference-dynedge-attention,IceCube - Neutrinos in Deep Ice
10499,116843350,585.0,,0,4,/gyozzza/icecube-3d-time-plot-charge-plot,IceCube - Neutrinos in Deep Ice
10500,117359632,619.0,1.5686327570344405,0,2,/saraswatitiwari/icecube-neutrinos-in-deep-ice,IceCube - Neutrinos in Deep Ice
10501,117989124,623.0,,0,2,/jacobhds/deepcore-sensor-ids,IceCube - Neutrinos in Deep Ice
10502,161469626,637.0,,0,0,/milosns/2023-01-ic-minimalist,IceCube - Neutrinos in Deep Ice
10503,122700662,657.0,1.219272695572541,0,3,/simonedegasperis/eda-baseline-with-polars,IceCube - Neutrinos in Deep Ice
10504,124154480,665.0,1.2189018728419825,0,0,/rohanjai/icecube-eda-pca-baseline-cv-1-23-lb-1-218-797d32,IceCube - Neutrinos in Deep Ice
10505,118953753,673.0,,0,15,/averkovanika/icecube-eda-more-doesn-t-mean-better,IceCube - Neutrinos in Deep Ice
10506,117550918,682.0,,13,101,/jirkaborovec/icecube-neutrino-eda-3d-interactive-viewer,IceCube - Neutrinos in Deep Ice
10507,118590960,683.0,,0,0,/higgsgama/v1-polars,IceCube - Neutrinos in Deep Ice
10508,118014635,696.0,,2,24,/bowaka/icecube-simple-detector-of-muon-neutrino-type,IceCube - Neutrinos in Deep Ice
10509,117122448,719.0,,9,26,/vshantam/icecube-neutrinos-in-deep-ice-eda,IceCube - Neutrinos in Deep Ice
10510,117487283,717.0,,1,22,/kennytanner/cherenkov-light-emission-cone-detection,IceCube - Neutrinos in Deep Ice
10511,117282700,729.0,1.5648533672208862,2,4,/astrung/pcaembed-gpu-catboost-optuna-approach,IceCube - Neutrinos in Deep Ice
10512,118807251,732.0,,1,11,/mmakhyanov/eda-and-first-look,IceCube - Neutrinos in Deep Ice
10513,120423573,739.0,,0,5,/ehsankhajeh/cubic-ice-v2,IceCube - Neutrinos in Deep Ice
10514,117795443,748.0,,4,9,/kaggleqrdl/probing-notebook,IceCube - Neutrinos in Deep Ice
10515,117877031,768.0,1.5521068058228231,2,9,/thenotfish/neutrinolstm,IceCube - Neutrinos in Deep Ice
10516,122714568,772.0,,0,1,/kaggsouma/ice-submission,IceCube - Neutrinos in Deep Ice
10517,122714568,772.0,,0,1,/kaggsouma/ice-submission,IceCube - Neutrinos in Deep Ice
10518,120280750,780.0,,0,16,/earyzhe/icecube-neutrinos-basic-pca-prediction,IceCube - Neutrinos in Deep Ice
10519,125412607,784.0,,0,0,/vaibhavsharma3012/icecube-neutrinos-in-deep-ice-1,IceCube - Neutrinos in Deep Ice
10520,120526179,792.0,1.5710895011160382,0,6,/younesselbrag/icecube-baseline-randomforest,IceCube - Neutrinos in Deep Ice
10521,117651760,241.0,0.8375225240681783,7,13,/satyaprakashshukl/xgb-prediction-v1,Binary Classification with a Tabular Credit Card Fraud Dataset
10522,117145169,176.0,0.809933032919685,9,46,/ravi20076/playgrounds3e4-eda-focalloss,Binary Classification with a Tabular Credit Card Fraud Dataset
10523,117150834,256.0,,0,2,/sadmansakib7/eda-original-synthetic-data-correlation,Binary Classification with a Tabular Credit Card Fraud Dataset
10524,159887429,275.0,,12,66,/javohirtoshqorgonov/credit-card-fraud-eda-optuna,Binary Classification with a Tabular Credit Card Fraud Dataset
10525,117543021,257.0,0.8320787245743496,0,2,/bernhardklinger/automl-baseline-v2,Binary Classification with a Tabular Credit Card Fraud Dataset
10526,117381016,97.0,,10,44,/devsubhash/playground-s3e4-eda-fraud-detection,Binary Classification with a Tabular Credit Card Fraud Dataset
10527,117592939,186.0,,8,74,/odins0n/playground-s-3-e-4-eda-modelling,Binary Classification with a Tabular Credit Card Fraud Dataset
10528,117420995,61.0,,15,35,/vaidyaprasad84/ps3-e4-eda-sampling-ft,Binary Classification with a Tabular Credit Card Fraud Dataset
10529,117680504,307.0,0.5894366641287,12,69,/ashishkumarak/credit-card-fraud-detection-tensorflow,Binary Classification with a Tabular Credit Card Fraud Dataset
10530,117684836,326.0,,23,58,/cv13j0/pss-3-episode-4-quick-start-gbdt,Binary Classification with a Tabular Credit Card Fraud Dataset
10531,117546591,156.0,,3,8,/ebrahimghantiwala/beginners-ensemble-approach,Binary Classification with a Tabular Credit Card Fraud Dataset
10532,117762878,226.0,0.8619519220692744,2,6,/magnussesodia/ps-s3e4-subsampling-ensemble-modelling,Binary Classification with a Tabular Credit Card Fraud Dataset
10533,117436815,31.0,0.8545063438348275,16,48,/soupmonster/simple-lgbm-baseline-optuna,Binary Classification with a Tabular Credit Card Fraud Dataset
10534,117771374,138.0,,2,5,/sagar118/pss3e4-eda,Binary Classification with a Tabular Credit Card Fraud Dataset
10535,117157815,302.0,0.8524702515369228,2,14,/manishwahale/ps-s3-e4-starter-eda-models,Binary Classification with a Tabular Credit Card Fraud Dataset
10536,117420776,333.0,0.8602527054385134,1,2,/shadowhat/join-live-card-fraud-detection-with-pycaret,Binary Classification with a Tabular Credit Card Fraud Dataset
10537,117644328,95.0,0.8584695597014164,1,2,/kirillka95/eda-16-models-test-ensemble,Binary Classification with a Tabular Credit Card Fraud Dataset
10538,117148646,63.0,,5,9,/craigmthomas/play-s3e4-eda-models,Binary Classification with a Tabular Credit Card Fraud Dataset
10539,117681418,78.0,0.8462683079057508,13,33,/chunweishen/ps-s03e04-ensembling,Binary Classification with a Tabular Credit Card Fraud Dataset
10540,117555331,295.0,0.8491028859556465,0,5,/omarvivas/cb-tpgs-s3e4-v1,Binary Classification with a Tabular Credit Card Fraud Dataset
10541,117778704,22.0,,0,0,/edgarbc/playground-s3e4-lgbm-baseline,Binary Classification with a Tabular Credit Card Fraud Dataset
10542,117318419,58.0,,0,1,/kaggleqrdl/pg-series-s3e4-adversarial-validation,Binary Classification with a Tabular Credit Card Fraud Dataset
10543,117274497,27.0,0.8414407613529187,4,16,/paddykb/ps-s3e4-lightautoml-multistart,Binary Classification with a Tabular Credit Card Fraud Dataset
10544,117734669,73.0,0.8402286581266096,13,14,/satoshiss/fraud-predictions-s3e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10545,117512465,278.0,0.8492860461600811,1,12,/masayakawamata/lightgbm-xgboost-logreg-ensemble,Binary Classification with a Tabular Credit Card Fraud Dataset
10546,117527670,13.0,0.8429742064062484,12,20,/shilongzhuang/s3e4-sweetz-do-eda-like-a-chad-lgbm-optuna,Binary Classification with a Tabular Credit Card Fraud Dataset
10547,117527670,13.0,0.8429742064062484,12,20,/shilongzhuang/s3e4-sweetz-do-eda-like-a-chad-lgbm-optuna,Binary Classification with a Tabular Credit Card Fraud Dataset
10548,117707301,99.0,0.8429714242259279,1,3,/mukaseevru/ps-s3e4-lama-lightautoml-fe-extra-data,Binary Classification with a Tabular Credit Card Fraud Dataset
10549,118949274,263.0,,20,38,/abhi011097/detailed-eda-org-new-data-model,Binary Classification with a Tabular Credit Card Fraud Dataset
10550,117433922,206.0,0.8523144494389734,0,4,/manavd22/boosting-ensemble-bayesian-tuning-cv,Binary Classification with a Tabular Credit Card Fraud Dataset
10551,117396125,105.0,0.8362021476577287,2,10,/ifuurh/xgboost,Binary Classification with a Tabular Credit Card Fraud Dataset
10552,117444184,39.0,,0,6,/fadhilmuh/ranked-39-641-pss3e4-with-only-downsampling,Binary Classification with a Tabular Credit Card Fraud Dataset
10553,118159446,252.0,0.8434893734622657,12,31,/inaciobr/ps-s03e04-eda-multiple-models,Binary Classification with a Tabular Credit Card Fraud Dataset
10554,117436715,86.0,0.8245566363810882,2,9,/belati/pss3e4-fraud-detection,Binary Classification with a Tabular Credit Card Fraud Dataset
10555,117611527,230.0,0.8475383732220708,10,14,/sharvalishinde/ps-s3e4-lgbm-xgb-optuna-weighted-avg,Binary Classification with a Tabular Credit Card Fraud Dataset
10556,118323097,341.0,,10,46,/kevinmorgado/credit-card-fraud-analysis-s3-e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10557,117324253,148.0,,1,14,/tilii7/the-autoencoder-says-that-data-is-different,Binary Classification with a Tabular Credit Card Fraud Dataset
10558,117745822,300.0,0.8249215656997971,14,33,/khaledgamal1/ep3-4-ensemble-model,Binary Classification with a Tabular Credit Card Fraud Dataset
10559,117465537,108.0,,5,13,/slythe/powershap-automated-feature-selection-recursive,Binary Classification with a Tabular Credit Card Fraud Dataset
10560,117234549,306.0,0.8261253223851447,0,1,/nnjjpp/play-3-4-two-baseline-models,Binary Classification with a Tabular Credit Card Fraud Dataset
10561,117153014,282.0,,21,58,/burhanuddinlatsaheb/eda-ensembling-3-models,Binary Classification with a Tabular Credit Card Fraud Dataset
10562,117486277,62.0,,0,3,/kirkdco/ae-combined,Binary Classification with a Tabular Credit Card Fraud Dataset
10563,117948217,388.0,0.8344375497894353,3,14,/amrelsayeh/pgs-s3e4-ensemble,Binary Classification with a Tabular Credit Card Fraud Dataset
10564,117284750,98.0,0.8422642867277943,1,4,/vlad15lav/ps-s03e04-eda-with-pt-ensemble-cv-optuna,Binary Classification with a Tabular Credit Card Fraud Dataset
10565,117689754,125.0,0.840987265960673,5,20,/akioonodera/ps-3-04-lgbm-bin,Binary Classification with a Tabular Credit Card Fraud Dataset
10566,118087997,52.0,,1,3,/umanglodaya/playground-series-s3e4-xgboost,Binary Classification with a Tabular Credit Card Fraud Dataset
10567,117171137,123.0,0.8408782972314524,0,2,/datascientistsohail/lgbmclassifier-optuna-se03ep04,Binary Classification with a Tabular Credit Card Fraud Dataset
10568,117642735,207.0,,3,14,/mohammednabil98/meau-catboost,Binary Classification with a Tabular Credit Card Fraud Dataset
10569,117312553,212.0,0.8220744678384592,8,16,/samir95/i-still-suck-at-eda-less-though,Binary Classification with a Tabular Credit Card Fraud Dataset
10570,117765141,149.0,,2,10,/eliotlacroix/ps3e4-trying-neural-networks-with-pytorch,Binary Classification with a Tabular Credit Card Fraud Dataset
10571,117514027,127.0,0.8393606178666055,2,24,/snorfyang/catboost-xgboost-lgbm,Binary Classification with a Tabular Credit Card Fraud Dataset
10572,119205888,121.0,,2,7,/ryangreiner/s3e4-imbalanced-learning,Binary Classification with a Tabular Credit Card Fraud Dataset
10573,117214752,79.0,,0,2,/mobenmo/xgboost-grid-search-0-82-score,Binary Classification with a Tabular Credit Card Fraud Dataset
10574,119306328,76.0,,7,36,/oscarm524/ps-s3-ep4-eda-modeling,Binary Classification with a Tabular Credit Card Fraud Dataset
10575,117322537,179.0,,2,6,/kmskojim/3models-ensemble,Binary Classification with a Tabular Credit Card Fraud Dataset
10576,117763195,68.0,,0,3,/ashtcoder/playground-series-s3-e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10577,117260057,344.0,0.8274533497914756,0,13,/abraamadamidis/randomsearch-ensemble-xgb-lgbm-cb,Binary Classification with a Tabular Credit Card Fraud Dataset
10578,117344443,136.0,,0,1,/guptadikshant/xgb-optuna-starter-0-836,Binary Classification with a Tabular Credit Card Fraud Dataset
10579,117722750,110.0,0.8238221407764694,2,16,/marwanyasser/ps-se3ep4,Binary Classification with a Tabular Credit Card Fraud Dataset
10580,117845324,3.0,0.8354581462703482,2,11,/olliekemp/3rd-place-solution-ensemble-catboost,Binary Classification with a Tabular Credit Card Fraud Dataset
10581,117441887,150.0,,0,6,/catadanna/tab-jan-2023-e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10582,117231668,336.0,,12,16,/mkr9395/undersampling-lightgbm-credit-card-fraud,Binary Classification with a Tabular Credit Card Fraud Dataset
10583,137724396,246.0,,0,0,/cemduru/fraud-detection-and-optuna-parameter-optimization,Binary Classification with a Tabular Credit Card Fraud Dataset
10584,118288111,384.0,,2,9,/ahana09/ps-s3e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10585,117746776,131.0,0.8156569052324465,0,1,/pranjalrathore/fraud-detection,Binary Classification with a Tabular Credit Card Fraud Dataset
10586,117569681,310.0,0.8319366015296428,0,1,/barbagrande007/bbg007-s3e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10587,117567453,345.0,,2,2,/ryancaldwell/my-attempt-at-tilii-s-tsne-class-separation,Binary Classification with a Tabular Credit Card Fraud Dataset
10588,117214133,47.0,0.829937836817705,0,2,/jamiedonaldmccann/ps-s3e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10589,117288385,332.0,,18,48,/kimtaehun/simple-baseline-model-with-smote-auc-90,Binary Classification with a Tabular Credit Card Fraud Dataset
10590,117422075,172.0,0.825539673427674,0,12,/matthewjansen/credit-card-fraud-detection-xgboost-baseline,Binary Classification with a Tabular Credit Card Fraud Dataset
10591,117761008,347.0,,0,2,/rebeccapringle/credit-card-fraud-detection-model,Binary Classification with a Tabular Credit Card Fraud Dataset
10592,117710227,391.0,0.8269942900385888,4,11,/shiv7080/fraud-detection,Binary Classification with a Tabular Credit Card Fraud Dataset
10593,117688955,407.0,0.8132767499682367,2,9,/prem00/follow-the-trend,Binary Classification with a Tabular Credit Card Fraud Dataset
10594,117146959,356.0,,2,10,/gauravduttakiit/pss3e4-lazypredict,Binary Classification with a Tabular Credit Card Fraud Dataset
10595,117350348,475.0,,4,13,/sujaykapadnis/get-started-with-playground-s3e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10596,117519557,185.0,0.8229109767214973,0,6,/amoghgarg20/playground-s3e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10597,117589787,411.0,,0,6,/krviswanathan/credit-card-fraud-baseline-smote-ensemble,Binary Classification with a Tabular Credit Card Fraud Dataset
10598,117862848,438.0,,10,22,/hikmatullahmohammadi/simple-credit-card-fraud-detection-ps-s3e4,Binary Classification with a Tabular Credit Card Fraud Dataset
10599,117197344,403.0,0.8210914307918734,1,13,/tracyporter/play-3-4-logreg,Binary Classification with a Tabular Credit Card Fraud Dataset
10600,117375311,401.0,,2,6,/nhopet/playgroundseriesseason3episode4-data-visualization,Binary Classification with a Tabular Credit Card Fraud Dataset
10601,117764408,360.0,0.6174170516122272,0,0,/rohans1497/ps-s3e4-v3-with-lgbm,Binary Classification with a Tabular Credit Card Fraud Dataset
10602,117543426,398.0,0.8133377260869283,0,4,/normangitosh/tabular-classification-with-a-credit-card-fraud,Binary Classification with a Tabular Credit Card Fraud Dataset
10603,117448506,454.0,,1,2,/statchaitya/eda-logistic-regression-with-smote,Binary Classification with a Tabular Credit Card Fraud Dataset
10604,117216828,464.0,0.811457204038613,0,2,/regiusherder/prediction-with-deeplearning-tensorflow,Binary Classification with a Tabular Credit Card Fraud Dataset
10605,117160467,377.0,,1,5,/stpeteishii/pss3-ep4-visualize-importance,Binary Classification with a Tabular Credit Card Fraud Dataset
10606,117604476,421.0,0.8077128530239054,0,1,/ch124uec/plotly-data-viz-xgboost-model-tuning,Binary Classification with a Tabular Credit Card Fraud Dataset
10607,117431183,485.0,,0,3,/ryankkien/playground-s3e2-fastai-model,Binary Classification with a Tabular Credit Card Fraud Dataset
10608,117766131,406.0,0.7894928178015026,0,0,/mohammedalmasry/credit-card-fraud-detection,Binary Classification with a Tabular Credit Card Fraud Dataset
10609,117716155,457.0,0.7812160631962985,0,6,/sergeyyakovlev1312/playground-s3e4-naive-bayes,Binary Classification with a Tabular Credit Card Fraud Dataset
10610,117176347,481.0,0.7805981873167819,4,11,/takshpanchal/ps-s3-ep04-initial-eda-xgboost,Binary Classification with a Tabular Credit Card Fraud Dataset
10611,117848328,413.0,,0,0,/iamnotashutosh/pg-s3-e4-random-over-sampling,Binary Classification with a Tabular Credit Card Fraud Dataset
10612,117353965,496.0,0.7681270640300253,0,0,/azazali/playground-series-4-ensemble-learning,Binary Classification with a Tabular Credit Card Fraud Dataset
10613,117346533,539.0,0.6789405642818126,2,1,/fuad0857/playground-series-4-with-tensorflow,Binary Classification with a Tabular Credit Card Fraud Dataset
10614,118305320,503.0,,1,7,/qiaoningchen/credit-card-fraud-prediction,Binary Classification with a Tabular Credit Card Fraud Dataset
10615,117157876,519.0,,3,7,/rohan8771/playground-s3e4-undersampling-xgboost,Binary Classification with a Tabular Credit Card Fraud Dataset
10616,117252052,537.0,,0,1,/maheswarareddyp/palyground-series-s3e4-mahesh,Binary Classification with a Tabular Credit Card Fraud Dataset
10617,118193322,527.0,,1,1,/teowaihong/credit-card-fraud-detection-with-sklearn,Binary Classification with a Tabular Credit Card Fraud Dataset
10618,117199485,525.0,0.714695754671049,0,2,/sharansmenon/credit-card-fraud-with-xgboost,Binary Classification with a Tabular Credit Card Fraud Dataset
10619,117342207,553.0,0.6761797140104109,0,5,/smackia/xgb-cbr-lgb-easy,Binary Classification with a Tabular Credit Card Fraud Dataset
10620,117612556,563.0,,0,1,/shamimahossain/tree-models-baseline,Binary Classification with a Tabular Credit Card Fraud Dataset
10621,117246498,587.0,,0,0,/anshulkunwar/notebook0c4b6942ed,Binary Classification with a Tabular Credit Card Fraud Dataset
10622,117172896,607.0,,0,1,/ashokkumargarain/notebook162733468d,Binary Classification with a Tabular Credit Card Fraud Dataset
10623,118543541,11.0,,1,15,/nahman/discover-top-hidden-bots,Lux AI Season 2
10624,122982165,35.0,,0,11,/tosyama/light-robot-rl-on-simple-virtual-lux-ai-env,Lux AI Season 2
10625,123012340,42.0,,15,36,/jtbontinck/shortest-path-on-mars-using-networkx,Lux AI Season 2
10626,126487617,99.0,,5,12,/yoyobar/il-with-lux-json-data-to-map-based-observation,Lux AI Season 2
10627,126313796,105.0,568.169594982219,0,0,/elvenmonk/simple-tests,Lux AI Season 2
10628,118670460,107.0,,4,28,/kuto0633/luxai2-episode-scraper-match-downloader,Lux AI Season 2
10629,118173432,109.0,,3,9,/shin7jp/lux-ai-challenge-season-2-tutorial-python,Lux AI Season 2
10630,119811802,213.0,191.75202854690616,0,0,/joshmijoshuamable/lux-ai-challenge-season-2,Lux AI Season 2
10631,122682280,232.0,,1,8,/takeshiiijima/eda-episode-json,Lux AI Season 2
10632,119089900,389.0,411.96773551867466,21,144,/stonet2000/lux-ai-challenge-season-2-tutorial-python,Lux AI Season 2
10633,117857870,415.0,,2,28,/klukin/ppo-example,Lux AI Season 2
10634,118041893,469.0,,1,54,/istinetz/picking-a-good-starting-location,Lux AI Season 2
10635,122653257,560.0,125.78377845399896,0,1,/stevennoel/notebook4b9b41f544,Lux AI Season 2
10636,126778108,571.0,137.4942784280665,0,29,/parikshitsharma2001/lux-ai-challenge-season-2,Lux AI Season 2
10637,119000935,42.0,,8,28,/nightwolfbrooks/multinomial-logistic-regression-neural-network,Ordinal Regression with a Tabular Wine Quality Dataset
10638,119023860,16.0,,0,3,/jbomitchell/boltzmann-ensemble-match-to-ideal-distribution,Ordinal Regression with a Tabular Wine Quality Dataset
10639,119125831,3.0,0.6301900195347185,1,6,/group16/mode-ensemble-3-private,Ordinal Regression with a Tabular Wine Quality Dataset
10640,118595758,18.0,0.5832625919637804,6,23,/paddykb/ps-s3e5-regression-optimise-class-cutoff,Ordinal Regression with a Tabular Wine Quality Dataset
10641,118809845,143.0,0.5483622080381566,0,12,/omarvivas/lgbm-tpgs-s3e5-v1,Ordinal Regression with a Tabular Wine Quality Dataset
10642,118579516,51.0,,0,5,/tushirsahu/wine-prediction-hyperparameter-tuning,Ordinal Regression with a Tabular Wine Quality Dataset
10643,117903185,175.0,0.5940546740584973,5,21,/jano123/ps-s03e05-symbolic-regression,Ordinal Regression with a Tabular Wine Quality Dataset
10644,118226084,86.0,0.5787207872078721,0,7,/icfoer/playground-stacking-solution,Ordinal Regression with a Tabular Wine Quality Dataset
10645,118830403,155.0,,1,14,/negoto/ps3-5-k-nearest-neighbors-regression-r,Ordinal Regression with a Tabular Wine Quality Dataset
10646,117845528,93.0,,12,40,/mattop/playground-series-s3-e5-eda-pca,Ordinal Regression with a Tabular Wine Quality Dataset
10647,132309924,37.0,,0,5,/amingraja12/ensemble-model-with-optimizedrounder,Ordinal Regression with a Tabular Wine Quality Dataset
10648,118318037,111.0,,1,4,/jacobsharples/s03e05-eda-with-seaborn-and-feature-engineering,Ordinal Regression with a Tabular Wine Quality Dataset
10649,119947378,82.0,,13,59,/phongnguyen1/s3e5-from-eda-to-final-submission,Ordinal Regression with a Tabular Wine Quality Dataset
10650,118680394,69.0,0.5947212724269084,4,18,/satoshiss/wine-quality-predictions-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10651,118930459,302.0,,0,2,/xbulat/neural-network-for-wine-recognition,Ordinal Regression with a Tabular Wine Quality Dataset
10652,118101564,176.0,0.5794966236955187,18,61,/soupmonster/s03e05-eda-modeling,Ordinal Regression with a Tabular Wine Quality Dataset
10653,118652804,386.0,0.5513066654620198,0,9,/klyushnik/5-episode,Ordinal Regression with a Tabular Wine Quality Dataset
10654,118742926,520.0,,0,5,/ramkan07/ps3e5-wine-quality-models-59,Ordinal Regression with a Tabular Wine Quality Dataset
10655,119086094,218.0,,28,62,/oscarm524/ps-s3-ep5-eda-modeling,Ordinal Regression with a Tabular Wine Quality Dataset
10656,118377747,67.0,,9,20,/saidislombek/playground-series-s3-e5-lazypredict,Ordinal Regression with a Tabular Wine Quality Dataset
10657,117774554,44.0,,0,2,/k0takahashi/ps-s3e5-2023-chart,Ordinal Regression with a Tabular Wine Quality Dataset
10658,118703559,174.0,,1,13,/shoabahamed/playground-s-3-ep-5-eda-and-model-selection,Ordinal Regression with a Tabular Wine Quality Dataset
10659,117785467,104.0,,0,6,/gauravmalik26/ps-s03e05-xgboost-baseline,Ordinal Regression with a Tabular Wine Quality Dataset
10660,118165095,112.0,,0,6,/yimingliang/s3e5-eda,Ordinal Regression with a Tabular Wine Quality Dataset
10661,130618954,434.0,0.538426516117283,3,3,/hermengardo/random-forest-eda-wine-quality-prediction,Ordinal Regression with a Tabular Wine Quality Dataset
10662,117961043,391.0,,3,9,/jhotor/winedatasetsynthetic,Ordinal Regression with a Tabular Wine Quality Dataset
10663,118219090,467.0,,4,7,/edgarbc/ps-s3e5-eda-baseline-submission,Ordinal Regression with a Tabular Wine Quality Dataset
10664,118870708,285.0,0.5695479668830128,1,10,/pranjalrathore/wine-classification,Ordinal Regression with a Tabular Wine Quality Dataset
10665,118637046,206.0,,0,1,/dylanfazo/multimodelblending-playground-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10666,117993207,295.0,0.5662179611908089,7,21,/chunweishen/ps-s03e05-ensembling,Ordinal Regression with a Tabular Wine Quality Dataset
10667,119079493,475.0,0.4223825123767832,3,7,/casati8/kaggle-s3exp5-fastai,Ordinal Regression with a Tabular Wine Quality Dataset
10668,118367970,242.0,,9,37,/validmodel/playground-s3-e5-eda-model-featureengg,Ordinal Regression with a Tabular Wine Quality Dataset
10669,118868142,98.0,,1,6,/danilcherinov/ps-s03e05-eda-rf,Ordinal Regression with a Tabular Wine Quality Dataset
10670,118305640,379.0,,8,26,/hikmatullahmohammadi/wine-quality-tf-keras-dnn-eda-ps-s3-ep5,Ordinal Regression with a Tabular Wine Quality Dataset
10671,119045150,199.0,0.5702845193869153,9,5,/boyochan/ps-s3-e5-use-lightgbm-optuna,Ordinal Regression with a Tabular Wine Quality Dataset
10672,118882690,196.0,0.5584491966029125,0,1,/sahilsg/wine-s03-e05-n1,Ordinal Regression with a Tabular Wine Quality Dataset
10673,119254817,289.0,,0,2,/moohamedelsayed/wine-quality-prediction-regression-models,Ordinal Regression with a Tabular Wine Quality Dataset
10674,120888384,416.0,,0,1,/rohanmudgalkar/playground-season3-e5,Ordinal Regression with a Tabular Wine Quality Dataset
10675,118465522,309.0,,0,10,/sujaykapadnis/ps-s3e5-eda-easy-to-understand-modeling,Ordinal Regression with a Tabular Wine Quality Dataset
10676,117920668,288.0,,4,7,/donjoeml/s3e5-first-impression,Ordinal Regression with a Tabular Wine Quality Dataset
10677,118122813,164.0,0.4497991967871485,2,10,/qiaoningchen/wine-quality-prediction-xgbboot-optimazation,Ordinal Regression with a Tabular Wine Quality Dataset
10678,118993233,393.0,,4,12,/bonniehall/s3-e5-feature-selection,Ordinal Regression with a Tabular Wine Quality Dataset
10679,119054177,305.0,0.5656505018290967,0,2,/ashtcoder/playground-series-s3-e5,Ordinal Regression with a Tabular Wine Quality Dataset
10680,117977803,425.0,,12,33,/akioonodera/ps-3-05-lgbm-multiclass,Ordinal Regression with a Tabular Wine Quality Dataset
10681,118875469,273.0,0.4014868093939321,15,47,/ashishkumarak/wine-quality-prediction-tensorflow,Ordinal Regression with a Tabular Wine Quality Dataset
10682,118631842,237.0,0.5334704605187979,2,6,/inaciobr/ps-s03e05-viz-classifiers-regressors,Ordinal Regression with a Tabular Wine Quality Dataset
10683,117863143,194.0,,2,9,/mobenmo/get-started-xgboost-eda-0-55-score,Ordinal Regression with a Tabular Wine Quality Dataset
10684,119067789,400.0,,0,1,/mckayla/ps-s3-e5-wine-quality,Ordinal Regression with a Tabular Wine Quality Dataset
10685,117817667,458.0,0.5611864332411918,4,14,/snorfyang/ps-s03e05-catboost,Ordinal Regression with a Tabular Wine Quality Dataset
10686,117834348,484.0,0.4902119398155636,1,4,/priyanagda/ps3-05-smote-ensemble,Ordinal Regression with a Tabular Wine Quality Dataset
10687,118298654,608.0,0.5611531741409436,0,3,/sukantabasu/prediction-of-wine-quality-by-flaml,Ordinal Regression with a Tabular Wine Quality Dataset
10688,120547129,290.0,,0,0,/shuhei102/eda-t-sne-arcface,Ordinal Regression with a Tabular Wine Quality Dataset
10689,118964780,332.0,,0,0,/alessandrozanette/playground-s3e5-eda-pca-nn,Ordinal Regression with a Tabular Wine Quality Dataset
10690,119072622,485.0,,0,2,/abraamadamidis/ensemble-xgb-lgbm-cb,Ordinal Regression with a Tabular Wine Quality Dataset
10691,118363505,211.0,0.5538843231508761,0,5,/mnokno/wine-quality-classification-using-ann,Ordinal Regression with a Tabular Wine Quality Dataset
10692,118396939,308.0,,0,4,/ryangreiner/s3e5-apply-imbalanced-method,Ordinal Regression with a Tabular Wine Quality Dataset
10693,117979279,325.0,,1,3,/lucasgbezerra/ps-s03-e05-parte-5,Ordinal Regression with a Tabular Wine Quality Dataset
10694,118410349,312.0,0.5420630653794911,0,1,/mukaseevru/ps-s3e5-lama-lightautoml-fe-extra-data,Ordinal Regression with a Tabular Wine Quality Dataset
10695,119258483,2.0,,0,3,/nhopet/pgss3e5-eda-heatmap-boxplot-outlierfilter,Ordinal Regression with a Tabular Wine Quality Dataset
10696,118610029,405.0,,0,0,/iamnotashutosh/playground-s3-e5,Ordinal Regression with a Tabular Wine Quality Dataset
10697,119012107,783.0,0.5369291621718807,2,12,/sergeyyakovlev1312/playground-s3e5-logistic-regression,Ordinal Regression with a Tabular Wine Quality Dataset
10698,118035721,678.0,0.502642341804145,1,12,/ch124uec/wine-tasting-with-plotly-viz-xgboost-tuning,Ordinal Regression with a Tabular Wine Quality Dataset
10699,119082201,571.0,0.5552566896999489,0,0,/mcaputo/r-intermediate-session-winequality-dl-dataset,Ordinal Regression with a Tabular Wine Quality Dataset
10700,118152982,423.0,,10,19,/jimgruman/tidymodels-stack,Ordinal Regression with a Tabular Wine Quality Dataset
10701,118189040,374.0,0.5187468635744497,0,7,/docxian/ps-s3-e5-linear-model-for-multiclass-problem,Ordinal Regression with a Tabular Wine Quality Dataset
10702,117997146,231.0,0.5414951833928814,4,17,/shilongzhuang/s3e5-training-with-data-from-uci,Ordinal Regression with a Tabular Wine Quality Dataset
10703,117997146,231.0,0.5414951833928814,4,17,/shilongzhuang/s3e5-training-with-data-from-uci,Ordinal Regression with a Tabular Wine Quality Dataset
10704,118001912,356.0,,1,6,/lavagod/pc-s03e05-catboost-code-0-55378,Ordinal Regression with a Tabular Wine Quality Dataset
10705,117937419,723.0,0.5529196657948944,2,8,/utkarshgaikwad1994/plg-s3e5-utkarsh-gaikwad,Ordinal Regression with a Tabular Wine Quality Dataset
10706,119010691,24.0,,1,2,/davidhguerrero/23205-pss3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10707,118443434,212.0,,10,14,/priyankapalshetkar/playground-s3-e5,Ordinal Regression with a Tabular Wine Quality Dataset
10708,118526380,428.0,,2,9,/christrandata/eda-lgbm-xgboost,Ordinal Regression with a Tabular Wine Quality Dataset
10709,118123130,776.0,0.5339912806017344,0,13,/wojciechdobrychop/deep-learning-works-too-i-guess-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10710,118647056,692.0,0.5489032138385197,7,18,/shiv7080/ps-3-5-xgb-with-cluster-pca,Ordinal Regression with a Tabular Wine Quality Dataset
10711,117956142,349.0,,0,2,/vivekvarma23/ps-s3e5-eda-catboost,Ordinal Regression with a Tabular Wine Quality Dataset
10712,118659054,652.0,,0,6,/kosimon/start-playground-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10713,117950043,403.0,,4,13,/amrelsayeh/pgs-s3e5-eda-logistic-regression,Ordinal Regression with a Tabular Wine Quality Dataset
10714,117862739,372.0,,1,6,/eliotlacroix/ps3e5-eda-baseline-lgbm-ensemble-model,Ordinal Regression with a Tabular Wine Quality Dataset
10715,118435163,424.0,,0,0,/sapnajha0304/s3-ep-5,Ordinal Regression with a Tabular Wine Quality Dataset
10716,118421165,152.0,0.53277512524402,9,22,/pardeep19singh/pss3e5-eda-and-modeling-using-original-dataset,Ordinal Regression with a Tabular Wine Quality Dataset
10717,119082749,511.0,,0,2,/bradywagner/playground-series-season-3-episode-5-bw-dw,Ordinal Regression with a Tabular Wine Quality Dataset
10718,117987517,650.0,0.5062485373274046,1,10,/masayakawamata/randomforest-t-sne,Ordinal Regression with a Tabular Wine Quality Dataset
10719,117894008,486.0,0.4819092395748159,0,9,/cv13j0/pss-3-episode-5-a-simple-model,Ordinal Regression with a Tabular Wine Quality Dataset
10720,118469920,157.0,0.5421177977465127,0,1,/jamiedonaldmccann/ps-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10721,118153037,409.0,,4,9,/lusfernandotorres/playground-s03e05-wine-quality-prediction,Ordinal Regression with a Tabular Wine Quality Dataset
10722,137724725,251.0,,0,0,/cemduru/feature-engineering-and-keras-deep-learning,Ordinal Regression with a Tabular Wine Quality Dataset
10723,117877550,456.0,0.5229761304805974,18,33,/matthewjansen/wine-quality-prediction-baseline,Ordinal Regression with a Tabular Wine Quality Dataset
10724,119906989,1.0,0.5390571162187361,6,17,/rapela/tpss3e5-1st-place-solution-rapids-xgboost,Ordinal Regression with a Tabular Wine Quality Dataset
10725,117778568,462.0,,12,44,/burhanuddinlatsaheb/eda-4-0-different-model,Ordinal Regression with a Tabular Wine Quality Dataset
10726,119085216,259.0,,0,8,/jedchristensen/playground-season-3-episode-5-eda-lr,Ordinal Regression with a Tabular Wine Quality Dataset
10727,118107013,268.0,,2,12,/adivireza/pg-s3e5-wine-quality-prediction,Ordinal Regression with a Tabular Wine Quality Dataset
10728,118349872,525.0,0.5259955880645536,2,6,/fuad0857/playground-series-season-3-episode-5,Ordinal Regression with a Tabular Wine Quality Dataset
10729,117878371,466.0,,2,9,/abdoulayebalde/pss3-e5-eda-catboost-baseline-model,Ordinal Regression with a Tabular Wine Quality Dataset
10730,117784858,468.0,,1,9,/gauravduttakiit/pss3e5-lazypredict,Ordinal Regression with a Tabular Wine Quality Dataset
10731,117955936,517.0,0.0471782722734581,0,4,/sanketsz/baseline-catboost-score-0-53,Ordinal Regression with a Tabular Wine Quality Dataset
10732,119008032,586.0,,2,4,/atrijtalgery/pss3e5quantilediscr-n-adaboostednb,Ordinal Regression with a Tabular Wine Quality Dataset
10733,118181612,381.0,0.5278250080419099,9,13,/krviswanathan/wine-quality-eda-feature-engg-prediction,Ordinal Regression with a Tabular Wine Quality Dataset
10734,123387384,712.0,,0,6,/jakubwalczykowski/wine-classification-tf-pca,Ordinal Regression with a Tabular Wine Quality Dataset
10735,118423963,778.0,,4,5,/trushatalati/pse5-easy-eda-logistic-regression,Ordinal Regression with a Tabular Wine Quality Dataset
10736,118955391,490.0,0.5132706374085685,0,2,/rebeccapringle/playground-s3e5-competition,Ordinal Regression with a Tabular Wine Quality Dataset
10737,119873045,380.0,,0,4,/kavishchaudhary1003/playground-s3-e5,Ordinal Regression with a Tabular Wine Quality Dataset
10738,120264463,695.0,0.54999110046763,1,5,/scirpus/jeepy-booze,Ordinal Regression with a Tabular Wine Quality Dataset
10739,118927329,688.0,0.0,1,9,/tylergermain/wine-quality-prediction-support-vector-machines,Ordinal Regression with a Tabular Wine Quality Dataset
10740,118482222,753.0,,0,0,/massimot/pgs-s3-e5,Ordinal Regression with a Tabular Wine Quality Dataset
10741,117842962,755.0,0.5224885408708939,0,3,/tracyporter/play-3-5,Ordinal Regression with a Tabular Wine Quality Dataset
10742,117799849,402.0,,1,7,/vlad15lav/s3e5-eda-for-all-columns,Ordinal Regression with a Tabular Wine Quality Dataset
10743,118220917,377.0,,0,0,/natchimuthun/ps3e5-wine-quality-prediction,Ordinal Regression with a Tabular Wine Quality Dataset
10744,119088377,280.0,0.5165431163110155,1,7,/kirillka95/s3e5-eda-models-test,Ordinal Regression with a Tabular Wine Quality Dataset
10745,117807275,314.0,,0,3,/ashokkumargarain/notebook6540c99e58,Ordinal Regression with a Tabular Wine Quality Dataset
10746,117873836,589.0,,1,9,/refat094/playground-series-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10747,119115563,713.0,,15,54,/jeyasrisenthil/wine-quality-analysis,Ordinal Regression with a Tabular Wine Quality Dataset
10748,118430319,714.0,,5,31,/harinuu/wine-quality-prediction,Ordinal Regression with a Tabular Wine Quality Dataset
10749,117775662,601.0,0.5104228707564027,20,60,/odins0n/playground-s-3-e-5-eda-modelling,Ordinal Regression with a Tabular Wine Quality Dataset
10750,117775662,601.0,0.5089377152965273,20,60,/odins0n/playground-s-3-e-5-eda-modelling,Ordinal Regression with a Tabular Wine Quality Dataset
10751,118220223,807.0,,0,5,/manavd22/eda-regression-models,Ordinal Regression with a Tabular Wine Quality Dataset
10752,135671603,579.0,,4,17,/kagleo123/playground-s3e5-visualization-modeling,Ordinal Regression with a Tabular Wine Quality Dataset
10753,119003386,750.0,,0,2,/macklinshanahan/ep5-notebook,Ordinal Regression with a Tabular Wine Quality Dataset
10754,118017103,759.0,0.4965742870012565,0,10,/priyanshu594/simple-eda-and-modeling,Ordinal Regression with a Tabular Wine Quality Dataset
10755,137917107,524.0,,0,0,/kieranyogaraj/tps-feb-2023-important-information-1,Ordinal Regression with a Tabular Wine Quality Dataset
10756,118610662,611.0,,1,3,/ericdeuber/wine-quality-predictions-ps-s3-e5-eda-models,Ordinal Regression with a Tabular Wine Quality Dataset
10757,118199779,542.0,0.5041462408943053,0,7,/amoghgarg20/playground-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10758,118458313,575.0,0.5019817537934756,1,3,/kaushalkrishna2000/playground-s03e05,Ordinal Regression with a Tabular Wine Quality Dataset
10759,117994450,773.0,0.4673896362985321,0,7,/stpeteishii/pss3-ep5-visualize-importance,Ordinal Regression with a Tabular Wine Quality Dataset
10760,118995704,591.0,,0,2,/bibhusundarmohapatra/notebookab07d96c16,Ordinal Regression with a Tabular Wine Quality Dataset
10761,118200472,728.0,,3,6,/liuxudong1986/pg-3-05-0-49509-xgb-resample-anomalydetect,Ordinal Regression with a Tabular Wine Quality Dataset
10762,117972972,528.0,,2,11,/kmskojim/eda-baseline-prediction,Ordinal Regression with a Tabular Wine Quality Dataset
10763,118474880,526.0,0.4887353144436767,0,3,/cipollinonewbie/prediction-decision-tree-and-random-forest,Ordinal Regression with a Tabular Wine Quality Dataset
10764,119823766,674.0,,1,16,/riyaelizashaju/wine-quality-random-forest,Ordinal Regression with a Tabular Wine Quality Dataset
10765,117925603,751.0,,2,8,/jaygun84/wine-quality-prediction-pyspark,Ordinal Regression with a Tabular Wine Quality Dataset
10766,147343286,829.0,,11,84,/meeratif/ps-eda-gradientboostingclassifier,Ordinal Regression with a Tabular Wine Quality Dataset
10767,132603500,828.0,,0,6,/benidictusgalihmp/playground-s3e5-regression-tabular-wine-quality,Ordinal Regression with a Tabular Wine Quality Dataset
10768,118239006,580.0,0.438984438984439,2,5,/poloarol/wine-quality-prediction-eda-catboost,Ordinal Regression with a Tabular Wine Quality Dataset
10769,120169201,740.0,0.4513434879342803,2,11,/kattat/wine-quality-prediction-extra-trees-classifier,Ordinal Regression with a Tabular Wine Quality Dataset
10770,119066831,821.0,0.4402841813378839,0,1,/elsayovita/wine-quality-prediction-regression-approach,Ordinal Regression with a Tabular Wine Quality Dataset
10771,117793297,681.0,,3,9,/rohan8771/playground-s3-e5-eda-smote-xgboost,Ordinal Regression with a Tabular Wine Quality Dataset
10772,118957188,736.0,,0,3,/shuvojitdas/regression-classification-model,Ordinal Regression with a Tabular Wine Quality Dataset
10773,118715195,849.0,,1,8,/barbagrande007/bbg007-s3e5,Ordinal Regression with a Tabular Wine Quality Dataset
10774,118000144,845.0,,0,9,/ksqrt9/classification-wine-quality-with-kerasnn,Ordinal Regression with a Tabular Wine Quality Dataset
10775,118641256,826.0,,0,0,/vashalavenugopal75/wine-quality-using-spark,Ordinal Regression with a Tabular Wine Quality Dataset
10776,118086912,745.0,,0,5,/datascientistsohail/wine-quality-eda-se03-ep05,Ordinal Regression with a Tabular Wine Quality Dataset
10777,119002619,837.0,,0,4,/hardikmirani/basic-solution-s3-e5,Ordinal Regression with a Tabular Wine Quality Dataset
10778,118251851,873.0,,0,1,/maheswarareddyp/pss35-winequality-mahesh,Ordinal Regression with a Tabular Wine Quality Dataset
10779,118440118,865.0,,1,3,/shiraeharuto/dnn-regression,Ordinal Regression with a Tabular Wine Quality Dataset
10780,118673784,844.0,0.3720762938299011,0,0,/mohammadahmar/ps-s03e05-eda-and-basic-baseline,Ordinal Regression with a Tabular Wine Quality Dataset
10781,119008913,846.0,0.3655517941773866,0,18,/gokulprasantht/wine-quality,Ordinal Regression with a Tabular Wine Quality Dataset
10782,118997366,852.0,,0,9,/rubanzasilva/fastai-for-ps-s03e05,Ordinal Regression with a Tabular Wine Quality Dataset
10783,118117594,884.0,,0,3,/prem00/power-of-pandas,Ordinal Regression with a Tabular Wine Quality Dataset
10784,118856206,898.0,,0,2,/shaileshgoku/wine-quality-competition,Ordinal Regression with a Tabular Wine Quality Dataset
10785,118453699,895.0,0.0,4,8,/hamdy17298/predict-and-tuning-5-models-for-better-score,Ordinal Regression with a Tabular Wine Quality Dataset
10786,118453699,895.0,0.0,4,8,/hamdy17298/predict-and-tuning-5-models-for-better-score,Ordinal Regression with a Tabular Wine Quality Dataset
10787,120410131,14.0,,14,101,/takanashihumbert/magic-bingo-train-part-lb-0-687,Predict Student Performance from Game Play
10788,123002545,1.0,0.6593194578884856,2,25,/cpmpml/random-submission,Predict Student Performance from Game Play
10789,128699801,7.0,,0,15,/rsakata/psp-1-save-data,Predict Student Performance from Game Play
10790,130127930,24.0,0.6816751237698325,0,1,/wjdzxh/lightgbm-baseline-v2,Predict Student Performance from Game Play
10791,132492462,52.0,,4,12,/flyingdb/xgboost-cv-score-public-lb-private-lb-0-698,Predict Student Performance from Game Play
10792,123308990,63.0,,2,14,/gehallak/train-labels-eda,Predict Student Performance from Game Play
10793,135692389,2.0,,0,1,/mark4h/jowilder-2nd-place-solution-4-submission,Predict Student Performance from Game Play
10794,135312235,97.0,,0,2,/informhunter/polars-static-graph-tests,Predict Student Performance from Game Play
10795,119207101,199.0,,3,26,/curiosity30/reduce-memory-2gb-500mb,Predict Student Performance from Game Play
10796,123497932,739.0,,0,4,/kentatanaka1data/the-training-dataset-into-small-chunks,Predict Student Performance from Game Play
10797,134862828,150.0,0.6975766198448261,0,3,/levdvernik/jo-wilder-test,Predict Student Performance from Game Play
10798,133852375,397.0,0.6996812700270263,12,50,/thelastsmilodon/catboost-xgb-mlp,Predict Student Performance from Game Play
10799,118528928,88.0,,15,95,/cdeotte/predict-train-mean-baseline-0-648,Predict Student Performance from Game Play
10800,122864479,185.0,,9,64,/abaojiang/eda-on-game-progress,Predict Student Performance from Game Play
10801,135228699,224.0,,2,14,/lyalindmitriy/catboost-and-xgb-blend,Predict Student Performance from Game Play
10802,127435862,362.0,,2,13,/kaitokusumoto/eng-eda-on-game-play-dataset,Predict Student Performance from Game Play
10803,134970162,402.0,,0,0,/hideyukizushi/psp-train-cat-xgb-mlp-v0627v1,Predict Student Performance from Game Play
10804,124511007,259.0,,2,21,/tsuyoshifujii/xgboost-using-only-text-which-text-is-important,Predict Student Performance from Game Play
10805,131983223,743.0,,0,3,/jakubzeman/genetic-alogrithm-for-threshold-optimization,Predict Student Performance from Game Play
10806,119541945,212.0,,1,5,/ootake/catboost-baseline-something-wrong,Predict Student Performance from Game Play
10807,135548729,291.0,,0,2,/roberthatch/student-efficiency-polars-inference,Predict Student Performance from Game Play
10808,120567533,163.0,,0,4,/jonathanchan/csc532-tf-keras-tunable,Predict Student Performance from Game Play
10809,123606486,300.0,,4,31,/vadimkamaev/reading-data-953-mb,Predict Student Performance from Game Play
10810,128356713,440.0,0.6724399033303121,0,0,/huangjielun/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10811,133679831,121.0,,8,50,/inoway/catboost-japanese,Predict Student Performance from Game Play
10812,125417028,459.0,,0,4,/senfweow/some-sessions-are-missing-levels-7-15-20-and-21,Predict Student Performance from Game Play
10813,133011077,462.0,0.7000763184366169,0,0,/thangnv8/catboost-mix,Predict Student Performance from Game Play
10814,161932189,276.0,,12,75,/mohammad2012191/reduce-memory-usage-2gb-780mb,Predict Student Performance from Game Play
10815,120985153,897.0,,2,36,/inabower/eda-gameplay-overview-jpn,Predict Student Performance from Game Play
10816,129618128,472.0,,0,3,/kanghong401/replace-env-iter-test,Predict Student Performance from Game Play
10817,133336615,275.0,,10,36,/ivanisaev/0-99-f1-on-a-few-questions-with-simple-nn,Predict Student Performance from Game Play
10818,122909034,274.0,,1,11,/dinowun/eda-simplified-jo-wilder-student-performance,Predict Student Performance from Game Play
10819,118481962,486.0,,0,5,/hidebu/eda-of-predict-student-performance,Predict Student Performance from Game Play
10820,163810585,499.0,,3,30,/vinayaktiwari28/for-beginners-creating-memory-efficient-data,Predict Student Performance from Game Play
10821,127656518,213.0,0.6775012351778656,0,2,/hngphmngc/graduation-thesis-xgboost-baseline,Predict Student Performance from Game Play
10822,122072673,353.0,,1,25,/machengyuan/simple-xgb-model,Predict Student Performance from Game Play
10823,122026206,549.0,,3,40,/judehunt23/saving-predictions-from-previous-levels-2-ways,Predict Student Performance from Game Play
10824,130442742,115.0,0.6627316468168745,0,2,/zhangyip/xgboost-test,Predict Student Performance from Game Play
10825,134593119,613.0,0.7000763184366169,0,1,/abdotohamy/catboost-mix,Predict Student Performance from Game Play
10826,126723805,620.0,0.6407134540756554,0,0,/ryotaro45123/exp015-notebook,Predict Student Performance from Game Play
10827,126723805,620.0,0.6407134540756554,0,0,/ryotaro45123/exp015-notebook,Predict Student Performance from Game Play
10828,121714840,625.0,,0,3,/javihm77/students-performance-eda-chapu,Predict Student Performance from Game Play
10829,141825026,342.0,,0,2,/ammarahmadqazi/public-lb-vs-private-lb,Predict Student Performance from Game Play
10830,119208456,857.0,,10,58,/mayukh18/lgbm-regressor-ensemble-pipeline,Predict Student Performance from Game Play
10831,133916974,641.0,0.6939789287531595,0,1,/dplg007/psp-catboost-gridseacrhcv,Predict Student Performance from Game Play
10832,148087611,642.0,,7,49,/yutodennou/competition-simple-xgboost-with-gridsearchcv,Predict Student Performance from Game Play
10833,127901807,664.0,0.2145497755479271,0,20,/risakashiwabara/i-didn-t-know-how-to-submit-a-submission,Predict Student Performance from Game Play
10834,137380314,675.0,0.698910840050353,0,2,/dongyk/pspfgp-nn-inference,Predict Student Performance from Game Play
10835,135224658,239.0,,0,0,/adegladius/training-notebook-gbclassifier-0-695-pri-0-693-pub,Predict Student Performance from Game Play
10836,118440399,695.0,,0,3,/nfedorov/predict-train-mean-baseline,Predict Student Performance from Game Play
10837,122862508,70.0,,0,2,/kmitsuhiro/retrieving-text-not-used-in-the-train-data-set,Predict Student Performance from Game Play
10838,154961797,250.0,,0,0,/ducnh279/mistral-7b-chat,Predict Student Performance from Game Play
10839,132262480,800.0,0.6992221844136557,0,0,/tqhuyhq/hcmus-fit-hsp,Predict Student Performance from Game Play
10840,133385064,823.0,0.6914916291256186,0,1,/phamdinhkhanh1988/catboost,Predict Student Performance from Game Play
10841,133385064,823.0,0.6914916291256186,0,1,/phamdinhkhanh1988/catboost,Predict Student Performance from Game Play
10842,136493423,839.0,,0,2,/affanzuhaib/final-submission-in-competition,Predict Student Performance from Game Play
10843,137734787,956.0,,7,10,/kononenko/psp-0-676lb-in-6-seconds-with-linearmodel,Predict Student Performance from Game Play
10844,132264960,870.0,0.6519197252286314,0,1,/nhattruong1009/cat-boost,Predict Student Performance from Game Play
10845,126559637,141.0,,0,0,/liqifeng123/pytorch-using-only-1-column-submission,Predict Student Performance from Game Play
10846,126559637,141.0,,0,0,/liqifeng123/pytorch-using-only-1-column-submission,Predict Student Performance from Game Play
10847,122092911,370.0,,0,2,/narendra/psp-null-model-analysis,Predict Student Performance from Game Play
10848,132849056,730.0,0.6833201269553855,3,7,/natomar1/catboost-0-684-student-performance-from-game-play,Predict Student Performance from Game Play
10849,123261000,908.0,,5,12,/econjt/explore-supplemental-data,Predict Student Performance from Game Play
10850,134613545,748.0,0.6661440905146995,0,0,/muchammadaquila/randomforestmodelonpredictstudentperformance,Predict Student Performance from Game Play
10851,126160367,757.0,,0,1,/kazumasatokaggle/error-code-predict-student-performance,Predict Student Performance from Game Play
10852,125258770,760.0,,0,9,/tyeestudio/zero-rule-baseline-and-f1-score,Predict Student Performance from Game Play
10853,135100412,939.0,0.6898556761018674,0,3,/belalemadhussein/simple-highly-efficient-model,Predict Student Performance from Game Play
10854,129238483,901.0,,12,40,/dungdore1312/session-info-as-sequence-use-lstm-to-predict,Predict Student Performance from Game Play
10855,121257278,910.0,,1,4,/thedark735/fork-of-baseline-preserve-train-proportions,Predict Student Performance from Game Play
10856,121953112,945.0,,0,2,/mdreyadhossainnsu/predict-student-performance-from-game-play-1,Predict Student Performance from Game Play
10857,130186133,1055.0,,0,2,/vinitkp/eda-student-performance-r,Predict Student Performance from Game Play
10858,127924800,1261.0,,0,20,/daniarlert/memory-optimization-walkthrough,Predict Student Performance from Game Play
10859,128703596,1087.0,,0,6,/miltiadesgeneral/tensorflow-decision-forest,Predict Student Performance from Game Play
10860,129567516,1021.0,,0,0,/harrynelson/notebook3014456216,Predict Student Performance from Game Play
10861,127740819,1122.0,0.6796073408892314,0,0,/beshwar/dl-proj,Predict Student Performance from Game Play
10862,128138806,987.0,0.4953050485584908,1,7,/rizkykiky/baseline-logistic-regression-only-group-level,Predict Student Performance from Game Play
10863,130792519,1020.0,0.6742191789064791,0,8,/elleneug/elleneug-students-performance,Predict Student Performance from Game Play
10864,133590599,1101.0,,0,0,/pealik/neural-networks-project,Predict Student Performance from Game Play
10865,137817015,1041.0,,0,0,/eastuk/xgboost-baseline-hgry,Predict Student Performance from Game Play
10866,129100823,1046.0,,0,0,/thedeafone/xgboost-f-scoring,Predict Student Performance from Game Play
10867,132675417,1034.0,0.6597430042832318,0,1,/nataliekalina/student-performance-random-forest-xgboost,Predict Student Performance from Game Play
10868,126458757,1318.0,,0,2,/paulmerica/model-inference,Predict Student Performance from Game Play
10869,130897840,1175.0,0.6726198788778686,0,6,/keisukenakata0316/20230523-game,Predict Student Performance from Game Play
10870,126619062,1765.0,,7,48,/zhangyue325/eda-xgboost-and-lgbm-baseline-ongoing,Predict Student Performance from Game Play
10871,129728903,1072.0,0.6772810968995102,0,0,/khuranar/xgboost-more-features,Predict Student Performance from Game Play
10872,128403611,1208.0,0.6775773410954673,0,2,/robyyy123/lks-smk-mahardhika-batujajar-v1,Predict Student Performance from Game Play
10873,128398813,1210.0,,0,3,/koriiabuhori/lks-smkn-1-uruguay,Predict Student Performance from Game Play
10874,127987322,1211.0,,1,2,/elizabethandreaj/lks-smk-wikrama-bogor,Predict Student Performance from Game Play
10875,132321051,1239.0,0.6682528448473989,0,0,/mecer80/game-xgboost-baseline,Predict Student Performance from Game Play
10876,130477220,1246.0,0.6728230154440047,0,0,/csupples/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10877,127875737,1883.0,,0,0,/ayakaueta/catboostfirst-test,Predict Student Performance from Game Play
10878,121944894,1257.0,,0,2,/zeyulau/predict-student-performance-from-game-play-eda,Predict Student Performance from Game Play
10879,133443548,1260.0,,5,17,/benidictusgalihmp/pspg-xgb-lgb-catboost-default-params-comparison,Predict Student Performance from Game Play
10880,130648813,1388.0,,0,0,/doomba2023/notebook4a3fd4c192,Predict Student Performance from Game Play
10881,132307298,1353.0,0.6070238399359777,0,0,/diegofalconc/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10882,132329326,1354.0,0.6728230154440047,0,0,/jonbio/student-performance-w-tensorflow-decision-7fe1a5,Predict Student Performance from Game Play
10883,129155087,1413.0,,107,308,/gusthema/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10884,126284781,1419.0,0.6724399033303121,0,6,/srddev/student-performance,Predict Student Performance from Game Play
10885,126284781,1419.0,0.6724399033303121,0,6,/srddev/student-performance,Predict Student Performance from Game Play
10886,136185510,1444.0,0.6724399033303121,1,14,/corneliuskristianto/student-performance-with-tf-decision-forests,Predict Student Performance from Game Play
10887,128430823,1491.0,0.6724399033303121,1,5,/izdiharfazrianti/lks-smkn-2-kota-bekasi-izdihar-fazrianti,Predict Student Performance from Game Play
10888,128874003,1512.0,0.6724399033303121,0,3,/cuecacuela/competition-student-performance,Predict Student Performance from Game Play
10889,124472414,1522.0,,1,5,/fabraz/exploratory-data-analisys,Predict Student Performance from Game Play
10890,130001869,1549.0,0.6724399033303121,0,0,/popcornmike/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10891,130001869,1549.0,0.6724399033303121,0,0,/popcornmike/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10892,121765372,1553.0,,0,2,/svaningelgem/predict-student-performance-from-game-play,Predict Student Performance from Game Play
10893,130523105,1566.0,0.6724399033303121,0,6,/manojkumarpentapalli/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10894,130523105,1566.0,0.6724399033303121,0,6,/manojkumarpentapalli/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10895,130523105,1566.0,0.6724399033303121,0,6,/manojkumarpentapalli/student-performance-w-tensorflow-decision-forests,Predict Student Performance from Game Play
10896,132773256,1614.0,0.6724399033303121,0,1,/artemhrachov/notebooke51a9669ce,Predict Student Performance from Game Play
10897,119195319,1616.0,,0,2,/erivanoliveirajr/a-simple-test-to-undestand-kaggle-api,Predict Student Performance from Game Play
10898,129805418,1287.0,0.6708581990919467,0,5,/pjawahar/game-success-prediction,Predict Student Performance from Game Play
10899,129805418,1287.0,0.6718233897265882,0,5,/pjawahar/game-success-prediction,Predict Student Performance from Game Play
10900,129805418,1287.0,0.6721609607782354,0,5,/pjawahar/game-success-prediction,Predict Student Performance from Game Play
10901,126462145,1401.0,,0,4,/maurocoimbrab/teste,Predict Student Performance from Game Play
10902,121184408,1687.0,,3,59,/shashwatraman/gpu-xgb-baseline-using-rapids-cudf-train,Predict Student Performance from Game Play
10903,163144134,1712.0,0.6059631240764343,7,23,/kentaro7/beginner-lgbm,Predict Student Performance from Game Play
10904,128969905,1754.0,0.6593194578884856,0,1,/nautpanda/majority-class,Predict Student Performance from Game Play
10905,134293341,1758.0,0.6593194578884856,4,5,/marcellopelosi1998/marcello-loris-0-659-on-lb-without-training-set,Predict Student Performance from Game Play
10906,130973161,1725.0,,2,13,/chiaenchen/eda-predict-student-performance-from-game-play,Predict Student Performance from Game Play
10907,123238029,1726.0,,5,18,/glipko/reading-time-eda,Predict Student Performance from Game Play
10908,126923167,1734.0,0.6227013544117666,0,1,/trinm110/studentperformance-pass,Predict Student Performance from Game Play
10909,129967948,1797.0,,0,2,/serjhenrique/lstm-data-prep-group-level,Predict Student Performance from Game Play
10910,130513266,1790.0,0.6426259031116809,0,2,/kanishkpatel/understanding-features-with-logistic-regression,Predict Student Performance from Game Play
10911,129452541,1826.0,0.6330799347904692,0,4,/haydenlabrie/predict-student-performance,Predict Student Performance from Game Play
10912,122638511,1854.0,,2,8,/merlinbartel/persistent-correctness-and-heavy-clickers,Predict Student Performance from Game Play
10913,121249753,1943.0,,0,1,/thanasansengjaroen/csc532-tf-keras,Predict Student Performance from Game Play
10914,119657393,1970.0,,5,55,/carnozhao/cpu-catboost-baseline-using-polars-train,Predict Student Performance from Game Play
10915,134297733,2000.0,,0,0,/abienugraha/random-forest-hyperparameter-tuning,Predict Student Performance from Game Play
10916,128093978,1999.0,,0,3,/sethmckeehan/ml-final-project,Predict Student Performance from Game Play
10917,127772188,2013.0,0.4718961818051832,0,2,/masakihigashi/catboostfirst,Predict Student Performance from Game Play
10918,134051730,2036.0,0.4209091794023167,0,0,/chennanli/random-submission-modify-value-assignment,Predict Student Performance from Game Play
10919,129611752,2048.0,0.2145497755479271,0,1,/reikiazizyogautama/project-statistika,Predict Student Performance from Game Play
10920,119544221,23.0,2476155.801905031,0,3,/autumnawrange/unsupervised-tabnet,Regression with a Tabular Paris Housing Price Dataset
10921,118889576,24.0,223952.40474633453,0,12,/francescoliveras/playground-series-s3-e6-eda-modeling-en-es,Regression with a Tabular Paris Housing Price Dataset
10922,119044164,278.0,108756.2074026388,2,13,/mingyuwang1/playground-season3-episode-6,Regression with a Tabular Paris Housing Price Dataset
10923,119419796,28.0,,0,1,/dmtamm/playg-s3-e6-russian,Regression with a Tabular Paris Housing Price Dataset
10924,118890424,469.0,113171.53013296588,9,22,/lyasdemir/best-algorithm-for-prediction-xgboost,Regression with a Tabular Paris Housing Price Dataset
10925,118501111,246.0,130216.5995691496,6,15,/satyaprakashshukl/pycaret-and-eda,Regression with a Tabular Paris Housing Price Dataset
10926,119503126,108.0,84038.00523316182,8,36,/vaidyaprasad84/p3-e6-piecewise-model,Regression with a Tabular Paris Housing Price Dataset
10927,119252484,5.0,,9,13,/mscgeorges/adversarial-validation-proper-validation-set,Regression with a Tabular Paris Housing Price Dataset
10928,118969584,137.0,255004.0420563577,0,9,,Regression with a Tabular Paris Housing Price Dataset
10929,119554290,259.0,84038.00523316182,0,2,/umanglodaya/playground-series-s3e6-xgboost,Regression with a Tabular Paris Housing Price Dataset
10930,119760303,103.0,223798.3272090887,0,1,/omarvivas/lgbm-tpgs-s3e6-v1,Regression with a Tabular Paris Housing Price Dataset
10931,118861003,268.0,,21,37,/pardeep19singh/pss3e6-insightful-eda-and-outliers-handling,Regression with a Tabular Paris Housing Price Dataset
10932,119087980,162.0,143894.74891817785,0,0,/massimot/pgs-s3-e6-back-to-1st-try,Regression with a Tabular Paris Housing Price Dataset
10933,119424754,177.0,,0,8,/mahimchrl/initial-data-exploration,Regression with a Tabular Paris Housing Price Dataset
10934,119252189,200.0,,0,5,/teradiot/simple-xgboost-baseline-optuna,Regression with a Tabular Paris Housing Price Dataset
10935,119787685,43.0,150428.9506570761,0,4,/ambrosm/pss3e6-quickstart-without-machine-learning,Regression with a Tabular Paris Housing Price Dataset
10936,118515735,556.0,224034.5997258579,8,26,/kdmitrie/pgs36-eda-test-of-models-blending,Regression with a Tabular Paris Housing Price Dataset
10937,132024618,416.0,,4,7,/mirabirhossain/playground-s3-e6,Regression with a Tabular Paris Housing Price Dataset
10938,119828229,68.0,121232.96826559244,8,24,/donjoeml/xgbregressor-optuna,Regression with a Tabular Paris Housing Price Dataset
10939,119549411,228.0,,1,3,/vindymessi/s3e6-additional-features-for-xgb,Regression with a Tabular Paris Housing Price Dataset
10940,119548818,476.0,124822.80193601882,17,26,/sujaykapadnis/s3e6-thorough-eda-baseline-tunedmodel,Regression with a Tabular Paris Housing Price Dataset
10941,119799263,9.0,,3,11,/brendanmoore14/9th-place-solution,Regression with a Tabular Paris Housing Price Dataset
10942,119168938,80.0,127439.85238151756,8,24,/utkarshgaikwad1994/playground-s3e6-utkarsh-gaikwad,Regression with a Tabular Paris Housing Price Dataset
10943,119537019,448.0,,2,13,/mtulgac/baseline-model-with-gradientboosting-and-rf,Regression with a Tabular Paris Housing Price Dataset
10944,119875048,502.0,157032.73652849416,2,16,/hwikookchoe/pgs-s3e6-generalized-ensemble-model-gem,Regression with a Tabular Paris Housing Price Dataset
10945,119330790,423.0,232153.8930304491,3,6,/ahsanulislam/house-price-predict-with-tensorflow,Regression with a Tabular Paris Housing Price Dataset
10946,119639819,6.0,,0,4,/iamvaibhav100/pg-s6e3-xgboost,Regression with a Tabular Paris Housing Price Dataset
10947,119735734,537.0,133325.5673253816,0,2,/sarvesh42kesharwani/playground-series-season-3-episode-6,Regression with a Tabular Paris Housing Price Dataset
10948,119493241,78.0,,0,3,/bayesianterrapin/s3e6-simple-baseline-score-using-xgboost,Regression with a Tabular Paris Housing Price Dataset
10949,118830957,493.0,231409.68089213312,2,7,/kaushalkrishna2000/playground-s03e06-notebook,Regression with a Tabular Paris Housing Price Dataset
10950,119852504,484.0,,0,0,/iamnotashutosh/pg-s3-e6-eda-basic-model,Regression with a Tabular Paris Housing Price Dataset
10951,118762550,507.0,,0,5,/ch124uec/playground-s3e6-plotly-eda-and-model-ensembling,Regression with a Tabular Paris Housing Price Dataset
10952,119647243,345.0,141132.98966878728,2,7,/ashtcoder/pg-s3-e6,Regression with a Tabular Paris Housing Price Dataset
10953,120883098,300.0,,12,14,/lusfernandotorres/pss3e6-dealing-with-noisy-data,Regression with a Tabular Paris Housing Price Dataset
10954,119073257,216.0,148593.40296161323,2,7,/qiaoningchen/house-price-prediction,Regression with a Tabular Paris Housing Price Dataset
10955,119759261,393.0,169547.2649004442,1,8,/mnokno/paris-housing-price-prediction-using-xgboost,Regression with a Tabular Paris Housing Price Dataset
10956,119773458,404.0,149622.8830126833,0,0,/abhishek123maurya/ps-s2e6,Regression with a Tabular Paris Housing Price Dataset
10957,119614252,189.0,,13,29,/vivek153/with-randomforestregressor,Regression with a Tabular Paris Housing Price Dataset
10958,119128626,341.0,,2,9,/anurag629/episode-6-choose-best-model,Regression with a Tabular Paris Housing Price Dataset
10959,118820202,88.0,217818.9258395028,0,0,/tylerchi/playground-season-3-episode-6-house-pred,Regression with a Tabular Paris Housing Price Dataset
10960,118982471,142.0,,0,1,/arosielle/playground-s306,Regression with a Tabular Paris Housing Price Dataset
10961,119793740,474.0,175835.41455519537,0,8,/cv13j0/gbdt-using-xgboost,Regression with a Tabular Paris Housing Price Dataset
10962,119716311,208.0,,0,4,/sonukumar2k19it124/simple-code,Regression with a Tabular Paris Housing Price Dataset
10963,118588327,211.0,209928.48407210867,0,15,/mpwolke/how-i-found-mon-pied-terre-ep-6,Regression with a Tabular Paris Housing Price Dataset
10964,119563433,276.0,,2,7,/shivijaiswal/playground-6,Regression with a Tabular Paris Housing Price Dataset
10965,119682946,444.0,,0,7,/matteosilla/s3e6-eda-ml,Regression with a Tabular Paris Housing Price Dataset
10966,119291896,4.0,,7,16,/icfoer/ps3e6-validation-scheme,Regression with a Tabular Paris Housing Price Dataset
10967,119712938,195.0,158401.35686549832,0,4,/sergeyyakovlev1312/playground-s3e6,Regression with a Tabular Paris Housing Price Dataset
10968,118592537,348.0,159039.46050355883,0,0,/mohib94/playground-series-s3e6,Regression with a Tabular Paris Housing Price Dataset
10969,124104014,73.0,,0,0,/manaidu/playground-series-s3e6,Regression with a Tabular Paris Housing Price Dataset
10970,118811217,376.0,172303.29411120567,0,3,/matthieuqcc/pg-series-s3-e6-paris-housing-price-regression,Regression with a Tabular Paris Housing Price Dataset
10971,119636433,172.0,,0,2,/nhopet/pss3e6-datavisualization-and-outliearstreatment,Regression with a Tabular Paris Housing Price Dataset
10972,119583079,518.0,163535.4878773232,7,10,/klyushnik/episode-6,Regression with a Tabular Paris Housing Price Dataset
10973,118487064,358.0,225142.8175790799,0,5,/gauravduttakiit/pss3e6-flaml-rmse,Regression with a Tabular Paris Housing Price Dataset
10974,119118735,446.0,,0,2,/vicsuperman/ps3e6-baseline-automl,Regression with a Tabular Paris Housing Price Dataset
10975,118678325,14.0,180697.725774136,2,11,/satoshiss/paris-housing-price-predictions-s3e6,Regression with a Tabular Paris Housing Price Dataset
10976,118829279,134.0,,0,1,/maheswarareddyp/pgs3e6-mahesh-parishouseprediction-1,Regression with a Tabular Paris Housing Price Dataset
10977,118792112,285.0,223463.94390657303,0,7,/docxian/ps-s3-e6-house-price-regression,Regression with a Tabular Paris Housing Price Dataset
10978,118664749,122.0,276551.10056791845,0,8,/azazali/playground-series-episode-6-ensemble-learning,Regression with a Tabular Paris Housing Price Dataset
10979,119010567,353.0,,20,53,/manthanx/ps3e6-xgboost-feature-selection-ensemble,Regression with a Tabular Paris Housing Price Dataset
10980,119772785,34.0,219902.22436377843,0,0,/olliekemp/paris-house-prices,Regression with a Tabular Paris Housing Price Dataset
10981,119634472,500.0,191479.2696985477,1,4,/muhammadumairab/eda-prediction,Regression with a Tabular Paris Housing Price Dataset
10982,119777436,503.0,173808.3500801166,0,2,/jpkochar/paris-housing-price,Regression with a Tabular Paris Housing Price Dataset
10983,119461895,70.0,185809.4494432896,0,3,/amrelsayeh/pgs-s3e6-house-prediction1-xgboost,Regression with a Tabular Paris Housing Price Dataset
10984,120725061,182.0,,1,1,/elsayovita/paris-housing-prediction-with-random-forest,Regression with a Tabular Paris Housing Price Dataset
10985,119366027,529.0,1174399.7074962617,0,1,/hiroshikurokawa/automl-gbr-catb-xgb-ensembled,Regression with a Tabular Paris Housing Price Dataset
10986,119366027,529.0,239816.94599003447,0,1,/hiroshikurokawa/automl-gbr-catb-xgb-ensembled,Regression with a Tabular Paris Housing Price Dataset
10987,119366027,529.0,1165212.832112659,0,1,/hiroshikurokawa/automl-gbr-catb-xgb-ensembled,Regression with a Tabular Paris Housing Price Dataset
10988,118443392,90.0,208403.62999698124,3,14,/khawajaabaidullah/ps3e6-ensembling-xgboost-catboost-lightgbm,Regression with a Tabular Paris Housing Price Dataset
10989,118618179,519.0,179652.45210541735,0,3,/coyleliam/pandas-profiling-deepchecks-and-simple-model,Regression with a Tabular Paris Housing Price Dataset
10990,119780059,304.0,,0,4,/rupeshmahanty/playground-series-season-3-episode-6,Regression with a Tabular Paris Housing Price Dataset
10991,119288394,119.0,1165981.1829432624,0,1,/datascientistsohail/observing-outliers-building-model-rfr,Regression with a Tabular Paris Housing Price Dataset
10992,118466282,505.0,2055629.2245068608,0,5,/tracyporter/play-3-6-paris-lin-reg,Regression with a Tabular Paris Housing Price Dataset
10993,119157234,106.0,,2,6,/tetsutani/playgrounds3e6-lightgbm-randomforest-stacking,Regression with a Tabular Paris Housing Price Dataset
10994,119199635,461.0,,0,0,/agunbiadeopeyemi/notebookc6cd88d030,Regression with a Tabular Paris Housing Price Dataset
10995,120425019,145.0,,17,44,/jonbown/cluster-feature-engineering-tps3e6,Regression with a Tabular Paris Housing Price Dataset
10996,119201998,210.0,335668.76771798497,0,0,/yarribryn/playground-series-s3e6-paris-housing-prices,Regression with a Tabular Paris Housing Price Dataset
10997,120915622,84.0,,18,37,/gopimali/eda-pycaret-bayesian,Regression with a Tabular Paris Housing Price Dataset
10998,118601134,139.0,,1,6,/craigmthomas/play-s3e6-eda-models,Regression with a Tabular Paris Housing Price Dataset
10999,119746547,91.0,213184.0402085399,8,14,/kimmik123/starter-notebook-ensemble-feature-eng,Regression with a Tabular Paris Housing Price Dataset
11000,118528154,380.0,222867.2552128645,0,6,/wasshoiwasshoi/pss3e6-eda-and-lightgbm-baseline,Regression with a Tabular Paris Housing Price Dataset
11001,119408416,144.0,,0,0,/umitemreilhan/housing-price,Regression with a Tabular Paris Housing Price Dataset
11002,119386706,558.0,207432.8778815002,0,1,/mukaseevru/ps-s3e6-lama-lightautoml,Regression with a Tabular Paris Housing Price Dataset
11003,120003773,543.0,,0,22,/meeratif/play-s3e6-eda-model,Regression with a Tabular Paris Housing Price Dataset
11004,119229165,190.0,224328.26411439537,0,12,/amarloni/pgs3e6,Regression with a Tabular Paris Housing Price Dataset
11005,118579586,430.0,,0,5,/stpeteishii/pss3-ep6-visualize-importance,Regression with a Tabular Paris Housing Price Dataset
11006,119900756,595.0,,0,2,/matejper/predicting-paris-housing-prices,Regression with a Tabular Paris Housing Price Dataset
11007,118927773,580.0,224076.3616847469,0,4,/cipollinonewbie/linear-regression-of-house-prices-in-paris,Regression with a Tabular Paris Housing Price Dataset
11008,118659543,619.0,361429.5364798058,2,8,/fuad0857/playground-s3-e6-with-tensorflow,Regression with a Tabular Paris Housing Price Dataset
11009,127875359,566.0,,4,27,/validmodel/s03e05-eda-featureengg-tuning-model,Regression with a Tabular Paris Housing Price Dataset
11010,119353317,629.0,,0,5,/barbagrande007/bbg007-s3e6,Regression with a Tabular Paris Housing Price Dataset
11011,119793096,650.0,,0,2,/radhwanadem/exploring-paris-housing-prices-an-eda-and-model-b,Regression with a Tabular Paris Housing Price Dataset
11012,118907540,656.0,,0,3,/yeemeitsang/paris-housing-sklearn,Regression with a Tabular Paris Housing Price Dataset
11013,119089812,665.0,,0,4,/yadusarath/baseline-random-forest-regression,Regression with a Tabular Paris Housing Price Dataset
11014,119774099,667.0,1503344.3253287626,0,4,/chongjiaxu/paris,Regression with a Tabular Paris Housing Price Dataset
11015,126427715,669.0,,2,6,/ahana09/ps-s3e6,Regression with a Tabular Paris Housing Price Dataset
11016,119695834,678.0,2031275.655555048,0,0,/samra22/parishousingpriceprediction,Regression with a Tabular Paris Housing Price Dataset
11017,119379374,698.0,5531466.014974057,0,0,/rubanzasilva/fastai-solution-for-ps-s03e06,Regression with a Tabular Paris Housing Price Dataset
11018,119379374,698.0,5531466.014974057,0,0,/rubanzasilva/fastai-solution-for-ps-s03e06,Regression with a Tabular Paris Housing Price Dataset
11019,120547715,4.0,0.9289891218179388,3,23,/ryanbarretto/4th-place-solution,Binary Classification with a Tabular Reservation Cancellation Dataset
11020,119108812,14.0,0.8386827793635461,4,15,/satyaprakashshukl/xgboost-pss3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11021,119304681,15.0,,0,5,/martynovandrey/ps-3-7-autokeras,Binary Classification with a Tabular Reservation Cancellation Dataset
11022,119646836,17.0,0.9129113952312896,0,7,/omarvivas/cb-tpgs-s3e7-v1,Binary Classification with a Tabular Reservation Cancellation Dataset
11023,120228274,159.0,0.8998327747501574,1,6,/dillanwilliams/playground-s3-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11024,120228274,159.0,0.913588473899115,1,6,/dillanwilliams/playground-s3-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11025,120228274,159.0,0.7973271129252623,1,6,/dillanwilliams/playground-s3-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11026,119206452,37.0,,1,21,/mattop/playground-series-s3-e7-eda,Binary Classification with a Tabular Reservation Cancellation Dataset
11027,119853699,22.0,0.8941950255565589,2,4,/haruomiyoshikawa/s3e7-tabtransformer-with-kfold,Binary Classification with a Tabular Reservation Cancellation Dataset
11028,119924406,43.0,,1,10,/griffenthoma/simple-gradient-boosted-trees-model,Binary Classification with a Tabular Reservation Cancellation Dataset
11029,120547230,47.0,,3,6,/magnussesodia/ps-s3e7-feature-eng-data-leakage-47th,Binary Classification with a Tabular Reservation Cancellation Dataset
11030,120247637,67.0,0.908121473884858,3,14,/pardeep19singh/pss3e7-insightful-eda-baseline-using-pycaret,Binary Classification with a Tabular Reservation Cancellation Dataset
11031,149275010,68.0,,4,34,/ashishkumarak/reservation-cancellation-prediction-lgbm-tf-rf,Binary Classification with a Tabular Reservation Cancellation Dataset
11032,119686337,85.0,0.9263159119404988,9,39,/icfoer/ps6e7-xgboost-leak,Binary Classification with a Tabular Reservation Cancellation Dataset
11033,120538957,39.0,,2,4,/pasqualemar/basic-ensemble-leakage-exploitation,Binary Classification with a Tabular Reservation Cancellation Dataset
11034,120427214,76.0,0.9117658491419232,0,7,/eamonntweedy/playgrounds3e7-lgbm-xgb-cb,Binary Classification with a Tabular Reservation Cancellation Dataset
11035,120118899,81.0,0.9237184261969456,1,19,/grantgonnerman/ps-s3-e7-model-comparisons-ensembles,Binary Classification with a Tabular Reservation Cancellation Dataset
11036,120118899,81.0,0.9237184261969456,1,19,/grantgonnerman/ps-s3-e7-model-comparisons-ensembles,Binary Classification with a Tabular Reservation Cancellation Dataset
11037,119323468,92.0,0.8891558063732552,1,7,/pradeepchandrasuyal/s3-e7-stacking-with-xgboost,Binary Classification with a Tabular Reservation Cancellation Dataset
11038,120362114,106.0,0.9170565181801136,0,1,/muhammadumairab/playground-s3e-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11039,119705827,112.0,0.9139116801046742,2,11,/rkoirala129/xgboost-classification-baseline,Binary Classification with a Tabular Reservation Cancellation Dataset
11040,120421725,135.0,,6,25,/inaciobr/ps-s03e07-votingclassifier-xgb-lgbm,Binary Classification with a Tabular Reservation Cancellation Dataset
11041,132674298,121.0,,12,79,/kimtaehun/simple-eda-with-lgmb-baseline,Binary Classification with a Tabular Reservation Cancellation Dataset
11042,122363203,153.0,,1,16,/alpayabbaszade/combined-feature-selection-analysis,Binary Classification with a Tabular Reservation Cancellation Dataset
11043,120498591,188.0,0.910744044088393,4,16,/samuraikaggle/samurai-s3e7ens-cb-xb-lb,Binary Classification with a Tabular Reservation Cancellation Dataset
11044,120080312,147.0,0.9065345623508214,0,9,/amrelsayeh/pgs-s3e7-ensemble-but-not-the-best,Binary Classification with a Tabular Reservation Cancellation Dataset
11045,119133515,124.0,0.9120531435468646,3,9,/khawajaabaidullah/ps3e7-simple-but-strong-ensemble,Binary Classification with a Tabular Reservation Cancellation Dataset
11046,119237346,126.0,,7,30,/ahmadalijamali/data-analysis-of-playground-series-s3-e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11047,119775804,156.0,,0,1,/sahilsg/seaborn-reservation-s03-e07,Binary Classification with a Tabular Reservation Cancellation Dataset
11048,120435577,151.0,0.813049823790075,0,3,/macklinshanahan/notebook-ep7,Binary Classification with a Tabular Reservation Cancellation Dataset
11049,120135350,173.0,0.8250155147048736,0,8,/kimmik123/starter-notebook-ps-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11050,119301714,178.0,0.907201149930826,0,8,/satoshiss/cancellation-prediction-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11051,121628638,231.0,,0,1,/alfiyafakhrutdinova/strshufflesplit-kfold-strkfold-0-9099,Binary Classification with a Tabular Reservation Cancellation Dataset
11052,119706310,255.0,0.907636933578771,0,4,/ahsanulislam/ps-s3-e7-xgb-classifier,Binary Classification with a Tabular Reservation Cancellation Dataset
11053,119898077,227.0,0.9096206906848016,0,1,/datascientistsohail/optuna-lgbmclassifier-se03-ep07,Binary Classification with a Tabular Reservation Cancellation Dataset
11054,120414591,253.0,0.9094181319891828,0,2,/abraamadamidis/lightgbm-optuna-first-try,Binary Classification with a Tabular Reservation Cancellation Dataset
11055,119884558,221.0,,10,31,/manthanx/ps3e7-indepth-eda-xgboost-optuna,Binary Classification with a Tabular Reservation Cancellation Dataset
11056,119978633,194.0,,0,10,/abdoulayebalde/pse7-eda-catboost-baseline-with-score-of-0-9,Binary Classification with a Tabular Reservation Cancellation Dataset
11057,119830901,262.0,,5,13,/demko1/s3e7-data-vizualization-and-a-bit-feature-engineer,Binary Classification with a Tabular Reservation Cancellation Dataset
11058,119203433,204.0,0.9063820380740408,0,5,/oldjerry/model-integration-under-bayesian-optimization,Binary Classification with a Tabular Reservation Cancellation Dataset
11059,119415391,230.0,,0,6,/ryangreiner/s3-e7-initial-eda,Binary Classification with a Tabular Reservation Cancellation Dataset
11060,120287860,198.0,0.9089772372984536,0,4,/adivireza/playground-series-season-3-episode-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11061,119187991,195.0,,0,9,/daltondencklau/ps3-ep7-eda-baseline-models,Binary Classification with a Tabular Reservation Cancellation Dataset
11062,119490787,209.0,,2,10,/jaredsavage/ps-s3e07-testing-multiple-models-with-tidymodels,Binary Classification with a Tabular Reservation Cancellation Dataset
11063,119743835,212.0,,23,45,/abhi011097/predict-reservation-eda-lazypredict-lgbm-xgb,Binary Classification with a Tabular Reservation Cancellation Dataset
11064,119408114,233.0,0.9083752102588852,0,4,/mukaseevru/ps-s3e7-lama-lightautoml,Binary Classification with a Tabular Reservation Cancellation Dataset
11065,119376812,243.0,,0,8,/qiaoningchen/reservation-cancellation-prediction,Binary Classification with a Tabular Reservation Cancellation Dataset
11066,120498854,279.0,0.9082830769876374,2,2,/boyochan/ps-s3-e7-eda-lightgbm,Binary Classification with a Tabular Reservation Cancellation Dataset
11067,120079705,254.0,0.9078961172483976,0,7,/mnokno/reservation-cancellation-prediction-using-xgboost,Binary Classification with a Tabular Reservation Cancellation Dataset
11068,119412423,260.0,,2,10,/mckayla/ps-s3-e7-eda,Binary Classification with a Tabular Reservation Cancellation Dataset
11069,119794023,265.0,0.9079754729126838,5,15,/hwikookchoe/pgs-s3e7-eda-and-pycaret-practice,Binary Classification with a Tabular Reservation Cancellation Dataset
11070,119848435,244.0,,9,16,/hiroshikurokawa/p3s7-lgb-catb-xgb-ensemble,Binary Classification with a Tabular Reservation Cancellation Dataset
11071,120213928,276.0,0.907523011125126,0,6,/charunumesh/playground-series-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11072,120012368,241.0,0.9044239706830586,0,0,/yarribryn/playground-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11073,119495653,263.0,,0,4,/gauravduttakiit/pss3e7-smote-lazypredict,Binary Classification with a Tabular Reservation Cancellation Dataset
11074,119423608,219.0,0.906657630881028,0,10,/akioonodera/ps-3-07-lgbm-bin,Binary Classification with a Tabular Reservation Cancellation Dataset
11075,119677330,321.0,0.9061816313964364,1,15,/cv13j0/auto-ml-model-using-pycaret,Binary Classification with a Tabular Reservation Cancellation Dataset
11076,120356280,285.0,0.9062650220945,1,9,/manavd22/boosting-ensemble-bayesian-tuning-eda,Binary Classification with a Tabular Reservation Cancellation Dataset
11077,120055385,288.0,,2,16,/timothylincoln2/s3-e7-ps-omar-tim,Binary Classification with a Tabular Reservation Cancellation Dataset
11078,119251303,289.0,0.9059953473370526,5,13,/utkarshgaikwad1994/ps3e7-utkarsh-gaikwad,Binary Classification with a Tabular Reservation Cancellation Dataset
11079,119128083,296.0,0.8453954615554087,1,3,/tracyporter/play-3-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11080,119954063,325.0,0.904160550227966,2,8,/ashtcoder/pg-s3-e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11081,120046356,365.0,0.9029680632456576,0,1,/azazali/playground-series-s3e7-automl,Binary Classification with a Tabular Reservation Cancellation Dataset
11082,119321829,353.0,,1,5,/thedwong/playground-s3-e7-very-basic-eda-modeling,Binary Classification with a Tabular Reservation Cancellation Dataset
11083,119846034,335.0,,0,8,/moradrawashdeh/playground-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11084,119410268,318.0,0.9000320381681916,1,11,/ch124uec/plotly-eda-feature-engineering-xgb-tuning,Binary Classification with a Tabular Reservation Cancellation Dataset
11085,120191216,361.0,0.1406651107576421,3,14,/klyushnik/episode-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11086,119097605,356.0,,0,5,/masayakawamata/s3e7-trying-pca,Binary Classification with a Tabular Reservation Cancellation Dataset
11087,120513664,376.0,,0,1,/rebeccapringle/playground-series-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11088,119535579,386.0,,2,11,/refat094/playground-series-s3e7-stack,Binary Classification with a Tabular Reservation Cancellation Dataset
11089,119862118,390.0,0.8916166389728848,1,9,/sergeyyakovlev1312/playground-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11090,120219364,395.0,,11,44,/hikmatullahmohammadi/reservation-cancellation-simple-dnn-tf-keras,Binary Classification with a Tabular Reservation Cancellation Dataset
11091,119806867,396.0,0.8881981583567836,5,12,/chongjiaxu/reservation-lgbm-0-88883,Binary Classification with a Tabular Reservation Cancellation Dataset
11092,120513072,408.0,0.8881981583567836,0,0,/rohitkumar7690/rohitkumar7690,Binary Classification with a Tabular Reservation Cancellation Dataset
11093,120461226,403.0,,0,7,/davidhguerrero/230219-pss3-e7-reservation-cancellation-dataset,Binary Classification with a Tabular Reservation Cancellation Dataset
11094,120248996,409.0,0.8864189774632604,4,10,/aonzahaha/ps-ss3-ep7-keras-randomsearchcv-crossvalidation,Binary Classification with a Tabular Reservation Cancellation Dataset
11095,120248996,409.0,0.8864189774632604,4,10,/aonzahaha/ps-ss3-ep7-keras-randomsearchcv-crossvalidation,Binary Classification with a Tabular Reservation Cancellation Dataset
11096,120539551,411.0,0.8855266297434176,1,13,/kattat/reservation-cancellation-classification-with-keras,Binary Classification with a Tabular Reservation Cancellation Dataset
11097,119665880,413.0,,4,6,/khaledgamal1/ep7-baseline,Binary Classification with a Tabular Reservation Cancellation Dataset
11098,119813924,414.0,,0,1,/sapnajha0304/s3-ep-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11099,122413371,427.0,0.8212007937718446,0,9,/lizhecheng/s3e7-booking-status-prediction,Binary Classification with a Tabular Reservation Cancellation Dataset
11100,119712374,435.0,,6,18,/nancysamuel/pss-3-ep-7-basic-xgb,Binary Classification with a Tabular Reservation Cancellation Dataset
11101,119202460,438.0,0.8526957791663674,0,3,/tylerjthomas9/ps-s3-e7-ensemble-model-polars,Binary Classification with a Tabular Reservation Cancellation Dataset
11102,120755431,456.0,,0,1,/moohamedelsayed/reservation-cancellation-prediction,Binary Classification with a Tabular Reservation Cancellation Dataset
11103,119455031,454.0,,0,10,/amarloni/pgs3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11104,119775020,467.0,0.829996360399533,5,13,/shyamgupta196/feature-selection-xgb-baseline-ps-e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11105,120551034,461.0,0.8256845233051446,4,6,/barbagrande007/bbg007-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11106,120628956,478.0,,0,0,/elsayovita/booking-cancellation-prediction-xgboost,Binary Classification with a Tabular Reservation Cancellation Dataset
11107,119968874,485.0,,0,3,/jth3000/eda-and-basic-models-no-tuning-or-data-leak,Binary Classification with a Tabular Reservation Cancellation Dataset
11108,119252575,528.0,,1,5,/stpeteishii/pss3-ep7-visualize-importance,Binary Classification with a Tabular Reservation Cancellation Dataset
11109,119323640,496.0,,0,15,/altafk/playground-serires-eda-with-paycaret,Binary Classification with a Tabular Reservation Cancellation Dataset
11110,119837147,497.0,,0,1,/murtazaaamir/play-ground-series-with,Binary Classification with a Tabular Reservation Cancellation Dataset
11111,119967293,558.0,0.8198791184581006,0,0,/matejper/classification-reservation-cancellation,Binary Classification with a Tabular Reservation Cancellation Dataset
11112,119949522,526.0,0.8007633476899835,0,2,/reeturajharsh/ps-with-xgboost-and-hyperparameter-tuning,Binary Classification with a Tabular Reservation Cancellation Dataset
11113,120217835,495.0,,0,1,/manaidu/playground-series-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11114,119768082,548.0,0.8172073208424828,0,0,/pohzixiang/zx-playground-series-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11115,119839933,569.0,0.7696945963634662,0,0,/arnaumarsal/my-first-ml-model,Binary Classification with a Tabular Reservation Cancellation Dataset
11116,119574644,537.0,0.8163188064047284,0,1,/takahironamatame/playground-series-season-3-episode-7,Binary Classification with a Tabular Reservation Cancellation Dataset
11117,119988189,555.0,,0,0,/kavishchaudhary1003/playground-s3-e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11118,120103511,557.0,0.810552541385324,2,8,/shubhamsingh57/playground-series-multiple-model,Binary Classification with a Tabular Reservation Cancellation Dataset
11119,120582650,580.0,,1,2,/ssankarr/booking-status-prediction-with-stacking,Binary Classification with a Tabular Reservation Cancellation Dataset
11120,119827452,586.0,0.8023311600641408,0,0,/fuad0857/playground-s3-e7-with-tensorflow,Binary Classification with a Tabular Reservation Cancellation Dataset
11121,119777963,592.0,,0,24,/meeratif/exploring-ps3e7-eda-lgbmclassifier,Binary Classification with a Tabular Reservation Cancellation Dataset
11122,119489894,624.0,,0,9,/panini92/ps-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11123,120416598,626.0,,0,1,/deebahaider/deebah-playground-series-3x07,Binary Classification with a Tabular Reservation Cancellation Dataset
11124,119823486,627.0,,1,14,/riyaelizashaju/reservation-turnover-catboost-algo,Binary Classification with a Tabular Reservation Cancellation Dataset
11125,133566849,659.0,,0,4,/atrijtalgery/ps3-7-adaboost-pipeline-overfit-check,Binary Classification with a Tabular Reservation Cancellation Dataset
11126,120545515,664.0,,2,15,/jonbown/pyspark-ml-pipeline-s3e7,Binary Classification with a Tabular Reservation Cancellation Dataset
11127,120248369,666.0,,0,3,/taruchit/reservation-cancelation-analysis-and-prediction,Binary Classification with a Tabular Reservation Cancellation Dataset
11128,130821161,3.0,0.6493517834741391,1,3,/sai11fkaneko/3rd-place-solution,Stable Diffusion - Image to Prompts
11129,122778734,4.0,-1.0,0,7,/gerwynng/quick-submit-trick,Stable Diffusion - Image to Prompts
11130,129713704,6.0,0.6455730635618023,5,4,/sokazaki/sdip-6th-place-submission,Stable Diffusion - Image to Prompts
11131,129731389,7.0,,0,5,/rturley/custom-prompt-generator-for-image-generation,Stable Diffusion - Image to Prompts
11132,122151276,20.0,0.5071706495589468,0,10,/dolphin15/stable-diffusion-vit-baseline-inference-tta,Stable Diffusion - Image to Prompts
11133,122413733,23.0,,0,2,/h1astro/diffusiondb-data-cleansing,Stable Diffusion - Image to Prompts
11134,120610661,24.0,,1,16,/motono0223/sdip-example-exec-stable-diffusion-2,Stable Diffusion - Image to Prompts
11135,122805248,26.0,,1,45,/vlomme/coca-clip-and-blip-clip,Stable Diffusion - Image to Prompts
11136,135887240,37.0,,0,0,/holmes0610/stable-diffusion-inference,Stable Diffusion - Image to Prompts
11137,127352919,43.0,,0,1,/minar44/diffusiondb-2m-resize224,Stable Diffusion - Image to Prompts
11138,120493990,51.0,0.4515070528549545,4,21,/ksork6s4/sdip-blip2-baseline-public,Stable Diffusion - Image to Prompts
11139,120719081,58.0,,1,8,/wuwenmin/failed-to-reproduce-kaggle-dataset,Stable Diffusion - Image to Prompts
11140,127390577,64.0,,1,1,/wanggaoyang/stable-diffusion-vit-baseline-train,Stable Diffusion - Image to Prompts
11141,127992319,71.0,,0,0,/tangmengcheng/dataset-to-local-zip1,Stable Diffusion - Image to Prompts
11142,123701795,73.0,,0,0,/siyuchenrun/diffusiondb-data-cleansing,Stable Diffusion - Image to Prompts
11143,126515978,68.0,,0,0,/ayaanjang/stable-diffusion-vit-baseline-train,Stable Diffusion - Image to Prompts
11144,128959117,86.0,,4,36,/tomokihirose/use-vector-search-for-diffusion-db-cleansing,Stable Diffusion - Image to Prompts
11145,119151081,90.0,,1,10,/leolu1998/how-to-calculate-your-cv,Stable Diffusion - Image to Prompts
11146,122451054,98.0,0.5061328219837741,7,2,/pe4eniks/inference-vit-hypernet,Stable Diffusion - Image to Prompts
11147,127387327,111.0,0.5554634776599441,10,5,/lupin11/lb-0-55543-clipinterrogator-ofa-vit,Stable Diffusion - Image to Prompts
11148,127178376,120.0,0.5187580668701998,2,2,/huangjingstark/stable-prompt-inference-swin-large,Stable Diffusion - Image to Prompts
11149,119299046,121.0,,2,30,/yawata/post-processing-adding-modifiers,Stable Diffusion - Image to Prompts
11150,125044766,117.0,,0,0,/qiexifan/huggingface-accelerate-learn-beyond-laion2b-brute,Stable Diffusion - Image to Prompts
11151,126914373,127.0,,0,1,/fanchuan/stable-diffusion-vit-baseline-train,Stable Diffusion - Image to Prompts
11152,122089716,132.0,0.5087704155270711,0,1,/neos960518/clip-interrogator-ofa,Stable Diffusion - Image to Prompts
11153,123222175,138.0,,0,2,/tanreinama/direct-backward-to-prompt-tokens,Stable Diffusion - Image to Prompts
11154,127635200,139.0,0.5681595780903582,8,21,/lhllmlt/clipinterrogator-ofa-vit-lb0-568,Stable Diffusion - Image to Prompts
11155,119180370,140.0,,2,6,/safavieh/sdip-generating-training-data,Stable Diffusion - Image to Prompts
11156,127292366,149.0,0.3821374870914472,0,3,/iambestfeeder/test-7-3-clipinterrogator-vitlarge,Stable Diffusion - Image to Prompts
11157,119285844,182.0,,0,3,/narek1110/train-starter-code-for-blip-no-validation,Stable Diffusion - Image to Prompts
11158,122845560,186.0,0.1239625876428008,2,5,/mewmlelswm/sentencetransformer-inference,Stable Diffusion - Image to Prompts
11159,125097212,189.0,0.5422604231358603,4,12,/juntaojiang/lb-0-54226-clipinterrogator-vitlarge,Stable Diffusion - Image to Prompts
11160,119673462,214.0,,3,27,/leonidkulyk/img2prompt-eda-problem-investigation,Stable Diffusion - Image to Prompts
11161,125960016,202.0,0.5406079005897132,6,36,/maverickss26/lb-0-55161-clipinterrogator-ofa-vit,Stable Diffusion - Image to Prompts
11162,123956220,266.0,,2,20,/xiaozhouwang/hard-coded-prompt-generator,Stable Diffusion - Image to Prompts
11163,124052853,241.0,,0,0,/josephwei/clip-with-vit,Stable Diffusion - Image to Prompts
11164,128639170,233.0,,0,1,/mrsixalex/vit-gpt2,Stable Diffusion - Image to Prompts
11165,122214786,246.0,,0,1,/millerrfu/stable-diffusion-vit-baseline-train,Stable Diffusion - Image to Prompts
11166,123933994,260.0,,3,14,/sapeksh/ensemble-clip-ofa-vit,Stable Diffusion - Image to Prompts
11167,123295722,318.0,,0,12,/seshurajup/stable-diffusion-clusters-lets-probe-the-lb,Stable Diffusion - Image to Prompts
11168,128547012,371.0,,0,0,/mlgzackfly/stable-diffusion-embedding-all-images-save-db-csv,Stable Diffusion - Image to Prompts
11169,128957135,393.0,,0,0,/dlobatog/sd-image-to-text,Stable Diffusion - Image to Prompts
11170,126780047,428.0,0.5406856723217847,0,33,/parikshitsharma2001/lb-0-55161-clipinterrogator-ofa-vit,Stable Diffusion - Image to Prompts
11171,125254570,443.0,,2,8,/tyeestudio/random-baseline-and-cosine-similarity-score,Stable Diffusion - Image to Prompts
11172,119273733,471.0,0.4005793007371235,3,50,/bibanh/blip-0-40057-baseline-blip-large-pretrained,Stable Diffusion - Image to Prompts
11173,128418669,482.0,0.5730052021467845,0,0,/haidermasood/clip-knnregression-vit,Stable Diffusion - Image to Prompts
11174,127894336,515.0,,0,1,/huangjingsmu/train,Stable Diffusion - Image to Prompts
11175,125936862,514.0,,0,0,/arli2016/kandinsky-remix,Stable Diffusion - Image to Prompts
11176,127064566,565.0,0.5379530423899692,0,3,/greenfruit2/ensemble-clip-ofa-vit-copy,Stable Diffusion - Image to Prompts
11177,123320727,599.0,,1,1,/mengmouren/stable-diffusion-diffusiondb-to-vector,Stable Diffusion - Image to Prompts
11178,123405032,611.0,,2,2,/ksmcg90/diffusiondb-language-filtering,Stable Diffusion - Image to Prompts
11179,124505065,606.0,,0,0,/hchen549/stable-diffusion-vit-baseline-train-3c5a34,Stable Diffusion - Image to Prompts
11180,122433271,610.0,,2,12,/chandanverma/make-inference-1-6x-faster-with-torch-tensorrt,Stable Diffusion - Image to Prompts
11181,124575498,630.0,0.4583673703885781,0,0,/lenferdetroud/stable-diffusion-image-to-prompts-ver1,Stable Diffusion - Image to Prompts
11182,124422059,622.0,,0,5,/jesherjoshua/only-clip-interrogator,Stable Diffusion - Image to Prompts
11183,127259296,688.0,-0.000624817035698,0,1,/sdu2014brz/randommethod0426,Stable Diffusion - Image to Prompts
11184,121000340,743.0,0.4575818971024263,0,10,/saniyatlamim007/team-x-squad-i2p,Stable Diffusion - Image to Prompts
11185,125116201,706.0,0.5081965886791638,0,0,/bolmas/modified-by-vit-baseline-train,Stable Diffusion - Image to Prompts
11186,123210859,707.0,,2,9,/nayakroshan/stable-diffusion-swin-transformer,Stable Diffusion - Image to Prompts
11187,124879667,751.0,,0,5,/lonelvino/ensemble-clip-ofa-vit-larger,Stable Diffusion - Image to Prompts
11188,122400752,775.0,0.2817876971216273,0,3,/opanichev/baseline-hacking-universal-prompt,Stable Diffusion - Image to Prompts
11189,122232476,785.0,0.5167782662802841,0,37,/finlay/stable-diffusion-vit-baseline-inference-with-tta,Stable Diffusion - Image to Prompts
11190,120572640,816.0,,0,1,/pavan9065/explore-stable-diffusion-image-to-prompts,Stable Diffusion - Image to Prompts
11191,120424189,882.0,,0,5,/skt7shivam/cos-sim-of-corresponding-embeddings-from-two-lists,Stable Diffusion - Image to Prompts
11192,127592784,916.0,,6,16,/ipythonx/kerascv-stable-diffusion-on-gpu-s-tpu-vm,Stable Diffusion - Image to Prompts
11193,127796469,931.0,,0,0,/yitaoyu/stable-diffusion-vit-baseline-train,Stable Diffusion - Image to Prompts
11194,122404254,992.0,,0,19,/alejopaullier/detecting-noise-in-text-encoders,Stable Diffusion - Image to Prompts
11195,119903280,999.0,,2,12,/umongsain/base-line-image-captioning-model-lb-0-30590,Stable Diffusion - Image to Prompts
11196,120555742,1038.0,0.4575730264876819,0,29,/masterofdeception/image2prompts-eda,Stable Diffusion - Image to Prompts
11197,120270639,1045.0,,0,8,/sabahesaraki/text-to-image-generation-stable-diffusion,Stable Diffusion - Image to Prompts
11198,124020382,1046.0,0.3060902818499879,0,12,/vkoriukina/baseline-w-vit-gpt2-no-out-of-ram-memory-error,Stable Diffusion - Image to Prompts
11199,119597208,1070.0,0.4155107419589547,0,0,/arstimgames/blip-model1,Stable Diffusion - Image to Prompts
11200,119790039,1074.0,0.4264457154177387,4,53,/mayukh18/ofa-transformer-lb-0-42644,Stable Diffusion - Image to Prompts
11201,119656705,1088.0,,0,3,/yaswanthgali/exploring-sd,Stable Diffusion - Image to Prompts
11202,120955518,1093.0,0.4210963183198654,0,2,/umesalma/lb-0-42118-laion-s-coca-vit-openclip,Stable Diffusion - Image to Prompts
11203,143828188,1111.0,,1,0,/akshatgupta2810/blip-large-inference,Stable Diffusion - Image to Prompts
11204,119106553,1135.0,,2,23,/nasuka/lb-0-30612-vit-gpt2-image-captioning-baseline,Stable Diffusion - Image to Prompts
11205,124058117,1134.0,,2,2,/rajkumarl/customized-image-generation-from-prompts,Stable Diffusion - Image to Prompts
11206,128574103,1131.0,,0,1,/sajit08/stable-difusion-v1,Stable Diffusion - Image to Prompts
11207,119501471,1151.0,0.316303664436338,3,41,/thedevastator/blip-large-training-inference,Stable Diffusion - Image to Prompts
11208,119501471,1151.0,0.316303664436338,3,41,/thedevastator/blip-large-training-inference,Stable Diffusion - Image to Prompts
11209,127416993,1173.0,0.305638010131337,0,5,/joonmoahn/generate-prompt-vit-gpt2-img-captioning,Stable Diffusion - Image to Prompts
11210,119333966,1178.0,0.0925831454370764,0,3,/programmaticart/pytorch-inference,Stable Diffusion - Image to Prompts
11211,128369223,1214.0,,0,4,/vinitkp/r-stable-diffusion,Stable Diffusion - Image to Prompts
11238,124074273,12.0,,18,135,/vitalykudelya/explain-dataset-test-api-cross-validation-tips,AMP®-Parkinson's Disease Progression Prediction
11239,129119292,2.0,54.47324442059259,0,4,/dc5e964768ef56302a32/2nd-solution,AMP®-Parkinson's Disease Progression Prediction
11240,119852460,8.0,,3,22,/takanashihumbert/months-average-rating-method,AMP®-Parkinson's Disease Progression Prediction
11241,158687483,1376.0,,0,0,/junbai2022/fixedsetttingdtmodelnewfeatures,AMP®-Parkinson's Disease Progression Prediction
11242,129546685,9.0,,0,0,/mhyodo/amp-visitmonth-model-first-month,AMP®-Parkinson's Disease Progression Prediction
11243,127724288,5.0,56.174983287386695,7,69,/ambrosm/pdpp-almost-only-trends,AMP®-Parkinson's Disease Progression Prediction
11244,130047228,860.0,55.35786638150342,0,1,/hideyukizushi/amp-inf-0518v10-trend-npxx3,AMP®-Parkinson's Disease Progression Prediction
11245,123456412,57.0,,2,3,/adityavartak/comprehensive-eda-amp-pdp,AMP®-Parkinson's Disease Progression Prediction
11246,130259513,600.0,,0,1,/nyosh1005/protein-npx-groups-trend-test,AMP®-Parkinson's Disease Progression Prediction
11247,124489422,804.0,,6,35,/cody11null/using-the-smape-metric,AMP®-Parkinson's Disease Progression Prediction
11248,129995978,931.0,55.93654931453175,0,2,/jiawen9/55-6-in-private-lb-but-overfitting,AMP®-Parkinson's Disease Progression Prediction
11249,129995978,931.0,55.93654931453175,0,2,/jiawen9/55-6-in-private-lb-but-overfitting,AMP®-Parkinson's Disease Progression Prediction
11250,128295926,861.0,56.41491478682641,1,4,/jinshanzhongxue/multi-month-trend,AMP®-Parkinson's Disease Progression Prediction
11251,130153623,21.0,,0,3,/gehallak/pdpp-xgb-no-protein,AMP®-Parkinson's Disease Progression Prediction
11252,127705297,928.0,56.34933514384358,21,58,/dearxsoso/using-feature-selection-xgboost-trend,AMP®-Parkinson's Disease Progression Prediction
11253,119491692,552.0,,2,30,/alejopaullier/amp-train-inference,AMP®-Parkinson's Disease Progression Prediction
11254,141229422,78.0,54.85933593056836,0,4,/gimgoon/amp-single-lightgbm-private-60-179-late-sub,AMP®-Parkinson's Disease Progression Prediction
11255,125727948,34.0,96.09807207372324,1,3,/callmewenhao/amp-pdpp-eda-tf-model,AMP®-Parkinson's Disease Progression Prediction
11256,124396445,45.0,57.26915334897217,0,3,/joonyoungjang/amp-with-randomforest-svr-lasso-decisiontree,AMP®-Parkinson's Disease Progression Prediction
11257,127669408,275.0,,0,4,/zskagcomp/simple-linear-model,AMP®-Parkinson's Disease Progression Prediction
11258,128499144,322.0,57.12996656581342,0,1,/thomasdubail/pdpp-2-stage-model,AMP®-Parkinson's Disease Progression Prediction
11259,123811570,262.0,,0,5,/samvelkoch/prknsn-umap-sandbox,AMP®-Parkinson's Disease Progression Prediction
11260,129510236,329.0,58.06767810543705,10,40,/smnuruzzaman/amp-parkinson-s-xgb-lasso-svm-rfc,AMP®-Parkinson's Disease Progression Prediction
11261,125647288,350.0,,0,0,/m1gusta/notebook677081ca28,AMP®-Parkinson's Disease Progression Prediction
11262,124349244,201.0,,1,16,/dinowun/eda-simplified-amp-pd-progression-prediction,AMP®-Parkinson's Disease Progression Prediction
11263,122595092,820.0,59.33761003288961,0,3,/shitianyu/lb-57-2-ensemble-randomforest-svr-linear,AMP®-Parkinson's Disease Progression Prediction
11264,123998821,25.0,59.59924808455517,6,24,/shimman/baseline-model-using-lgbm-regression,AMP®-Parkinson's Disease Progression Prediction
11265,129996297,485.0,57.26915334897217,0,0,/mewmlelswm/amp-parkinson-s-xgb-lasso-lgbm-rfc-svm-f00156,AMP®-Parkinson's Disease Progression Prediction
11266,129641517,504.0,56.05677682400354,0,1,/lenferdetroud/protein-npx-groups-trend,AMP®-Parkinson's Disease Progression Prediction
11267,122842144,526.0,,0,1,/jackzhang0925/notebook96de96f69b,AMP®-Parkinson's Disease Progression Prediction
11268,127818341,643.0,57.95345420556169,1,1,/zwanguws/wang-arima-apr30,AMP®-Parkinson's Disease Progression Prediction
11269,130245485,571.0,57.26301970096487,12,46,/dangkhanhle/parkinson-s-disease-progression-prediction,AMP®-Parkinson's Disease Progression Prediction
11270,128698257,649.0,57.07229863427749,0,3,/hwang1221/wang-smapelinearregression-may6th,AMP®-Parkinson's Disease Progression Prediction
11271,132840499,665.0,,0,2,/nilupulsandarusiru/pdpp-quadratic-trends,AMP®-Parkinson's Disease Progression Prediction
11272,128476628,711.0,57.08038639584701,0,4,/nikvor/notebook33f1691476,AMP®-Parkinson's Disease Progression Prediction
11273,122535641,558.0,57.56520872587924,0,3,/huhao05133/amp-parkinsons-ensemble-add-xgboost,AMP®-Parkinson's Disease Progression Prediction
11274,128418257,203.0,56.62864553864237,0,2,/weishanshan033/simple-extratreesregressor-56-5-smape,AMP®-Parkinson's Disease Progression Prediction
11275,127423376,1574.0,,0,1,/seangormann/amp-updrs-data-prep-eda,AMP®-Parkinson's Disease Progression Prediction
11276,122583031,1002.0,,1,6,/cafelatte1/pdpp-eda-on-parkinson-s-disease,AMP®-Parkinson's Disease Progression Prediction
11277,128886456,583.0,,4,19,/yzokulu/simple-extratreesregressor-56-5-smape,AMP®-Parkinson's Disease Progression Prediction
11278,128510672,586.0,,0,0,/wesleytjy/pdpp-almost-only-trends-f8776b,AMP®-Parkinson's Disease Progression Prediction
11279,126956052,279.0,76.00981453302018,0,0,/nickvorr/notebook5c84d147f1,AMP®-Parkinson's Disease Progression Prediction
11280,122556453,916.0,,0,5,/kpkent/linear-model-of-proteins-only-parkinsons,AMP®-Parkinson's Disease Progression Prediction
11281,128317230,122.0,,20,41,/serkanp/amp-parkinson-s-disease-progression-prediction,AMP®-Parkinson's Disease Progression Prediction
11282,124585531,280.0,,3,20,/demche/amp-parkinson-s-disease-eda,AMP®-Parkinson's Disease Progression Prediction
11283,130714286,856.0,,0,0,/uom200269j/uom-cs3111-23-group07-final-submission,AMP®-Parkinson's Disease Progression Prediction
11284,125465155,146.0,56.40089450757424,0,3,/slimreaper/fork-of-fork-of-parkcomp,AMP®-Parkinson's Disease Progression Prediction
11285,125680771,720.0,,0,1,/shujunge/best-model,AMP®-Parkinson's Disease Progression Prediction
11286,127542509,1408.0,,0,0,/mariastephenson/peptide-and-protein-correlations,AMP®-Parkinson's Disease Progression Prediction
11287,126576072,124.0,56.37838443627018,0,11,/devanshjpg/time-trends,AMP®-Parkinson's Disease Progression Prediction
11288,124760734,110.0,,1,4,/pcjimmmy/what-patients-are-control,AMP®-Parkinson's Disease Progression Prediction
11289,124167050,130.0,57.353912011753685,0,6,/vijaykumarphy068/amp-parkinson-disease-score-50,AMP®-Parkinson's Disease Progression Prediction
11290,125513022,150.0,61.66588143690556,0,0,/seanwibi/lgbm-baseline,AMP®-Parkinson's Disease Progression Prediction
11291,129935720,250.0,56.39939646499015,0,9,/sabahesaraki/parkinson-s-disease-progression-prediction,AMP®-Parkinson's Disease Progression Prediction
11292,130530205,833.0,,0,5,/ridamahmood005/practicing-amp-parkinsons-s-disease-62-3,AMP®-Parkinson's Disease Progression Prediction
11293,129039154,846.0,56.43005150922068,0,0,/uom200399g/trial-submission-using-public-notebooks,AMP®-Parkinson's Disease Progression Prediction
11294,128961875,1495.0,61.72146193384436,0,1,/filipelipster/new-approach-using-proteins,AMP®-Parkinson's Disease Progression Prediction
11295,128961875,1495.0,61.72146193384436,0,1,/filipelipster/new-approach-using-proteins,AMP®-Parkinson's Disease Progression Prediction
11296,126610501,1034.0,,0,2,/jiaqingfu2000/parkinsons-different-models,AMP®-Parkinson's Disease Progression Prediction
11297,126610501,1034.0,,0,2,/jiaqingfu2000/parkinsons-different-models,AMP®-Parkinson's Disease Progression Prediction
11298,126006982,983.0,56.602416920840135,0,4,/federer/basic-regressions-linear-bayesian,AMP®-Parkinson's Disease Progression Prediction
11299,126737766,1036.0,,0,0,/redredguy/simple-linearregression-updated-56-6-smape,AMP®-Parkinson's Disease Progression Prediction
11300,130877496,1043.0,,0,1,/uom200384g/lab-2-regression,AMP®-Parkinson's Disease Progression Prediction
11301,121143429,1052.0,57.70914186836917,13,22,/hiramcho/gridsearchcv-randomforest-optuna-xgboost,AMP®-Parkinson's Disease Progression Prediction
11302,128945331,938.0,56.75769127519986,0,2,/dhanyabenjamin/amp-pd-progression-prediction-lsvr-u-based,AMP®-Parkinson's Disease Progression Prediction
11303,164996950,940.0,,1,5,/femate2357/get-protein-sequences,AMP®-Parkinson's Disease Progression Prediction
11304,125841891,966.0,,0,2,/mcliff/amp-pd-exploratory-data-analysis,AMP®-Parkinson's Disease Progression Prediction
11305,127495174,1058.0,57.13953517382024,11,18,/umbertofasci/amp-pdpp-eda-tf-model,AMP®-Parkinson's Disease Progression Prediction
11306,124072405,1106.0,60.5702130347899,0,2,/mmmarchetti/cross-validation,AMP®-Parkinson's Disease Progression Prediction
11307,129992955,1145.0,61.0107875641689,0,2,/uom200590j/group-03-uom-cse,AMP®-Parkinson's Disease Progression Prediction
11308,119677491,904.0,67.5981780764119,7,30,/danielpeshkov/manual-estimate-baseline,AMP®-Parkinson's Disease Progression Prediction
11309,122152402,1211.0,57.70914186836917,18,98,/bibanh/update-57-4-train-inference-randomforest,AMP®-Parkinson's Disease Progression Prediction
11310,124661215,1252.0,57.26915334897217,1,6,/suneetsaini/amp-pdpp-random-forest-lasso-lgbm-others,AMP®-Parkinson's Disease Progression Prediction
11311,120034587,947.0,,7,57,/prachi13/amp-parkinson-disease,AMP®-Parkinson's Disease Progression Prediction
11312,120046228,949.0,,1,6,/soumikdasgupta/severity-is-related-to-no-of-proteins-in-csf,AMP®-Parkinson's Disease Progression Prediction
11313,120558774,954.0,57.353912011753685,0,1,/ahsanhabib98/parkinson-s-disease-progression,AMP®-Parkinson's Disease Progression Prediction
11314,120809153,957.0,57.353912011753685,3,16,/eslamfouad/apd-prediction-using-timeseries,AMP®-Parkinson's Disease Progression Prediction
11315,121858093,1084.0,,1,7,/xarispanagiotopoulos/linearregression-xgb,AMP®-Parkinson's Disease Progression Prediction
11316,132770973,1081.0,,0,0,/gayaniwickramarathna/notebook5-parkinson,AMP®-Parkinson's Disease Progression Prediction
11317,120445886,1132.0,57.3893586754599,1,6,/saraswatitiwari/parkinson-s-disease-progression-prediction,AMP®-Parkinson's Disease Progression Prediction
11318,130101024,1417.0,57.43449920190725,0,1,/uom200279n/parkinson-syndrome-prediction,AMP®-Parkinson's Disease Progression Prediction
11319,132319603,1359.0,57.43874554153222,0,3,/uom200421u/lab-2-group-17,AMP®-Parkinson's Disease Progression Prediction
11320,122584073,1301.0,58.49148493712132,1,6,/lordxerxes/baseline-model,AMP®-Parkinson's Disease Progression Prediction
11321,122283633,1306.0,63.22839105565827,0,1,/johnycooly/parkinson-disease-predictions,AMP®-Parkinson's Disease Progression Prediction
11322,126472359,1319.0,,0,0,/bennardong/eda-with-sql-pandas-finance,AMP®-Parkinson's Disease Progression Prediction
11323,126159492,1321.0,,0,0,/minstones/notebook5d08e86353,AMP®-Parkinson's Disease Progression Prediction
11324,129343031,1328.0,,0,0,/dagartallison/parkinsons-submission-v1,AMP®-Parkinson's Disease Progression Prediction
11325,130029326,1326.0,63.42218012254575,0,0,/ginushmalwikumjith/uom-cs3111-23-group09-attempt-01,AMP®-Parkinson's Disease Progression Prediction
11326,129054909,1327.0,57.478954818120656,0,1,/thefreakin/linearregression-simple-57-3-smape,AMP®-Parkinson's Disease Progression Prediction
11327,124037134,1160.0,,1,8,/michal71/sequential-rnn,AMP®-Parkinson's Disease Progression Prediction
11328,120857924,1420.0,,0,1,/josuah/datasets-to-predict-6-12-24-months-updrs-scores,AMP®-Parkinson's Disease Progression Prediction
11329,122555391,1459.0,,1,4,/abinsingh/top-8-peptide-levels-affecting-updrs-1-score,AMP®-Parkinson's Disease Progression Prediction
11330,130096244,1199.0,57.82739873050804,0,0,/uom200441f/200441f-2,AMP®-Parkinson's Disease Progression Prediction
11331,120605979,1339.0,,2,19,/ravindrasonawane/parkinsons-disease-eda-prelim-model-84-smape,AMP®-Parkinson's Disease Progression Prediction
11332,119977372,1333.0,,0,3,/albertoannoni/inconsistencies-between-features-and-target-tables,AMP®-Parkinson's Disease Progression Prediction
11333,121728753,1149.0,58.48302014646954,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11334,121728753,1149.0,58.57112048841532,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11335,121728753,1149.0,58.41491760272118,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11336,121728753,1149.0,58.09893769020312,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11337,121728753,1149.0,58.06053792572293,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11338,121728753,1149.0,58.75282509429053,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11339,121728753,1149.0,58.923236144931,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11340,121728753,1149.0,58.46220661801229,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11341,121728753,1149.0,58.565669872003966,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11342,121728753,1149.0,58.18159291877307,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11343,121728753,1149.0,58.47421493582412,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11344,121728753,1149.0,58.38969797811192,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11345,121728753,1149.0,58.05626004775436,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11346,121728753,1149.0,58.17604141366884,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11347,121728753,1149.0,58.66640763780732,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11348,121728753,1149.0,58.26900566624988,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11349,121728753,1149.0,58.204973870858886,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11350,121728753,1149.0,58.66187208133569,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11351,121728753,1149.0,58.11683251554246,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11352,121728753,1149.0,58.67558225388847,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11353,121728753,1149.0,58.62654011897618,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11354,121728753,1149.0,58.61308016409011,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11355,121728753,1149.0,57.96754798555854,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11356,121728753,1149.0,58.86716476486664,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11357,121728753,1149.0,58.71760007636998,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11358,121728753,1149.0,58.65935191862157,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11359,121728753,1149.0,58.10126433065096,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11360,121728753,1149.0,58.26078661911723,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11361,121728753,1149.0,58.69545145679247,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11362,121728753,1149.0,58.78672567824809,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11363,121728753,1149.0,58.63516281813842,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11364,121728753,1149.0,58.34282123883485,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11365,121728753,1149.0,58.29313008192785,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11366,121728753,1149.0,58.80106403779867,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11367,121728753,1149.0,58.87418186252388,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11368,121728753,1149.0,58.95660408450419,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11369,121728753,1149.0,58.490939589540005,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11370,121728753,1149.0,58.46453471867975,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11371,121728753,1149.0,58.404856695104655,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11372,121728753,1149.0,58.27808878394771,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11373,121728753,1149.0,58.79087155915593,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11374,121728753,1149.0,58.62299672636402,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11375,121728753,1149.0,58.75061737085146,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11376,121728753,1149.0,58.57654531648004,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11377,121728753,1149.0,58.462363620349976,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11378,121728753,1149.0,58.525524002502536,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11379,121728753,1149.0,58.414838816999485,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11380,121728753,1149.0,58.46811958207853,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11381,121728753,1149.0,58.74060838174915,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11382,121728753,1149.0,58.62245169311192,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11383,121728753,1149.0,58.26606498805835,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11384,121728753,1149.0,58.387311890487325,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11385,121728753,1149.0,58.47435785229487,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11386,121728753,1149.0,58.59000021587895,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11387,121728753,1149.0,58.30274791842568,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11388,121728753,1149.0,58.32071965360248,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11389,121728753,1149.0,58.03385676809657,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11390,121728753,1149.0,58.05930849754047,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11391,121728753,1149.0,58.397905566813726,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11392,121728753,1149.0,58.67259519660346,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11393,121728753,1149.0,58.289669133244594,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11394,121728753,1149.0,58.61352554882594,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11395,121728753,1149.0,58.67822726575332,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11396,121728753,1149.0,58.58502784933496,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11397,121728753,1149.0,58.69678125876035,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11398,121728753,1149.0,59.06667433522792,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11399,121728753,1149.0,58.644767062494296,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11400,121728753,1149.0,58.80045489954057,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11401,121728753,1149.0,58.45948079894978,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11402,121728753,1149.0,58.741525101209,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11403,121728753,1149.0,58.2783331469398,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11404,121728753,1149.0,58.56316702381422,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11405,121728753,1149.0,58.01926437940013,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11406,121728753,1149.0,58.14758066506378,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11407,121728753,1149.0,58.0846107696882,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11408,121728753,1149.0,58.09584717580888,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11409,121728753,1149.0,59.24270907057188,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11410,121728753,1149.0,58.97942378648536,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11411,121728753,1149.0,58.38971913249442,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11412,121728753,1149.0,59.200351042074,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11413,121728753,1149.0,59.18183928337015,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11414,121728753,1149.0,58.52324541768269,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11415,121728753,1149.0,58.60995278202533,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11416,121728753,1149.0,58.60342892775341,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11417,121728753,1149.0,58.38984680192879,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11418,121728753,1149.0,58.58108110550299,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11419,121728753,1149.0,58.32826022369826,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11420,121728753,1149.0,58.098394988267664,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11421,121728753,1149.0,58.64368590607387,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11422,121728753,1149.0,58.45253371079535,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11423,121728753,1149.0,58.39954268086648,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11424,121728753,1149.0,58.34555280342969,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11425,121728753,1149.0,58.45038929306615,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11426,121728753,1149.0,58.54471533215554,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11427,121728753,1149.0,58.58970040812444,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11428,121728753,1149.0,58.94559530752371,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11429,121728753,1149.0,58.33745871257919,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11430,121728753,1149.0,58.47097199618223,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11431,121728753,1149.0,58.13101367250135,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11432,121728753,1149.0,58.50884970334188,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11433,121728753,1149.0,58.87725763538243,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11434,121728753,1149.0,58.202124313533865,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11435,121728753,1149.0,58.29291793141138,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11436,121728753,1149.0,58.34925262647593,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11437,121728753,1149.0,58.24085371839692,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11438,121728753,1149.0,58.3588576276109,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11439,121728753,1149.0,58.48715438507701,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11440,121728753,1149.0,58.28030728842384,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11441,121728753,1149.0,58.69585406811236,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11442,121728753,1149.0,58.585720358701096,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11443,121728753,1149.0,58.59433463170197,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11444,121728753,1149.0,58.3611140680646,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11445,121728753,1149.0,58.84529690548455,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11446,121728753,1149.0,58.41858647580028,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11447,121728753,1149.0,58.48280584370505,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11448,121728753,1149.0,58.462736340701824,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11449,121728753,1149.0,58.6765508706369,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11450,121728753,1149.0,58.58744892799632,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11451,121728753,1149.0,58.65935404053093,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11452,121728753,1149.0,58.66570285269741,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11453,121728753,1149.0,58.74327780709432,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11454,121728753,1149.0,58.4191988423505,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11455,121728753,1149.0,58.448022975862216,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11456,121728753,1149.0,58.61311680664056,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11457,121728753,1149.0,58.67722515675285,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11458,121728753,1149.0,58.40802465252494,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11459,121728753,1149.0,58.35003449544652,0,4,/gopalakrishnankumar/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11460,126048362,1336.0,58.80633808962551,0,3,/ebrahimgholami/amp-parkinson-s-disease-progression-prediction,AMP®-Parkinson's Disease Progression Prediction
11461,122584086,1077.0,68.81285273612137,19,72,/seanmulholland/protein-data-tf-model-70-8-lb,AMP®-Parkinson's Disease Progression Prediction
11462,122043420,1380.0,58.37163250535847,1,3,/masahikofujita/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11463,126519314,1387.0,,20,73,/adityarahul/eda-linearregression,AMP®-Parkinson's Disease Progression Prediction
11464,127109808,1393.0,,0,2,/rachanabisht/simple-profiling-eda-using-pandas-profiling,AMP®-Parkinson's Disease Progression Prediction
11465,130781230,1551.0,,0,0,/malshancs/notebooka07222a0dd,AMP®-Parkinson's Disease Progression Prediction
11466,121755882,1367.0,59.00165694266727,0,3,/sanandachowdhury/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11467,121755882,1367.0,58.79415335024076,0,3,/sanandachowdhury/eda-tf-model-median-baseline-moderate-75,AMP®-Parkinson's Disease Progression Prediction
11468,129064704,1518.0,104.28710085871067,0,0,/uom200110p/submission-1,AMP®-Parkinson's Disease Progression Prediction
11469,123462570,981.0,,2,6,/leweisele/basic-api-usage-random-forest,AMP®-Parkinson's Disease Progression Prediction
11470,130071337,1482.0,,0,1,/uom200472b/notebook5c63eaf1a9,AMP®-Parkinson's Disease Progression Prediction
11471,124092658,1538.0,,0,1,/ved1104/peptide-disease-progression-and-detection,AMP®-Parkinson's Disease Progression Prediction
11472,125030324,1504.0,,0,3,/vinitkp/eda-r-logisticregression,AMP®-Parkinson's Disease Progression Prediction
11473,120063507,1591.0,91.2867698408879,3,11,/acousticmusic/2023-easy-understand-parkinson-train-inference,AMP®-Parkinson's Disease Progression Prediction
11474,128767923,1572.0,61.3873960755616,0,0,/bennamafethi/amp-linear,AMP®-Parkinson's Disease Progression Prediction
11475,129828047,1506.0,61.38488890443615,0,0,/uom200480x/parkinson-s-disease-progression-prediction-w-tfdf,AMP®-Parkinson's Disease Progression Prediction
11476,126136984,1558.0,,1,2,/samratthapa/parkinsons-lstm-model-groupkfold-lb-62,AMP®-Parkinson's Disease Progression Prediction
11477,129325436,1588.0,83.89243030434652,0,3,/hongyuguo/amp-protein-peptides-network-deeplearning-v2,AMP®-Parkinson's Disease Progression Prediction
11478,130498191,1578.0,,0,1,/uom200040b/ml-lab2-group-20,AMP®-Parkinson's Disease Progression Prediction
11479,119575605,1639.0,,5,13,/sijovm/score-89-how-to-make-submissions,AMP®-Parkinson's Disease Progression Prediction
11480,128160992,1544.0,62.88687401199727,14,72,/gusthema/parkinson-s-disease-progression-prediction-w-tfdf,AMP®-Parkinson's Disease Progression Prediction
11481,119627785,1641.0,,2,10,/alexfir/multiple-patients-have-the-same-history-of-updrs-3,AMP®-Parkinson's Disease Progression Prediction
11482,130046630,1662.0,66.42807268160855,0,3,/yeemeitsang/parkinsons-progression-xgboost,AMP®-Parkinson's Disease Progression Prediction
11483,127556013,1584.0,63.12354597321296,2,4,/slavomirnp/data-analisis,AMP®-Parkinson's Disease Progression Prediction
11484,129115546,1524.0,63.241032677570864,0,19,/deepikaarikesavan/parkinson-s-disease-progression-prediction-w-tfdf,AMP®-Parkinson's Disease Progression Prediction
11485,129115546,1524.0,63.357352643829714,0,19,/deepikaarikesavan/parkinson-s-disease-progression-prediction-w-tfdf,AMP®-Parkinson's Disease Progression Prediction
11486,120547321,1651.0,,1,1,/danfu42/phate-t-sne-pca-for-pd-progression-clustering,AMP®-Parkinson's Disease Progression Prediction
11487,133352488,1554.0,,0,3,/uom200199t/lab02-group02-2-3fe622,AMP®-Parkinson's Disease Progression Prediction
11488,119912326,1679.0,,0,3,/kimorwu/quickstart-pdprediction,AMP®-Parkinson's Disease Progression Prediction
11489,127309491,1720.0,78.56231115831133,0,4,/treeleaves30760/20230425-amp,AMP®-Parkinson's Disease Progression Prediction
11490,127390469,1726.0,,0,2,/midhunthaduru/amp-parkinsons-prediction,AMP®-Parkinson's Disease Progression Prediction
11491,121601335,1735.0,,1,1,/ablambe/amp-parkinsons-competition-submission-notebook,AMP®-Parkinson's Disease Progression Prediction
11492,120024189,1751.0,,1,7,/younesselbrag/amp-park-gradientboostregression-datapipline,AMP®-Parkinson's Disease Progression Prediction
11493,125506646,1744.0,125.65429096905592,0,8,/dellalkhaled/real-wealth,AMP®-Parkinson's Disease Progression Prediction
11494,129385928,1749.0,89.07648125950041,0,0,/tikemoto/202304-amp-parkinsons-skb,AMP®-Parkinson's Disease Progression Prediction
11495,124483375,1763.0,,1,3,/matthewsfarmer/amp-parkinson-s-disease-progression-pred,AMP®-Parkinson's Disease Progression Prediction
11496,125580872,1769.0,,0,1,/shakirayman/prot-pep2,AMP®-Parkinson's Disease Progression Prediction
11497,125580872,1769.0,,0,1,/shakirayman/prot-pep2,AMP®-Parkinson's Disease Progression Prediction
11498,121278965,32.0,,0,0,/shionmatsuoka/new-features-and-outlier-improvement,Regression with a Tabular Gemstone Price Dataset
11499,119883857,19.0,,1,5,/dongjun819/pycaret-pgs3-8,Regression with a Tabular Gemstone Price Dataset
11500,121212054,7.0,574.7708397567038,0,1,/jbomitchell/gem-median-ensembler,Regression with a Tabular Gemstone Price Dataset
11501,121264462,35.0,574.8825604681152,0,6,/uyeanil/pgs-s3e8-ensemble-kfolds,Regression with a Tabular Gemstone Price Dataset
11502,148447122,23.0,,32,73,/javohirtoshqorgonov/gemstone-price-prediction-eda,Regression with a Tabular Gemstone Price Dataset
11503,121113284,25.0,3038.259929390712,0,12,/satyaprakashshukl/eda-playing-s3-e8-price-pred,Regression with a Tabular Gemstone Price Dataset
11504,121022965,30.0,,6,35,/samuelcortinhas/ps-s3e8-gem-price-prediction,Regression with a Tabular Gemstone Price Dataset
11505,120858369,41.0,,10,10,/atogni85/pgs03e08-eda-outliers-detection-basic-model,Regression with a Tabular Gemstone Price Dataset
11506,121246433,48.0,,10,28,/janmpia/s3-8-visual-eda,Regression with a Tabular Gemstone Price Dataset
11507,120830023,43.0,602.3821592669049,4,9,/saniyatlamim007/ps-3-8-w-xgbregressor,Regression with a Tabular Gemstone Price Dataset
11508,120830023,43.0,602.3821592669049,4,9,/saniyatlamim007/ps-3-8-w-xgbregressor,Regression with a Tabular Gemstone Price Dataset
11509,121071468,65.0,575.1868037065148,18,68,/tetsutani/ps3e8-xgb-lgbm-cat-ensemble-baseline,Regression with a Tabular Gemstone Price Dataset
11510,120982926,116.0,576.0225061227893,8,31,/ch124uec/plotly-eda-feature-engineering-optuna,Regression with a Tabular Gemstone Price Dataset
11511,120155763,60.0,,4,19,/khawajaabaidullah/ps3e8-starting-strong-ensembling-gdbts,Regression with a Tabular Gemstone Price Dataset
11512,121130434,36.0,575.4511239285499,2,12,/eamonntweedy/playground-s3-e8-gemstones-xgb-lgb-cb-ensemble,Regression with a Tabular Gemstone Price Dataset
11513,121319541,78.0,,22,36,/sujaykapadnis/ps3e8-models-ensemble-final-submission,Regression with a Tabular Gemstone Price Dataset
11514,119932364,61.0,581.6007396234163,5,12,/yimingliang/pss3-e8-eda-feature-engineering-lgbm,Regression with a Tabular Gemstone Price Dataset
11515,120679995,72.0,,4,12,/enjoyingworld/nn-fastai-lgbm-catboost,Regression with a Tabular Gemstone Price Dataset
11516,120749351,63.0,578.300507318481,0,6,/omarvivas/lgbm-tpgs-s3e8-v1,Regression with a Tabular Gemstone Price Dataset
11517,120020127,62.0,582.792871140419,0,3,/santiagopedroza/s3e8-eda-and-an-intro-submission,Regression with a Tabular Gemstone Price Dataset
11518,119817952,82.0,,2,13,/masayakawamata/catboost-lightgbm-xgboost,Regression with a Tabular Gemstone Price Dataset
11519,120359658,140.0,578.1548728681278,0,6,/rkoirala129/xgboost-regression-baseline,Regression with a Tabular Gemstone Price Dataset
11520,121266505,113.0,576.5369472584233,0,1,/sahilsg/gemstone-s3-e8-ensemble-xgb-lgbm-catb-stacking,Regression with a Tabular Gemstone Price Dataset
11521,120780249,146.0,577.7412504138098,1,14,/samuraikaggle/samurai-s3e8ens-featureengineering-cb-xb-lb,Regression with a Tabular Gemstone Price Dataset
11522,120931526,136.0,,1,3,/deshram/ps-s3e08-simple-baseline-model-for-begineers,Regression with a Tabular Gemstone Price Dataset
11523,120781762,131.0,577.6837630170396,14,25,/satoshiss/gemstone-price-prediction-s3e8,Regression with a Tabular Gemstone Price Dataset
11524,119990330,104.0,,5,29,/mattop/playground-series-s3-e8-eda-3d-plots,Regression with a Tabular Gemstone Price Dataset
11525,120400614,134.0,586.5663371755696,2,10,/mtulgac/chatgpt-lightgbm-optuna,Regression with a Tabular Gemstone Price Dataset
11526,120255260,282.0,584.8364033039126,0,1,/pawebiegun/playground-season-3-episode-8,Regression with a Tabular Gemstone Price Dataset
11527,121178144,209.0,586.2718945490731,4,20,/pranavkannepalli/gemstonepriceprediction,Regression with a Tabular Gemstone Price Dataset
11528,120206903,155.0,581.3091040693039,0,9,/lonnieqin/s3e8-with-optuna-pruner,Regression with a Tabular Gemstone Price Dataset
11529,121220945,169.0,1000.4892397929732,0,12,/charunumesh/playground-series-s3-e8-ensemble,Regression with a Tabular Gemstone Price Dataset
11530,120793206,200.0,579.666196103,0,2,/umanglodaya/playground-series-s3e8-xgboost,Regression with a Tabular Gemstone Price Dataset
11531,120021713,184.0,,6,19,/abdoulayebalde/pse8-eda-lgbm-baseline,Regression with a Tabular Gemstone Price Dataset
11532,120126368,190.0,581.8734478921111,2,14,/matthewjansen/gemstone-price-prediction-xgboost,Regression with a Tabular Gemstone Price Dataset
11533,119957016,166.0,631.1199796799274,0,2,/andreaskaufmann/s3e8-simple-dnn-with-tensorflow,Regression with a Tabular Gemstone Price Dataset
11534,120018888,214.0,580.4777167669553,4,11,/icfoer/ps3e8-original-train-eda-modeling-in-progress,Regression with a Tabular Gemstone Price Dataset
11535,120107384,130.0,580.2763292416017,7,38,/oscarm524/ps-s3-ep8-eda-modeling,Regression with a Tabular Gemstone Price Dataset
11536,120892015,168.0,585.3191406259639,0,5,/tnghthanh/s3e8-lgbm-optuna-and-tune-the-model-while-train,Regression with a Tabular Gemstone Price Dataset
11537,120446507,267.0,582.6087645971797,4,20,/akioonodera/ps-3-08-lgbm-reg,Regression with a Tabular Gemstone Price Dataset
11538,120419634,215.0,,0,4,/arosielle/s3-8-lgbm-optuna,Regression with a Tabular Gemstone Price Dataset
11539,121143588,171.0,580.9314542003507,0,0,/krbharat/ps3-e8-ensemble-model,Regression with a Tabular Gemstone Price Dataset
11540,119884071,202.0,580.9883672628708,1,12,/mnokno/gemstone-price-prediction-using-xgboost,Regression with a Tabular Gemstone Price Dataset
11541,121246394,251.0,583.4247618629392,1,6,/alexandrepetit881234/s3e8-eda-and-predictions,Regression with a Tabular Gemstone Price Dataset
11542,120187384,179.0,,0,9,/masatakasuzuki/starter-notebook-simple-keras-for-tabular-data,Regression with a Tabular Gemstone Price Dataset
11543,120980992,248.0,,0,0,/erwinhmtang/playground-s3e8-ensemble-wt-optuna,Regression with a Tabular Gemstone Price Dataset
11544,121235055,188.0,582.8947663566757,1,7,/amrelsayeh/pgs-s3e8-simple-xgboost,Regression with a Tabular Gemstone Price Dataset
11545,121096325,218.0,581.2144416323079,0,0,/alfax213/gemstone-price-prediction-using-xgboost,Regression with a Tabular Gemstone Price Dataset
11546,120087758,260.0,,0,0,/manaidu/playground-series-s3e8,Regression with a Tabular Gemstone Price Dataset
11547,119912030,206.0,,5,32,/jonbown/starter-nb-cluster-pca-reg-xgb-s3e8,Regression with a Tabular Gemstone Price Dataset
11548,120728778,208.0,,0,6,/hiroshikurokawa/p3s8-lgb-catb-xgb-ensemble,Regression with a Tabular Gemstone Price Dataset
11549,120215742,191.0,,0,4,/roxket/poissonregressor-716-5882,Regression with a Tabular Gemstone Price Dataset
11550,120834955,276.0,,2,4,/iamnotashutosh/pg-s3-e8,Regression with a Tabular Gemstone Price Dataset
11551,120335768,243.0,583.5892477696617,0,3,/stpeteishii/pss3-ep8-visualize-importance,Regression with a Tabular Gemstone Price Dataset
11552,120959974,225.0,,0,1,/gamerlacika/gemstone-price-prediktel,Regression with a Tabular Gemstone Price Dataset
11553,120354259,224.0,582.5067851279996,0,2,/dmtamm/s3e8-lightgbm-eng-rus,Regression with a Tabular Gemstone Price Dataset
11554,120536103,242.0,582.0427569282659,0,6,/utkarshgaikwad1994/ps3e8-pycaret-utkarsh-gaikwad,Regression with a Tabular Gemstone Price Dataset
11555,121013136,273.0,582.4204158065276,6,15,/jrreda/s03e08-gemstone-price-prediction,Regression with a Tabular Gemstone Price Dataset
11556,121144365,278.0,582.4251859408608,0,2,/hanrockyh/playgrounds3e8,Regression with a Tabular Gemstone Price Dataset
11557,121166386,309.0,582.6563056780933,0,2,/georgescutelnicu/ps-s3e8-gemstone-price-prediction-lightgbm,Regression with a Tabular Gemstone Price Dataset
11558,119899915,238.0,,1,6,/amarnathaditya/playground-s3e8-eda,Regression with a Tabular Gemstone Price Dataset
11559,143542234,291.0,,11,25,/kattat/gem-price-prediction,Regression with a Tabular Gemstone Price Dataset
11560,120457900,297.0,584.7022444961718,0,1,/catadanna/tab-s3-e8,Regression with a Tabular Gemstone Price Dataset
11561,120636449,341.0,,0,5,/kavishchaudhary1003/playground-s3-e8,Regression with a Tabular Gemstone Price Dataset
11562,120552154,281.0,,0,2,/gauravduttakiit/pss3e8-lazypredict,Regression with a Tabular Gemstone Price Dataset
11563,120640686,370.0,,0,7,/alexkonse/ps3e8-cat-ensemble-xgb-nn,Regression with a Tabular Gemstone Price Dataset
11564,121041575,327.0,588.546500409305,0,3,/sonukumar2k19it124/s3-e8,Regression with a Tabular Gemstone Price Dataset
11565,121188160,299.0,583.8664401521876,0,1,/datascientistsohail/regression-ml-optuna-xgbreg,Regression with a Tabular Gemstone Price Dataset
11566,122850019,425.0,,0,2,/sofiamatias/playground-s3e8,Regression with a Tabular Gemstone Price Dataset
11567,121008855,350.0,584.0147617737363,1,7,/sudhanshu2198/lgbm-with-optuna-plotly-and-feature-selection,Regression with a Tabular Gemstone Price Dataset
11568,119923014,301.0,791.8134643962426,19,60,/burhanuddinlatsaheb/eda-lgbm-catboost,Regression with a Tabular Gemstone Price Dataset
11569,121722941,367.0,588.4487929026807,6,25,/cv13j0/exploring-pycaret,Regression with a Tabular Gemstone Price Dataset
11570,121148896,354.0,,0,1,/tonychirilus/gemstone-price-prediction-with-lgbm-regressor,Regression with a Tabular Gemstone Price Dataset
11571,121066501,376.0,589.0130210629156,0,0,/kaylanghammerdata/gemstones-xgboost,Regression with a Tabular Gemstone Price Dataset
11572,120554021,349.0,585.3062680089346,8,20,/lizhecheng/s3e8-xgb-kfolds,Regression with a Tabular Gemstone Price Dataset
11573,120126762,311.0,,0,7,/mahimchrl/eda-model-s3-ep-8,Regression with a Tabular Gemstone Price Dataset
11574,119923389,357.0,585.0455398456696,10,12,/oldjerry/bayes-fusion-isolated-forest-xgb-lgb-stacking,Regression with a Tabular Gemstone Price Dataset
11575,121080883,427.0,586.2893058157027,6,15,/warcoder/xgboost-solution,Regression with a Tabular Gemstone Price Dataset
11576,119899488,431.0,,2,7,/hwikookchoe/pgs-s3e8-eda-and-regression-practice,Regression with a Tabular Gemstone Price Dataset
11577,120393123,361.0,,0,0,/stevennoel/notebook29dcfffeb1-dtr-2,Regression with a Tabular Gemstone Price Dataset
11578,121246378,374.0,,2,3,/alexbostick/xgboost-regressor-price-prediction,Regression with a Tabular Gemstone Price Dataset
11579,121166923,467.0,587.2620753080868,0,1,/barbagrande007/bbg007-s3e8-gemstones,Regression with a Tabular Gemstone Price Dataset
11580,120527006,385.0,598.0226047755352,2,9,/klyushnik/episode-8,Regression with a Tabular Gemstone Price Dataset
11581,121259704,392.0,586.4023909355175,0,7,/angelmartinezromero/590-explicada-en-espa-ol,Regression with a Tabular Gemstone Price Dataset
11582,120874392,443.0,,2,3,/qahramonuktamov2205/s3e8-xgbregressor-and-other-different-regressors,Regression with a Tabular Gemstone Price Dataset
11583,119992395,405.0,,0,4,/arlle26/s3e8-baseline-lgbm-xgb-rf-lb589,Regression with a Tabular Gemstone Price Dataset
11584,120144409,403.0,795.3800555151636,4,13,/amarloni/pgs3e8-eda-submission,Regression with a Tabular Gemstone Price Dataset
11585,121013874,388.0,587.4930458586341,0,14,/omkarchoulwar/tps-feb-23-eda,Regression with a Tabular Gemstone Price Dataset
11586,121258066,413.0,583.7128311592793,9,14,/ashtcoder/pg-s3-e8-ensemble-encoded-featureeng,Regression with a Tabular Gemstone Price Dataset
11587,120013999,437.0,588.4614438248146,5,11,/chongjiaxu/gemstone-price-lgbm-easy-to-follow-588,Regression with a Tabular Gemstone Price Dataset
11588,147547813,420.0,,10,90,/meeratif/eda-solution-gemstone-price,Regression with a Tabular Gemstone Price Dataset
11589,121097971,445.0,600.150954761955,2,3,/manavd22/xgboost-bayesian-tuning-eda,Regression with a Tabular Gemstone Price Dataset
11590,120818477,453.0,5631.504275412627,1,9,/xbulat/s3-e8-gradientboostingregressor,Regression with a Tabular Gemstone Price Dataset
11591,119978389,511.0,593.868654768562,3,7,/tracyporter/play-3-8,Regression with a Tabular Gemstone Price Dataset
11592,120574775,506.0,595.4564145685486,1,6,/sergeyyakovlev1312/playground-s3e8,Regression with a Tabular Gemstone Price Dataset
11593,121173860,516.0,,0,4,/adityasetyo/gem-stone-price-prediction-eda,Regression with a Tabular Gemstone Price Dataset
11594,120850374,534.0,,0,1,/saswat17/feature-engineering-lr-rfr-and-xgboost,Regression with a Tabular Gemstone Price Dataset
11595,120268494,586.0,611.6573070028758,0,4,/efrainp23/tensorflow-gpu-price-prediction,Regression with a Tabular Gemstone Price Dataset
11596,120666516,598.0,,1,7,/kylegraupe/2-xgboost-tuning-methods-random-and-bayesian,Regression with a Tabular Gemstone Price Dataset
11597,120980185,587.0,,0,0,/johnericbonilla/notebook99ff87ff1e,Regression with a Tabular Gemstone Price Dataset
11598,120049384,584.0,626.9427574075537,1,10,/fuad0857/playground-s3-e8-with-tensorflow,Regression with a Tabular Gemstone Price Dataset
11599,120720405,616.0,,0,0,/agunbiadeopeyemi/notebook0be70b28c1,Regression with a Tabular Gemstone Price Dataset
11600,121014001,627.0,655.1205235136594,0,1,/djwerterrichmond/keras-model,Regression with a Tabular Gemstone Price Dataset
11601,120838375,644.0,,9,18,/gopimali/gemstone-price-prediction,Regression with a Tabular Gemstone Price Dataset
11602,121105256,678.0,1017.4936300036596,0,0,/muhammadnaufalhawari/playground-series,Regression with a Tabular Gemstone Price Dataset
11603,121191780,684.0,,0,0,/anurag930777/notebook89b0ab2559111,Regression with a Tabular Gemstone Price Dataset
11604,121176472,703.0,,0,0,/ahmadjulius/playground-ahmad,Regression with a Tabular Gemstone Price Dataset
11605,120633743,731.0,5636.782302124854,0,0,/jethiwalasaivardhan/pricepredction,Regression with a Tabular Gemstone Price Dataset
11606,123154042,1.0,,0,11,/hoyso48/islr-create-tfr,Google - Isolated Sign Language Recognition
11607,124884880,14.0,,8,55,/tatamikenn/islr-eda-let-s-get-landmarks-animated,Google - Isolated Sign Language Recognition
11608,120208086,30.0,,7,138,/robikscube/sign-language-recognition-eda-twitch-stream,Google - Isolated Sign Language Recognition
11609,121000252,89.0,,4,100,/mayukh18/sign-language-eda-visualization,Google - Isolated Sign Language Recognition
11610,123655230,199.0,,0,1,/meowmeowmeowmeowmeow/asl-sratified-full-dataset-in-tfrecords-format,Google - Isolated Sign Language Recognition
11611,121170164,108.0,,1,1,/jonathanchan/gislr-feature-data-on-the-shoulders-segment3,Google - Isolated Sign Language Recognition
11612,124361919,147.0,0.2138265962005427,0,0,/soumenksarker/isolated-sign-language-recognition-quick-start,Google - Isolated Sign Language Recognition
11613,121126477,185.0,,2,14,/tantai/gislr-background-knowledge-landmarks-visualization,Google - Isolated Sign Language Recognition
11614,121839562,206.0,,0,8,/habedi/asl-signs-dataset-duckdb-notebook,Google - Isolated Sign Language Recognition
11615,121434351,140.0,,0,8,/alexandremoritz/slr-plot-frames-3d-static-animations,Google - Isolated Sign Language Recognition
11616,122785992,246.0,0.6724039422939581,8,23,/aleksandrkruchinin/tflite-ensemble,Google - Isolated Sign Language Recognition
11617,120203706,280.0,,4,19,/bibanh/cv-0-1247-baseline-model-with-tf-random-forest,Google - Isolated Sign Language Recognition
11618,120852232,398.0,0.0024996429081559,2,16,/kooaslansefat/google-islr-evidential-deep-learning,Google - Isolated Sign Language Recognition
11619,159579924,386.0,0.3017426081988287,47,117,/lonnieqin/isolated-sign-language-recognition-with-dnn,Google - Isolated Sign Language Recognition
11620,123633182,387.0,,0,0,/pranavbansal/american-sign-language-data-processing,Google - Isolated Sign Language Recognition
11621,122909480,506.0,,0,9,/dinowun/eda-simplified-isolated-asl-recognition,Google - Isolated Sign Language Recognition
11622,130152011,337.0,,8,42,/josephzahar/interactive-3d-animated-visualization-of-asl,Google - Isolated Sign Language Recognition
11623,120707913,376.0,,0,0,/venkataanandsaikumar/preproceesed-data,Google - Isolated Sign Language Recognition
11624,127885252,267.0,0.5664190829881446,4,11,/jessevanderlinden/basic-lstm-and-transformer-implementation,Google - Isolated Sign Language Recognition
11625,120202237,355.0,,4,22,/asimple/eda-sign-language-recognition,Google - Isolated Sign Language Recognition
11626,126799503,468.0,,0,0,/amirhosseintondari/check,Google - Isolated Sign Language Recognition
11627,120567482,495.0,,2,18,/prajwalsood/islr-with-transformers,Google - Isolated Sign Language Recognition
11628,123402467,616.0,,0,9,/koubouratouidjaton/sign-language-data-exploration-insights-and-fun-3d,Google - Isolated Sign Language Recognition
11629,121066951,711.0,,16,46,/roberthatch/gislr-feature-data-on-the-shoulders,Google - Isolated Sign Language Recognition
11630,120598125,772.0,,4,10,/aapokossi/asl-recognition-data-pipeline-time-series-model,Google - Isolated Sign Language Recognition
11631,123889529,718.0,,6,14,/dhk13491/gislr-simple-pytorch-to-tflite-baseline,Google - Isolated Sign Language Recognition
11632,123328617,716.0,0.562419654335095,0,1,/stanptown/lstm-baseline-for-starters-sign-language-eeff0f,Google - Isolated Sign Language Recognition
11633,126023628,712.0,,0,0,/lameuler/asl-eda,Google - Isolated Sign Language Recognition
11634,125666826,746.0,,0,1,/sujaykapadnis/sign-language,Google - Isolated Sign Language Recognition
11635,120239801,754.0,,4,16,/mhetrerajat/pytorch-tflite,Google - Isolated Sign Language Recognition
11636,122395197,758.0,,0,8,/johnrobinsn/use-mediapipe-to-render-parquet-files,Google - Isolated Sign Language Recognition
11637,120492048,798.0,0.3120982716754749,5,51,/myso1987/gislr-pytorch-tflite-baseline,Google - Isolated Sign Language Recognition
11638,143016471,782.0,,0,0,/nilsle/convlstm-asl,Google - Isolated Sign Language Recognition
11639,122169841,818.0,0.6339094415083559,0,0,/snehaiitkgp/challenge-isolated-sign-language-recognition,Google - Isolated Sign Language Recognition
11640,121677562,820.0,0.6333380945579203,0,5,/saraswatitiwari/tflite-isolated-sign-language-recognition,Google - Isolated Sign Language Recognition
11641,121578657,878.0,0.6291958291672618,0,0,/khaledjamal/popsign-asl-sign-classification-notebook,Google - Isolated Sign Language Recognition
11642,120606248,831.0,,0,2,/abdelrahmanhassanein/eda-and-visualize,Google - Isolated Sign Language Recognition
11643,120398412,776.0,,1,7,/juanolano/an-lstm-approach-still-very-sub-par,Google - Isolated Sign Language Recognition
11644,120314962,887.0,,1,18,/jarvisai7/tensorflow-pytorch-to-tflite,Google - Isolated Sign Language Recognition
11645,126979096,916.0,,1,13,/suyashsunilraomorale/isolated-sign-language-recognition-eda,Google - Isolated Sign Language Recognition
11646,140900240,909.0,,16,68,/jvthunder/lstm-baseline-for-starters-sign-language,Google - Isolated Sign Language Recognition
11647,122499908,930.0,0.5439937151835452,2,13,/sabahesaraki/google-isolated-sign-language-recognition,Google - Isolated Sign Language Recognition
11648,126830619,952.0,,0,2,/myominhtet/aslr-eda,Google - Isolated Sign Language Recognition
11649,128820163,977.0,,0,0,/kirstenwiens/eda-isolated-sign-language-recogntion,Google - Isolated Sign Language Recognition
11650,126282503,1042.0,0.4891444079417226,2,10,/researchlad/hand-recognition,Google - Isolated Sign Language Recognition
11651,127831000,986.0,0.4766461934009427,0,0,/priyam8210/sign-2b,Google - Isolated Sign Language Recognition
11652,121146896,1037.0,,0,4,/juanumusic/validate-all-data-is-arranged-the-same,Google - Isolated Sign Language Recognition
11653,126351043,1034.0,,0,5,/stpeteishii/asl-signs-2d-3d-slide-show,Google - Isolated Sign Language Recognition
11654,120213434,1046.0,,0,7,/profetul/how-to-generate-compatible-tf-lite-model,Google - Isolated Sign Language Recognition
11655,120308280,1063.0,,0,1,/rbhambri/tflite-model-conversion,Google - Isolated Sign Language Recognition
11656,124937137,1081.0,0.3049564347950292,0,0,/nihalraogokaraneni/isolated-american-sign-language-recognition,Google - Isolated Sign Language Recognition
11657,120553250,1088.0,0.2924582202542494,2,29,/masterofdeception/isolated-sign-language-recognition-with-dnn,Google - Isolated Sign Language Recognition
11658,121909882,1119.0,0.2769604342236823,0,13,/dorianmb/isolated-sign-language-recognition-quick-start,Google - Isolated Sign Language Recognition
11659,126576544,1125.0,0.1771889730038565,1,8,/alimustoofaa/pytorch-to-tflite,Google - Isolated Sign Language Recognition
11660,120207693,1133.0,,11,110,/danielpeshkov/animated-data-visualization,Google - Isolated Sign Language Recognition
11661,120666379,1163.0,0.0002856734752178,2,12,/renzophellan/understanding-the-data-creating-a-model,Google - Isolated Sign Language Recognition
11662,120649460,64.0,11.783198883914668,1,10,/lyasdemir/simple-price-estimation-projectt,Regression with a Tabular Concrete Strength Dataset
11663,120582883,135.0,,0,2,/dongjun819/pycaret-pgs3-9,Regression with a Tabular Concrete Strength Dataset
11664,120887152,202.0,,0,4,/tylerchi/concretestrengthpredictionfeb,Regression with a Tabular Concrete Strength Dataset
11665,121770660,63.0,11.84120868495127,5,6,/anhdangquy/baseline-model-xgboost-with-fine-tuning,Regression with a Tabular Concrete Strength Dataset
11666,121914033,215.0,11.883946138809018,0,7,/omarvivas/cb-tpgs-s3e9-v1,Regression with a Tabular Concrete Strength Dataset
11667,120677472,219.0,13.032014238825775,0,12,/satyaprakashshukl/eda-xgb-ps-s3-e9,Regression with a Tabular Concrete Strength Dataset
11668,120792817,161.0,11.82749954883696,1,8,/lizhecheng/s3e9-simple-gbr-strength-prediction,Regression with a Tabular Concrete Strength Dataset
11669,121984220,314.0,11.82219249750894,32,80,/alexandershumilin/ps-s3-e9-ensemble-model,Regression with a Tabular Concrete Strength Dataset
11670,162031476,317.0,,12,35,/tetsutani/ps3e9-eda-and-gbdt-catboost-median-duplicatedata,Regression with a Tabular Concrete Strength Dataset
11671,120560821,203.0,,3,33,/mattop/playground-series-s3-e9-eda-tsne-pca,Regression with a Tabular Concrete Strength Dataset
11672,121495962,167.0,,0,8,/uyeanil/playground-series-s3e9-kfolds-ensemble,Regression with a Tabular Concrete Strength Dataset
11673,121690466,162.0,11.730146464200788,3,7,/rustam1488/s3e9-ens-model,Regression with a Tabular Concrete Strength Dataset
11674,121627962,61.0,11.826358873948395,1,11,/dillanwilliams/playground-s3-9,Regression with a Tabular Concrete Strength Dataset
11675,121949776,262.0,11.818467110806353,2,19,/s4557161/playground-s3e9-lightgbm-xgboost-optuna,Regression with a Tabular Concrete Strength Dataset
11676,120770898,406.0,,2,14,/vaidyaprasad84/ps3-e9-feature-engineering,Regression with a Tabular Concrete Strength Dataset
11677,122475544,436.0,,0,0,/peterreid/concrete-strength-predictor,Regression with a Tabular Concrete Strength Dataset
11678,120827531,382.0,11.753137178883726,2,9,/saniyatlamim007/sklearn-boost-w-feature-engineering,Regression with a Tabular Concrete Strength Dataset
11679,120655439,196.0,,0,12,/nikitagrec/data-leak-53-catboost,Regression with a Tabular Concrete Strength Dataset
11680,121870395,499.0,,2,7,/alfiyafakhrutdinova/ensemble-model-bagging-stacking-voting-11-762,Regression with a Tabular Concrete Strength Dataset
11681,121609908,235.0,11.835746164755454,0,3,/syerramilli/ps3e9-xgboost-hyperopt,Regression with a Tabular Concrete Strength Dataset
11682,120871541,368.0,,0,6,/nayanpariya/regression-using-xgbooost-votingregressor,Regression with a Tabular Concrete Strength Dataset
11683,121987468,394.0,11.76842710111773,0,1,/nguynqunam/playgroundseries-s3e9,Regression with a Tabular Concrete Strength Dataset
11684,120713704,27.0,11.769836873336953,2,13,/matthewjansen/concrete-strength-prediction-with-tf-df,Regression with a Tabular Concrete Strength Dataset
11685,121975648,48.0,11.868941693207455,8,26,/sujaykapadnis/s3e9-ensemble-model-duplicates-in-kfold-final,Regression with a Tabular Concrete Strength Dataset
11686,133152214,194.0,,1,16,/gkitchen/concrete-strength-prediction,Regression with a Tabular Concrete Strength Dataset
11687,121355167,597.0,11.916887487185813,0,2,/sanandachowdhury/ps-s3-e9-ensemble-model,Regression with a Tabular Concrete Strength Dataset
11688,121355167,597.0,11.916887487185813,0,2,/sanandachowdhury/ps-s3-e9-ensemble-model,Regression with a Tabular Concrete Strength Dataset
11689,121355167,597.0,11.916887487185813,0,2,/sanandachowdhury/ps-s3-e9-ensemble-model,Regression with a Tabular Concrete Strength Dataset
11690,120790367,99.0,,0,8,/amarloni/pgs3e9-pandas-cut,Regression with a Tabular Concrete Strength Dataset
11691,121793175,30.0,11.813723144682529,8,31,/charunumesh/playground-series-s3e9-ensemble-xgb-cat-lgbm,Regression with a Tabular Concrete Strength Dataset
11692,120655428,32.0,11.783049546301203,0,1,/johandedeyne123456/season3episode9-bayessearchcv-xgbregressor,Regression with a Tabular Concrete Strength Dataset
11693,120757379,341.0,,7,11,/qiaoningchen/concretestrength-s3p9-ml-feature-engineering,Regression with a Tabular Concrete Strength Dataset
11694,121252192,281.0,,0,2,/macklinshanahan/notebook-ep9-rf-xgb-cat,Regression with a Tabular Concrete Strength Dataset
11695,121375898,129.0,,0,3,/alexbostick/xgboost-catboost-concrete-strength,Regression with a Tabular Concrete Strength Dataset
11696,121430683,73.0,,0,0,/shineyourlife/pg-s3e9-2nd,Regression with a Tabular Concrete Strength Dataset
11697,122376471,35.0,,0,5,/omargasmann/playground-s3-e9-35-solution,Regression with a Tabular Concrete Strength Dataset
11698,120841573,273.0,11.81219641710291,2,6,/amrelsayeh/pgs-s3e9-xgboost,Regression with a Tabular Concrete Strength Dataset
11699,120792361,1.0,11.821180501684967,14,70,/ambrosm/pss3e9-eda-which-makes-sense,Regression with a Tabular Concrete Strength Dataset
11700,120564923,72.0,,0,6,/christrandata/eda-xgboost-catboost-lgbm-optuna,Regression with a Tabular Concrete Strength Dataset
11701,121087505,409.0,,2,5,/takahironamatame/playground-series-s3-e9-baseline-model-xgboost,Regression with a Tabular Concrete Strength Dataset
11702,121544939,109.0,,0,5,/ashtcoder/pg-s3-e9-ensemble,Regression with a Tabular Concrete Strength Dataset
11703,120961232,25.0,,1,6,/byronjehrke/pg-s3-e9-starting-models,Regression with a Tabular Concrete Strength Dataset
11704,120960632,78.0,11.795414541629537,1,7,/mnokno/concrete-strength-prediction,Regression with a Tabular Concrete Strength Dataset
11705,121911506,40.0,,0,3,/ryangreiner/s3e9-initial-eda,Regression with a Tabular Concrete Strength Dataset
11706,122057776,45.0,,0,2,/nyagami/predicting-concrete-strength-regression,Regression with a Tabular Concrete Strength Dataset
11707,120894949,492.0,,0,1,/hikarinosensh1/lightgbm-english,Regression with a Tabular Concrete Strength Dataset
11708,120564405,87.0,,0,6,/daltondencklau/ps3-ep9-eda-baseline-models,Regression with a Tabular Concrete Strength Dataset
11709,122027401,184.0,,1,2,/daraghthomas/concrete-stength-with-xg-boost,Regression with a Tabular Concrete Strength Dataset
11710,120734841,112.0,,1,13,/bonniehall/ps3-e9-initial-eda-baseline-modeling,Regression with a Tabular Concrete Strength Dataset
11711,122084853,298.0,,0,4,/deshram/ps-s3-e9-xgb-cgb-lgb-rf-ann,Regression with a Tabular Concrete Strength Dataset
11712,120779545,154.0,,8,16,/abdoulayebalde/ps3e9-eda-catboost-basline-with-11,Regression with a Tabular Concrete Strength Dataset
11713,120899553,33.0,11.812910081992186,8,24,/akioonodera/ps-3-09-lgbm-reg,Regression with a Tabular Concrete Strength Dataset
11714,122024910,178.0,,0,3,/moohamedelsayed/ensemble-training-xgb-catboost-model-eda,Regression with a Tabular Concrete Strength Dataset
11715,120861128,158.0,11.807881284138052,1,8,/docxian/ps-s3-e9-concrete-strength-autogluon-regression,Regression with a Tabular Concrete Strength Dataset
11716,121857641,44.0,,5,20,/demko1/s3e9-using-features-based-on-linearregression,Regression with a Tabular Concrete Strength Dataset
11717,121354655,37.0,11.84168550682188,0,6,/manavd22/x-l-gbm-optuna-eda,Regression with a Tabular Concrete Strength Dataset
11718,122031330,395.0,,0,0,/aliosmankaya/ps3-9-model-blend,Regression with a Tabular Concrete Strength Dataset
11719,120731739,521.0,,0,1,/catadanna/tab-s3-e9,Regression with a Tabular Concrete Strength Dataset
11720,143874611,380.0,,1,9,/loki003/gradientboostingregressor,Regression with a Tabular Concrete Strength Dataset
11721,121719732,248.0,,0,5,/ryotapy/eda-submission-lgb-xgb-cat-cb-score11-8134,Regression with a Tabular Concrete Strength Dataset
11722,121335760,57.0,,0,7,/datascientistsohail/bayesian-optimization-on-csd-se03ep09,Regression with a Tabular Concrete Strength Dataset
11723,121233394,89.0,,1,16,/nancysamuel/pss-3-ep-9-basic-model,Regression with a Tabular Concrete Strength Dataset
11724,122071423,84.0,,0,8,/nikoolaylovyagin/playground-series-regressor,Regression with a Tabular Concrete Strength Dataset
11725,121786396,134.0,11.818207498231038,3,5,/denismunene/concrete-strength-prediction,Regression with a Tabular Concrete Strength Dataset
11726,121295553,241.0,11.874070808526689,0,5,/sonukumar2k19it124/playground-s3e9-xgboost-catboost,Regression with a Tabular Concrete Strength Dataset
11727,121160928,11.0,,1,1,/kenjif/pss3e9-0228-lgbmregressor,Regression with a Tabular Concrete Strength Dataset
11728,121698790,352.0,,0,3,/raihanzaki/playground-series-s3e9,Regression with a Tabular Concrete Strength Dataset
11729,120724067,308.0,,0,3,/hetax17/ep9-model-comparison-w-kfold-cv,Regression with a Tabular Concrete Strength Dataset
11730,121055048,127.0,,0,5,/kavishchaudhary1003/playground-s3-e9,Regression with a Tabular Concrete Strength Dataset
11731,120802210,490.0,,0,1,/vijayr2217019/s03e9,Regression with a Tabular Concrete Strength Dataset
11732,120895711,106.0,11.84846999093547,0,2,/rohithmahadevan/regression-analysis-s3-e9,Regression with a Tabular Concrete Strength Dataset
11733,121877695,453.0,11.825336622584578,2,7,/boyochan/ps-s3-e9-eda-lightgbm-catboost-with-optuna,Regression with a Tabular Concrete Strength Dataset
11734,121563950,69.0,,0,2,/arunpurakkatt/eda-xgb-submission,Regression with a Tabular Concrete Strength Dataset
11735,122032187,95.0,,2,4,/timothylincoln2/s3-e9-ps-macklin-tim,Regression with a Tabular Concrete Strength Dataset
11736,120666588,476.0,11.84054023537266,2,6,/chongjiaxu/concrete-strength,Regression with a Tabular Concrete Strength Dataset
11737,120966913,390.0,11.827609873831127,5,8,/djwerterrichmond/gradient-boosting-regressor,Regression with a Tabular Concrete Strength Dataset
11738,120952970,468.0,12.79603284922157,2,5,/klyushnik/episode-9-fast-start,Regression with a Tabular Concrete Strength Dataset
11739,121943087,80.0,19.034778051637733,0,3,/joon0830/pss3e9-eda-with-chatgpt-ensemble-solution,Regression with a Tabular Concrete Strength Dataset
11740,121420048,424.0,11.903796435856565,0,8,/adityarahul/strength-predictor,Regression with a Tabular Concrete Strength Dataset
11741,121479277,74.0,,1,5,/omkarchoulwar/playground-series-s3e9-eda-and-modelling,Regression with a Tabular Concrete Strength Dataset
11742,120554403,110.0,13.064119439277002,2,5,/gabrielott/quick-eda-baseline-nn,Regression with a Tabular Concrete Strength Dataset
11743,142805431,58.0,11.916401109197546,0,2,/stpeteishii/pss3-ep9-lgbm-with-optuna,Regression with a Tabular Concrete Strength Dataset
11744,121391961,289.0,,0,6,/fadhilmuh/pss3e9-eda-and-feature-engineering,Regression with a Tabular Concrete Strength Dataset
11745,121107861,434.0,,0,0,/georger174/model-searching-automation-with-tabular-data,Regression with a Tabular Concrete Strength Dataset
11746,121363648,494.0,11.859423899496816,0,1,/sahilkumar101/ps3e9,Regression with a Tabular Concrete Strength Dataset
11747,123922111,354.0,,0,0,/ammarlokhandwala10/s3-e9-cement-strength-prediction,Regression with a Tabular Concrete Strength Dataset
11748,123001212,156.0,,26,55,/phongnguyen1/a-framework-for-tabular-regression-e9-8-6,Regression with a Tabular Concrete Strength Dataset
11749,121895888,198.0,,2,2,/oksanakalytenko/playground-s3e9-featuretools-quick-predictions,Regression with a Tabular Concrete Strength Dataset
11750,120752315,291.0,,6,16,/masatakasuzuki/good-but-easy-automl-h2o-s3e9,Regression with a Tabular Concrete Strength Dataset
11751,120614252,143.0,11.845909453768275,3,49,/burhanuddinlatsaheb/s3-e9-eda-optuna-lgbm-xgb,Regression with a Tabular Concrete Strength Dataset
11752,121764067,367.0,12.026798207079036,0,2,/krbharat/benchmark-gradient-boosting,Regression with a Tabular Concrete Strength Dataset
11753,120593524,151.0,,0,8,/foolishboi/ps3e9-eda-basicmodelling,Regression with a Tabular Concrete Strength Dataset
11754,121079328,302.0,11.869884425884887,4,14,/samuraikaggle/s3e9ens-optuna-cb-xb-lb,Regression with a Tabular Concrete Strength Dataset
11755,129123155,166.0,11.82136673130419,0,6,/ranjeetshrivastav/playground-series-s3e9-catboost,Regression with a Tabular Concrete Strength Dataset
11756,121101482,547.0,11.988820741668412,2,5,/scirpus/caementicium,Regression with a Tabular Concrete Strength Dataset
11757,121187523,7.0,,2,5,/oldjerry/boost-fusion-based-on-bayes-optimization,Regression with a Tabular Concrete Strength Dataset
11758,120893168,543.0,11.93624345790576,0,2,/tnghthanh/s3e9-lgbm-optuna-and-tuning-model,Regression with a Tabular Concrete Strength Dataset
11759,121538265,514.0,12.115579610380818,0,11,/gopimali/eda-gb-xgb-cb-lg-bayes-opt,Regression with a Tabular Concrete Strength Dataset
11760,121857554,519.0,,0,2,/alexandrrudinskiy/catboost-optuna,Regression with a Tabular Concrete Strength Dataset
11761,120730016,251.0,,0,2,/hiroshikurokawa/p3s9-lgb-catb-xgb-ensemble,Regression with a Tabular Concrete Strength Dataset
11762,120553442,180.0,,0,4,/gauravduttakiit/pss3e9-lazypredict,Regression with a Tabular Concrete Strength Dataset
11763,120626662,536.0,11.898737148359308,1,5,/tracyporter/play-3-9-keras,Regression with a Tabular Concrete Strength Dataset
11764,122849880,173.0,,0,4,/sofiamatias/playground-s3e9,Regression with a Tabular Concrete Strength Dataset
11765,121337551,584.0,,4,9,/alexandrepetit881234/s3e9-eda-with-2d-kde,Regression with a Tabular Concrete Strength Dataset
11766,120859385,275.0,11.901530346897763,0,0,/swagatobhaskar/cement-strength-pgseries-s3-e9,Regression with a Tabular Concrete Strength Dataset
11767,121775469,388.0,,0,0,/niranjanstudy06/cnn-xgb-lightgbm-gb-optuna-tuning,Regression with a Tabular Concrete Strength Dataset
11768,121407523,473.0,11.931769977489228,0,3,/sudhanshuchaturvedi/playground-series-s3-e9,Regression with a Tabular Concrete Strength Dataset
11769,120808660,526.0,11.934400226949418,2,8,/utkarshgaikwad1994/ps3e9-keras-utkarsh-gaikwad,Regression with a Tabular Concrete Strength Dataset
11770,121488241,592.0,12.466984011297038,0,0,/leesstephanie/playground-s3e9-concrete-strength,Regression with a Tabular Concrete Strength Dataset
11771,120750642,615.0,11.951438771820554,0,3,/andrusha95/ps-s3e9-ipynb,Regression with a Tabular Concrete Strength Dataset
11772,121956327,174.0,,2,7,/jarmos/practice-notebook-ps-s3-e9,Regression with a Tabular Concrete Strength Dataset
11773,120592834,603.0,11.960333656308746,4,7,/fuad0857/playground-s3-e9-with-tensorflow,Regression with a Tabular Concrete Strength Dataset
11774,120682843,616.0,,2,6,/masayakawamata/s3e9-keras,Regression with a Tabular Concrete Strength Dataset
11775,121251449,557.0,11.997965708386168,4,10,/killershoaib/ps-e9-eda-baseline-xgboost,Regression with a Tabular Concrete Strength Dataset
11776,121260944,622.0,12.370718434970906,0,3,/finnsun/notebook6e4348b32a,Regression with a Tabular Concrete Strength Dataset
11777,121040634,594.0,,2,7,/donjoeml/lgbm-vs-catboost-regressor-optuna,Regression with a Tabular Concrete Strength Dataset
11778,121314852,620.0,,0,2,/arjunbasandrai/ps-s3e9,Regression with a Tabular Concrete Strength Dataset
11779,121750330,629.0,,1,1,/k4puneet/learning-with-skorch,Regression with a Tabular Concrete Strength Dataset
11780,120867756,530.0,12.130911103647692,3,6,/prutsaowaprut/s3e9-feature-engineering,Regression with a Tabular Concrete Strength Dataset
11781,121144821,593.0,12.132520845066082,0,2,/rupeshmahanty/playground-series-s3e9,Regression with a Tabular Concrete Strength Dataset
11782,121827871,661.0,12.172528722826222,0,8,/ricardorios/linear-regression,Regression with a Tabular Concrete Strength Dataset
11783,122033850,632.0,12.242834452161125,2,5,/nooruddinqur/pg-s3e9,Regression with a Tabular Concrete Strength Dataset
11784,122033850,632.0,12.242834452161125,2,5,/nooruddinqur/pg-s3e9,Regression with a Tabular Concrete Strength Dataset
11785,121969486,668.0,,0,3,/dellalkhaled/variables-normalization,Regression with a Tabular Concrete Strength Dataset
11786,121822324,642.0,12.418447509288043,1,10,/cv13j0/xgboost-model-optuna-optimization,Regression with a Tabular Concrete Strength Dataset
11787,120842894,663.0,12.454840983935972,0,2,/kandruszek/plotly-xgboost-basic-solution,Regression with a Tabular Concrete Strength Dataset
11788,120654971,690.0,12.974988065295705,0,1,/stefanmayer2006/playground-series-season-3-episode-9,Regression with a Tabular Concrete Strength Dataset
11789,122041001,715.0,11.878045463663153,0,9,/abdokhattab/playground-strength-prediction,Regression with a Tabular Concrete Strength Dataset
11790,122002364,736.0,14.118215457024732,5,22,/yakubsadlil/simple-21-lines-of-linear-regression,Regression with a Tabular Concrete Strength Dataset
11791,122027805,725.0,,0,0,/miseregin/concrete,Regression with a Tabular Concrete Strength Dataset
11792,121885762,729.0,14.127647981971696,0,3,/shreyarjun/notebookb4f18e9ebd,Regression with a Tabular Concrete Strength Dataset
11793,121256801,726.0,,0,0,/eatbeans2/notebook9326a5936d,Regression with a Tabular Concrete Strength Dataset
11794,121360869,750.0,,0,1,/mliammm/fastai-horrid-but-a-submission,Regression with a Tabular Concrete Strength Dataset
11795,121275719,8.0,,2,26,/mattop/playground-series-s3-e10-eda-tsne-pca,Binary Classification with a Tabular Pulsar Dataset
11796,126616387,1.0,,10,47,/seascape/how-to-detect-pulsars-with-gam-1st-place,Binary Classification with a Tabular Pulsar Dataset
11797,122200820,337.0,,8,9,/ashenranaweera/ps3e10-ensemble-model-score-0-03138,Binary Classification with a Tabular Pulsar Dataset
11798,122558994,5.0,,8,18,/pourchot/pygam-for-generalized-additive-model,Binary Classification with a Tabular Pulsar Dataset
11799,122353919,343.0,0.0324446333334768,6,11,/gopimali/pulsar-eda-cat-lgb-xgb-bayes-opt,Binary Classification with a Tabular Pulsar Dataset
11800,122353919,343.0,0.0324446333334768,6,11,/gopimali/pulsar-eda-cat-lgb-xgb-bayes-opt,Binary Classification with a Tabular Pulsar Dataset
11801,122259228,19.0,,7,29,/janmpia/s3-10-visual-eda,Binary Classification with a Tabular Pulsar Dataset
11802,122836182,4.0,,0,8,/manteemike/pgs-s3-e10-pulsars-4th-place-code,Binary Classification with a Tabular Pulsar Dataset
11803,122012909,6.0,,0,3,/grahambroughton/pulsars-umap-tsne,Binary Classification with a Tabular Pulsar Dataset
11804,121618342,17.0,0.0325212090704756,0,7,/omarvivas/cb-tpgs-s3e10-v1,Binary Classification with a Tabular Pulsar Dataset
11805,122809526,7.0,0.03121912790609,3,27,/ambrosm/pss3e10-7-winning-model,Binary Classification with a Tabular Pulsar Dataset
11806,122760776,9.0,0.031228003505,0,2,/jbomitchell/pulsar-boltzmann-ensembler,Binary Classification with a Tabular Pulsar Dataset
11807,122323761,2.0,0.0315007831364216,28,56,/paddykb/ps-s3e10-gam-finger-on-the-pulsarrrrr,Binary Classification with a Tabular Pulsar Dataset
11808,122817408,20.0,0.03230606483698,0,6,/docxian/ps-s3-e10-pulsar-classifier,Binary Classification with a Tabular Pulsar Dataset
11809,122817408,20.0,0.0324174341887056,0,6,/docxian/ps-s3-e10-pulsar-classifier,Binary Classification with a Tabular Pulsar Dataset
11810,122051378,296.0,0.0342377466803644,0,10,/satyaprakashshukl/eda-simple-model,Binary Classification with a Tabular Pulsar Dataset
11811,122334941,56.0,0.0322914671899086,3,5,/anhdangquy/baseline-model,Binary Classification with a Tabular Pulsar Dataset
11812,122355304,322.0,0.0320135353464905,0,7,/andreychubin/pg3e10-catboost-0-03201,Binary Classification with a Tabular Pulsar Dataset
11813,123403769,90.0,0.0322234613581275,4,10,/take5555/ps-season-3-episode-10-xgboost-score-0-03222,Binary Classification with a Tabular Pulsar Dataset
11814,121378312,54.0,0.0321505893735093,8,13,/georgescutelnicu/ps-s3e10-pulsar-classification-catboost,Binary Classification with a Tabular Pulsar Dataset
11815,122401653,200.0,,1,13,/jimgruman/season3-episode10,Binary Classification with a Tabular Pulsar Dataset
11816,122312026,324.0,0.0336027508957288,3,19,/matthewjansen/pulsar-detection-tf-df-baseline,Binary Classification with a Tabular Pulsar Dataset
11817,121888753,157.0,0.0340721322375275,9,7,/syerramilli/ps3e10-xgboost-hyperopt,Binary Classification with a Tabular Pulsar Dataset
11818,121435193,149.0,,1,1,/tremendous1192/ps-s3-ep-10-02,Binary Classification with a Tabular Pulsar Dataset
11819,122784958,414.0,,0,3,/finnsun/play-groupd-3-10,Binary Classification with a Tabular Pulsar Dataset
11820,121527837,258.0,0.0329918379959039,0,1,/gagan1234444/catboostclassifier-score-0-03299,Binary Classification with a Tabular Pulsar Dataset
11821,121527837,258.0,0.0329918379959039,0,1,/gagan1234444/catboostclassifier-score-0-03299,Binary Classification with a Tabular Pulsar Dataset
11822,122217381,153.0,0.0561992064926516,16,24,/jrreda/s03e10-pulsar-classification,Binary Classification with a Tabular Pulsar Dataset
11823,122519620,192.0,,2,7,/ksh9567/catboost-0-03206-very-simple,Binary Classification with a Tabular Pulsar Dataset
11824,122622695,156.0,,0,12,/siddharthkumarsah/s3e10-playground-solution,Binary Classification with a Tabular Pulsar Dataset
11825,122827645,206.0,,0,4,/magnussesodia/ps-s3e10-xgb-catboost-isotonic-regression,Binary Classification with a Tabular Pulsar Dataset
11826,122805640,113.0,,1,3,/kavishchaudhary1003/playground-s3-e10-optuna-xgb-lgbm-catboost,Binary Classification with a Tabular Pulsar Dataset
11827,121817486,195.0,,14,27,/tengluoxiyue/update-0-03207-catboost-with-k-fold,Binary Classification with a Tabular Pulsar Dataset
11828,122804588,319.0,0.032357785479887,16,54,/sujaykapadnis/s3e10-eda,Binary Classification with a Tabular Pulsar Dataset
11829,122615667,294.0,0.0320880090591822,1,7,/lizhecheng/s3e10-catboost-pulsar-classification,Binary Classification with a Tabular Pulsar Dataset
11830,121286902,251.0,,5,12,/gauravduttakiit/pss3e10-autoviz,Binary Classification with a Tabular Pulsar Dataset
11831,121832453,178.0,,17,33,/ryotapy/eda-submission-xgboost-lightgbm-score-0-03212,Binary Classification with a Tabular Pulsar Dataset
11832,122827017,233.0,0.0330377301592542,0,5,/inaciobr/ps-s03e10-pulsar-classification-baseline,Binary Classification with a Tabular Pulsar Dataset
11833,121850079,232.0,,3,9,/omkarchoulwar/playground-series-s3e10-eda-and-modelling,Binary Classification with a Tabular Pulsar Dataset
11834,122677614,110.0,0.0325663183415513,4,7,/japkeeratsingh/beginner-xgboost-optuna-stratifiedkfold,Binary Classification with a Tabular Pulsar Dataset
11835,121367489,211.0,0.0332782504769119,3,6,/ransakaravihara/quick-model-with-probability-calibration,Binary Classification with a Tabular Pulsar Dataset
11836,122314077,521.0,0.0408322387140924,0,4,/stpeteishii/pss3-ep10-visualize-importance,Binary Classification with a Tabular Pulsar Dataset
11837,122642061,181.0,0.0323181463027056,1,6,/krbharat/ps3-e10-eda-ensemble-model,Binary Classification with a Tabular Pulsar Dataset
11838,121557709,210.0,,3,6,/rustam1488/s3e10-clf-ens-optuna-lgbm-cb,Binary Classification with a Tabular Pulsar Dataset
11839,123662788,176.0,,4,18,/nancysamuel/pss-3-ep-10,Binary Classification with a Tabular Pulsar Dataset
11840,121618856,290.0,0.032478694906253,3,16,/akioonodera/ps-3-10-lgbm-bin,Binary Classification with a Tabular Pulsar Dataset
11841,122587277,263.0,0.0325671610478617,0,2,/ashtcoder/pg-s3-e10,Binary Classification with a Tabular Pulsar Dataset
11842,121399995,106.0,0.0343455002035732,0,6,/islandshuwang/playground-s3e10-simple-dnn-by-keras-0-03434,Binary Classification with a Tabular Pulsar Dataset
11843,121818962,375.0,,3,6,/donjoeml/catboost-pairwise-outlier-detection,Binary Classification with a Tabular Pulsar Dataset
11844,121552295,275.0,0.0340911029416942,0,1,/otsukitoru/tutorials-in-japanese,Binary Classification with a Tabular Pulsar Dataset
11845,122687385,237.0,0.2647722624749083,0,3,/datascientistsohail/lgbclassifier-bayesian-se03ep10,Binary Classification with a Tabular Pulsar Dataset
11846,121520812,222.0,0.0326056482767051,0,4,/sonukumar2k19it124/playground-s3e10-xgb-cat-and-lgm,Binary Classification with a Tabular Pulsar Dataset
11847,122172757,196.0,0.0326186469521853,0,0,/cristobalchavez/notebook53fffa08ce,Binary Classification with a Tabular Pulsar Dataset
11848,122463147,135.0,0.0654170382780596,8,15,/jarmos/quick-simple-eda-modelling,Binary Classification with a Tabular Pulsar Dataset
11849,121697725,279.0,0.0341339867403205,1,1,/catadanna/tab-s3e10,Binary Classification with a Tabular Pulsar Dataset
11850,122679729,315.0,0.0345683835880771,0,3,/mnokno/pulsar-classification-for-class-prediction,Binary Classification with a Tabular Pulsar Dataset
11851,122751359,331.0,0.034221329599961,0,6,/aonzahaha/ps-ss3-ep10-xgboost-optuna,Binary Classification with a Tabular Pulsar Dataset
11852,121292447,175.0,0.0329721793315931,1,5,/sfktrkl/playground-series-season-3-episode-10,Binary Classification with a Tabular Pulsar Dataset
11853,121292447,175.0,0.033027606509976,1,5,/sfktrkl/playground-series-season-3-episode-10,Binary Classification with a Tabular Pulsar Dataset
11854,121548589,489.0,0.0326763484242119,1,8,/adityarahul/pgs03e10,Binary Classification with a Tabular Pulsar Dataset
11855,122377619,171.0,,0,2,/hyunyoung/binary-classification-with-deep-learning,Binary Classification with a Tabular Pulsar Dataset
11856,122349125,325.0,,0,2,/iamnotashutosh/pg-s3-e10-eda,Binary Classification with a Tabular Pulsar Dataset
11857,122825859,277.0,0.0330043919021268,1,8,/pranavkannepalli/s3e10-ensemble,Binary Classification with a Tabular Pulsar Dataset
11858,121889644,177.0,,1,2,/testanother/tensorflow-submission,Binary Classification with a Tabular Pulsar Dataset
11859,146561735,399.0,,0,6,/loki003/neuralnets,Binary Classification with a Tabular Pulsar Dataset
11860,122016992,284.0,0.4208304786997038,0,0,/lowzhao/playground-series-s3e10-nn,Binary Classification with a Tabular Pulsar Dataset
11861,122010801,382.0,,0,4,/alexkonse/ps3e10-cat-ensemble-xgb-0-032,Binary Classification with a Tabular Pulsar Dataset
11862,121289719,272.0,0.0342878076080838,0,7,/masatakasuzuki/simple-eda-lgbm-benchmark,Binary Classification with a Tabular Pulsar Dataset
11863,122250255,358.0,0.033600900120396,7,14,/joehardin369/pulsar-classification-gam-in-r,Binary Classification with a Tabular Pulsar Dataset
11864,122225082,463.0,0.0331543942905731,0,5,/denismunene/imabalanced-data-classification-lightgbm,Binary Classification with a Tabular Pulsar Dataset
11865,122541214,446.0,,1,8,/kattat/pulsar-classification-with-tf-df,Binary Classification with a Tabular Pulsar Dataset
11866,122765975,447.0,,0,5,/edwardhuangtw/ps-s3e10-2023,Binary Classification with a Tabular Pulsar Dataset
11867,122444167,377.0,,2,5,/seholeee/automl-mljar,Binary Classification with a Tabular Pulsar Dataset
11868,122096485,416.0,0.0339699886617447,7,19,/amarloni/pgs3e10,Binary Classification with a Tabular Pulsar Dataset
11869,121340253,424.0,0.0339045675944495,0,5,/samuraikaggle/s3e10ens-optuna-cb-xb-lb,Binary Classification with a Tabular Pulsar Dataset
11870,122248666,413.0,0.034538649039441,3,7,/sharvalishinde/pss3e10-xgb-stratifiedkfold,Binary Classification with a Tabular Pulsar Dataset
11871,121293492,411.0,5.103726840457223,2,7,/masayakawamata/s3e10-keras,Binary Classification with a Tabular Pulsar Dataset
11872,121692078,428.0,0.0345813796154648,0,7,/sahilkumar101/ps3-e10-nn,Binary Classification with a Tabular Pulsar Dataset
11873,122317901,515.0,0.0342325746365965,0,0,/averma111/ps-s3e10,Binary Classification with a Tabular Pulsar Dataset
11874,122310112,425.0,,3,14,/warcoder/tf-decision-forest,Binary Classification with a Tabular Pulsar Dataset
11875,121529787,467.0,0.034999303584347,0,1,/utkarshgaikwad1994/ps3e10-keras-utkarsh-gaikwad,Binary Classification with a Tabular Pulsar Dataset
11876,121520289,491.0,0.035669706928105,0,7,/sanandachowdhury/ps-s3-ep10-eda-modeling,Binary Classification with a Tabular Pulsar Dataset
11877,121520289,491.0,0.035669706928105,0,7,/sanandachowdhury/ps-s3-ep10-eda-modeling,Binary Classification with a Tabular Pulsar Dataset
11878,124959861,477.0,,6,23,/iqbalsyahakbar/ps3e10-first-attempt-at-playground-competition,Binary Classification with a Tabular Pulsar Dataset
11879,122810546,516.0,0.0386764098421015,1,3,/nooruddinqur/pgs03e10,Binary Classification with a Tabular Pulsar Dataset
11880,134099459,531.0,,40,91,/javohirtoshqorgonov/pulsar-stars-binary-classification-research,Binary Classification with a Tabular Pulsar Dataset
11881,122717555,558.0,0.0407632193195048,0,1,/changjae0/logistic-and-tree-classification,Binary Classification with a Tabular Pulsar Dataset
11882,122755615,561.0,0.0425312970710293,0,2,/sofiamatias/playground-s3e10,Binary Classification with a Tabular Pulsar Dataset
11883,122446943,573.0,0.0568638583057284,4,9,/charunumesh/ps-s3e10-ensemble-smote,Binary Classification with a Tabular Pulsar Dataset
11884,121355091,564.0,,5,12,/eshraqsaeed/the-dead-star,Binary Classification with a Tabular Pulsar Dataset
11885,122721831,549.0,0.0541049889505093,0,9,/abhinavmangalore/s3e10-playground-pulsar-detection,Binary Classification with a Tabular Pulsar Dataset
11886,122641117,553.0,,4,20,/nishantborkar/play-eda-logistic-regression,Binary Classification with a Tabular Pulsar Dataset
11887,121351278,570.0,0.0464720581711185,0,3,/tracyporter/play-3-10-keras-tf,Binary Classification with a Tabular Pulsar Dataset
11888,122823134,560.0,0.0508353551604931,0,6,/barbagrande007/bbg007-s3e10-pulsars,Binary Classification with a Tabular Pulsar Dataset
11889,122043054,595.0,,0,3,/tylerchi/pycaret-eda-s3e10,Binary Classification with a Tabular Pulsar Dataset
11890,122755061,597.0,,3,7,/ndeperrois/sklearn-for-newbies-logistic-reg-random-f-etc,Binary Classification with a Tabular Pulsar Dataset
11891,122489477,612.0,0.1613509275767838,1,11,/klyushnik/episode-10,Binary Classification with a Tabular Pulsar Dataset
11892,121637090,618.0,0.1736311368489426,0,1,/ashishanton/xgboost-optuna-pulsar-classification,Binary Classification with a Tabular Pulsar Dataset
11893,122495914,621.0,0.4517070705688394,0,0,/anchaliyayash/plaground-seriess3e10,Binary Classification with a Tabular Pulsar Dataset
11894,121572002,647.0,,0,0,/eliadf/playground-s3e10-eda-baseline,Binary Classification with a Tabular Pulsar Dataset
11895,121332724,651.0,,8,20,/ahmadalijamali/analysis-and-prediction-playground-series-s3e10,Binary Classification with a Tabular Pulsar Dataset
11896,123498443,672.0,0.0346984826403172,0,2,/okoloboga/pgs-s03e10-densenn,Binary Classification with a Tabular Pulsar Dataset
11897,122524651,716.0,,2,10,/riyaelizashaju/beginner-catboost-xgboost-lgboost,Binary Classification with a Tabular Pulsar Dataset
11898,122794382,696.0,0.3261100917338806,0,3,/muhriddinmalik/playgorund-series-competition-notebook,Binary Classification with a Tabular Pulsar Dataset
11899,122358677,749.0,0.3944155255768472,0,9,/dellalkhaled/cart-algorithm-for-binary-classification,Binary Classification with a Tabular Pulsar Dataset
11900,121583312,738.0,,0,9,/cihangiryiit/svm-classifier-about-star-class,Binary Classification with a Tabular Pulsar Dataset
11901,124249958,755.0,0.3195005647658882,0,2,/itspavansatish/auto-ml-h20,Binary Classification with a Tabular Pulsar Dataset
11902,124249958,755.0,0.3195005647658882,0,2,/itspavansatish/auto-ml-h20,Binary Classification with a Tabular Pulsar Dataset
11903,124249958,755.0,0.3195005647658882,0,2,/itspavansatish/auto-ml-h20,Binary Classification with a Tabular Pulsar Dataset
11904,122704122,770.0,0.5304593886498778,0,1,/jankuper192/playground-3-10,Binary Classification with a Tabular Pulsar Dataset
11905,122270453,783.0,0.6931471805600774,0,2,/saniyatlamim007/ps-3-10-w-xgbregressor,Binary Classification with a Tabular Pulsar Dataset
11906,121347500,790.0,,0,10,/chandrashekhargt/pulsar-star-and-basic-eda,Binary Classification with a Tabular Pulsar Dataset
11907,130741882,3.0,0.8473593479461454,0,0,/mariotsaberlin/bc23-s225-e,BirdCLEF 2023
11908,130832819,1.0,0.8439159661503903,0,1,/vladimirsydor/bird-clef-2023-inference-v1,BirdCLEF 2023
11909,129505182,2.0,,0,11,/honglihang/openvino-is-all-you-need,BirdCLEF 2023
11910,131053721,4.0,0.8401959061872805,0,7,/atsunorifujita/4th-place-solution-inference-kernel,BirdCLEF 2023
11911,131053721,4.0,0.8401959061872805,0,7,/atsunorifujita/4th-place-solution-inference-kernel,BirdCLEF 2023
11912,121796742,9.0,,5,45,/nischaydnk/split-creating-melspecs-stage-1,BirdCLEF 2023
11913,123300717,19.0,0.8113616675414781,6,32,/myso1987/birdclef2023-sound-event-visualisations,BirdCLEF 2023
11914,126347392,22.0,,1,2,/leehann/split-creating-melspecs-stage-1,BirdCLEF 2023
11915,121868759,107.0,0.7726382200924606,0,10,/hideyukizushi/bird-inf-torch-timm-tf-efficientnetv2-s-fold3-5,BirdCLEF 2023
11916,124228675,86.0,0.8023729081833681,2,3,/domdejonge/remove-lowest-probability-predictions,BirdCLEF 2023
11917,125190806,95.0,,0,3,/robbynevels/eda-birdclef-2023,BirdCLEF 2023
11918,122942005,196.0,,9,12,/gabrielvinicius/speedup-spectogram-with-rapids,BirdCLEF 2023
11919,126535518,511.0,,0,0,/hypnotu/techtutors-predicting-birds-with-kaggle-models,BirdCLEF 2023
11920,121682642,191.0,,0,12,/hinepo/visualizing-mel-spectrograms-and-noise-reduce,BirdCLEF 2023
11921,123024886,351.0,,3,16,/oumouhouh/audio-feature-extraction,BirdCLEF 2023
11922,122891076,357.0,0.784262903910781,0,1,/muhammadahmedansari/birdclef23-effnet-fsr-cutmixup-infer,BirdCLEF 2023
11923,122879962,414.0,,3,45,/asimple/eda-birdclef,BirdCLEF 2023
11924,123641155,375.0,,0,0,/ineedacat/baseline-inference,BirdCLEF 2023
11925,122481005,404.0,,2,8,/venkatkumar001/day3-eda-audioanalysis,BirdCLEF 2023
11926,126493867,135.0,,2,18,/gpreda/birdclef-2023-metadata-and-sound-data-exploration,BirdCLEF 2023
11927,129214480,245.0,0.802373863437497,1,8,/chelseade/birdclef23-pretraining-is-all-you-need-infer,BirdCLEF 2023
11928,129605855,262.0,,0,0,/rubymyheart/notedta-2,BirdCLEF 2023
11929,121700985,308.0,,0,5,/miltiadesgeneral/inferringbirdsml,BirdCLEF 2023
11930,123331699,584.0,,0,6,/ollypowell/birdclef23-audio-to-numpy,BirdCLEF 2023
11931,122813181,155.0,,0,3,/tasmim/efficientnet-spectrogram-specaugment-skf-training,BirdCLEF 2023
11932,122235063,169.0,0.7170482831140387,0,23,/eishkaran/birdclef-competition-1,BirdCLEF 2023
11933,122235063,169.0,0.7170482831140387,0,23,/eishkaran/birdclef-competition-1,BirdCLEF 2023
11934,121387512,532.0,,2,22,/imeintanis/birdclef-interactive-spectrogram-viewer,BirdCLEF 2023
11935,121901989,138.0,,0,18,/morodertobias/bc23-data-inspection,BirdCLEF 2023
11936,123776052,721.0,,0,10,/lhanhsin/birdclef-2023-identifying-duplicates,BirdCLEF 2023
11937,126437859,573.0,0.7213108432728675,0,0,/lyz2002/baseline0421,BirdCLEF 2023
11938,126444357,563.0,,0,3,/pelegshilo/finding-mean-and-std-for-standardization,BirdCLEF 2023
11939,122634480,579.0,,1,8,/vpkprasanna/eda-visuvalizations-birdclef-2023,BirdCLEF 2023
11940,122473632,604.0,,0,10,/sabahesaraki/birdclef-2023-challenge,BirdCLEF 2023
11941,123335758,616.0,,0,0,/raniahelmy/birdclef-2023-eda,BirdCLEF 2023
11942,125900255,626.0,,2,12,/iamleonie/what-impacts-your-cpu-inference-time,BirdCLEF 2023
11943,126959379,623.0,,2,1,/diegomachado/splitting-audios,BirdCLEF 2023
11944,127689786,639.0,,0,0,/lucafaccin/create-images-from-audio-birdclef-2023,BirdCLEF 2023
11945,125229187,666.0,,0,8,/neurodr/eda-metadata-google-model-on-training-set,BirdCLEF 2023
11946,128401165,696.0,0.7784585936393943,0,8,/sonu123/birdclef-21-2nd-place-model-submit,BirdCLEF 2023
11947,124197321,673.0,,0,5,/mohib94/birdclef2023-overview,BirdCLEF 2023
11948,127047158,729.0,,4,4,/rounakkumbhakar/birdclef23-training,BirdCLEF 2023
11949,127385661,731.0,,0,1,/akumar6/birdclef23-dataprep-macm1,BirdCLEF 2023
11950,129116464,768.0,,0,0,/sprestrelski/birdclef23-uniform-no-call-sound-chunks,BirdCLEF 2023
11951,124180807,783.0,,0,1,/seydifaye/birddatsettotfrecords,BirdCLEF 2023
11952,123619383,804.0,,2,3,/jonasotto/birbs,BirdCLEF 2023
11953,121522588,805.0,,5,32,/bibanh/lb-0-72-resnet34-melspectrogram-stage-1-training,BirdCLEF 2023
11954,124058135,803.0,,0,2,/aymentabib/onset-detection,BirdCLEF 2023
11955,127328980,813.0,,0,0,/sharmisthapaul/r1006-birdclef2023,BirdCLEF 2023
11956,121389850,831.0,0.721179877091128,0,9,/eslamfouad/birdclef-2023-mlm-predictions,BirdCLEF 2023
11957,121416577,841.0,,0,6,/nivk0906/inferring-birds-with-kaggle-models-01f7a4,BirdCLEF 2023
11958,122232058,890.0,,0,2,/kuntalpal/bird-clef-baseline,BirdCLEF 2023
11959,124141901,898.0,,0,9,/lonnieqin/bird-species-classification-with-efficientnet,BirdCLEF 2023
11960,122595224,919.0,0.721179877091128,0,1,/nilimajain/inferring-birds-with-kaggle-models-99ee3d,BirdCLEF 2023
11961,123738766,958.0,,0,5,/lukalafaye/inferring-birds-with-kaggle-models,BirdCLEF 2023
11962,124567426,976.0,0.721179877091128,0,3,/aniketsharma00411/inferring-birds-with-kaggle-models,BirdCLEF 2023
11963,125476368,980.0,,0,2,/jocelyndumlao/birdclef-2023-melspectrogram,BirdCLEF 2023
11964,125720352,983.0,,0,0,/frontfrend/submission,BirdCLEF 2023
11965,126253870,1013.0,0.721179877091128,0,1,/jiaqingfu2000/inferring-birds-with-kaggle-models,BirdCLEF 2023
11966,128871347,1071.0,0.721179877091128,0,1,/sachinkumar413/inferring-birds,BirdCLEF 2023
11967,130823691,1102.0,0.721179877091128,0,0,/kot8egemot/bird2023,BirdCLEF 2023
11968,129256554,1081.0,0.7183880420759023,0,0,/nehalksahukar/birdclef-23,BirdCLEF 2023
11969,125228318,1154.0,,0,0,/rajeshradhakrishnan/submission-scoring-error-birdclef2023,BirdCLEF 2023
11970,121370510,1166.0,,2,17,/jirkaborovec/birdclef-convert-spectrograms-reduce-noise,BirdCLEF 2023
11971,122169796,1171.0,,1,11,/mayukh18/birdclef-eda-quickstart-sound-on,BirdCLEF 2023
11972,130277314,1182.0,0.7170482831140387,0,2,/mitanshuchakrawarty/bird-sound-classification,BirdCLEF 2023
11973,128996684,1164.0,,0,1,/markuslonss/notebooka2b27ac1ec,BirdCLEF 2023
11974,146047978,1189.0,0.7170482831140387,0,2,/rohitgunti/inferring-birds-with-kaggle-models,BirdCLEF 2023
11975,132425310,5.0,0.4897155291492297,0,4,/adityakumarsinha/wavenet-subm-focal-v1,Parkinson's Freezing of Gait Prediction
11976,132868028,3.0,0.4829335613324559,0,1,/stochoshi/fork-of-walk3,Parkinson's Freezing of Gait Prediction
11977,137663762,4.0,0.4729181765290556,0,2,/zinxira/parkinson-fog-pred-4th-place-submission-notebook,Parkinson's Freezing of Gait Prediction
11978,123101559,29.0,0.2424272087655633,3,35,/xzj19013742/groupkfold-cross-validation-tsflex,Parkinson's Freezing of Gait Prediction
11979,128424890,42.0,,0,10,/hiroakifukuse/pfogp-correct-defog-data-discrepancies,Parkinson's Freezing of Gait Prediction
11980,132606289,21.0,0.4036710370677194,0,4,/takanashihumbert/gait-single-models-inference,Parkinson's Freezing of Gait Prediction
11981,127959114,359.0,,10,38,/averkovanika/parkinson-s-fog-basic-eda,Parkinson's Freezing of Gait Prediction
11982,130292838,161.0,,2,4,/tinatuna/polars-parkinson-s-fog-simple-lightgbm,Parkinson's Freezing of Gait Prediction
11983,122477052,9.0,,1,9,/quincyqiang/read-train-files-faster,Parkinson's Freezing of Gait Prediction
11984,131530366,70.0,0.2896946691800996,2,12,/allenwpr/gait-prediction,Parkinson's Freezing of Gait Prediction
11985,132872590,99.0,,0,12,/fritzcremer/fog-shakeup,Parkinson's Freezing of Gait Prediction
11986,130963882,11.0,,0,0,/ismailgadzhiev/createdataset,Parkinson's Freezing of Gait Prediction
11987,122144951,639.0,0.1902677548634752,2,30,/ammarnassanalhajali/freezing-of-gait-prediction,Parkinson's Freezing of Gait Prediction
11988,122793508,205.0,,0,7,/avivlevi815/metadata-eda,Parkinson's Freezing of Gait Prediction
11989,131110667,79.0,0.270515547489138,0,2,/christianjschneider/fog-training-lgb,Parkinson's Freezing of Gait Prediction
11990,129468851,356.0,0.1722245326964402,33,31,/gokifujiya/pd-fog-prediction-baseline-by-logistic-regression,Parkinson's Freezing of Gait Prediction
11991,123918703,420.0,0.2780345712012713,7,45,/bernardbr/lgbm-with-hyperparams-and-tsflex-lb-0-28,Parkinson's Freezing of Gait Prediction
11992,126604903,662.0,0.2836082301818589,0,71,/nickcgray/gait-prediction,Parkinson's Freezing of Gait Prediction
11993,121849191,669.0,,2,23,/docxian/parkinson-fog-acceleration-visualization,Parkinson's Freezing of Gait Prediction
11994,131962052,353.0,0.1069530422153583,0,0,/teunpeeters/pytorch-lstm-fog-detection,Parkinson's Freezing of Gait Prediction
11995,125685476,459.0,0.3021973411765191,0,6,/jamilahsan/gait-prediction,Parkinson's Freezing of Gait Prediction
11996,125685476,459.0,0.3021973411765191,0,6,/jamilahsan/gait-prediction,Parkinson's Freezing of Gait Prediction
11997,126076909,461.0,,8,25,/dataanalojisan/parkinson-s-fog-eda,Parkinson's Freezing of Gait Prediction
11998,127534856,476.0,,6,29,/dinowun/eda-simplified-parkinson-s-fog-prediction,Parkinson's Freezing of Gait Prediction
11999,126070122,1202.0,,0,5,/josepharivera/parkinson-s-fog-ml-comp-rivera,Parkinson's Freezing of Gait Prediction
12000,126037626,480.0,,0,1,/aparnaburhade/parkinson-s-freezing-gait,Parkinson's Freezing of Gait Prediction
12001,131636337,489.0,0.1069499990356768,0,1,/soonmooksimonlee/slee-hmm-under1,Parkinson's Freezing of Gait Prediction
12002,122179149,496.0,,6,31,/benjenkins96/exploratory-data-statistical-analysis,Parkinson's Freezing of Gait Prediction
12003,126341674,498.0,0.3021973411765191,0,6,/zhaoningericwang/cap5610-competition,Parkinson's Freezing of Gait Prediction
12004,132882832,625.0,,0,4,/abrachan/exploratory-data-analysis,Parkinson's Freezing of Gait Prediction
12005,132768627,839.0,0.2856394082064144,0,0,/kabikabi0208/gait-prediction,Parkinson's Freezing of Gait Prediction
12006,126253496,202.0,,0,3,/albertoannoni/parallel-data-loading,Parkinson's Freezing of Gait Prediction
12007,128277542,543.0,0.2346705027716923,0,0,/sx66998756/time-series-tsflex,Parkinson's Freezing of Gait Prediction
12008,128652414,376.0,,2,16,/inabower/eda-parkinson-s-fog-overview-jpn,Parkinson's Freezing of Gait Prediction
12009,132728623,619.0,0.1078173446173631,0,2,/vladiluzjr/parkinson-s-fog-eda-and-model-submission,Parkinson's Freezing of Gait Prediction
12010,124654384,780.0,0.1069525811520628,9,24,/henriupton/pytorch-lstm-fog-detection,Parkinson's Freezing of Gait Prediction
12011,127138124,791.0,,0,2,/kcliu2000/check-fog,Parkinson's Freezing of Gait Prediction
12012,127564579,199.0,0.1069525811520628,0,2,/pitpkag/notebookc6f0fe3990,Parkinson's Freezing of Gait Prediction
12013,121934050,820.0,,0,12,/dongkeunbak/eda-feature-engineering-summary-of-domain-info,Parkinson's Freezing of Gait Prediction
12014,132808746,679.0,0.2710834698959412,0,0,/cosiiine/gait-prediction-f5ad09,Parkinson's Freezing of Gait Prediction
12015,123887651,952.0,,0,4,/dubito/eda-by-momo,Parkinson's Freezing of Gait Prediction
12016,132713939,312.0,0.2844321258560159,0,1,/gpreda/gait-prediction-v16-0-31,Parkinson's Freezing of Gait Prediction
12017,132649617,892.0,0.2844321258560159,0,6,/mahmudds/freezing-of-gait-prediction,Parkinson's Freezing of Gait Prediction
12018,123398676,335.0,,0,4,/neharawat/parkinson-fog-eda-v1,Parkinson's Freezing of Gait Prediction
12019,127256131,1338.0,,0,2,/trangnguyenpsu/learningpython,Parkinson's Freezing of Gait Prediction
12020,126073953,975.0,0.2478925865491711,0,1,/shuddhendumishra/parkinson-s,Parkinson's Freezing of Gait Prediction
12021,126067649,675.0,0.2154141708511347,4,22,/tanreinama/starter-kit-ridgeregressor-baseline,Parkinson's Freezing of Gait Prediction
12022,128138361,191.0,,0,0,/lindseydebeer/mlip-lindsey-lgbm-baseline,Parkinson's Freezing of Gait Prediction
12023,128138361,191.0,,0,0,/lindseydebeer/mlip-lindsey-lgbm-baseline,Parkinson's Freezing of Gait Prediction
12024,130789741,304.0,0.2484523577088242,5,2,/ahmedabdelhamied2501/using-calibrated-lgmbclassifier,Parkinson's Freezing of Gait Prediction
12025,126075772,1015.0,0.1290167089142714,1,6,/ashtonfrias/gait-prediction,Parkinson's Freezing of Gait Prediction
12026,122261256,1047.0,0.237102968491235,12,77,/jeroenvdd/time-series-tsflex,Parkinson's Freezing of Gait Prediction
12027,123890652,1153.0,0.2042212777918579,3,29,/jazivxt/familiar-solvs,Parkinson's Freezing of Gait Prediction
12028,123480253,1118.0,,0,2,/rishabsinghh/gait-lgbm-eda-feature-eng-modelling,Parkinson's Freezing of Gait Prediction
12029,131954897,1211.0,0.1838916448379662,0,0,/thilanidelpagoda/pd-fog-xgb-td,Parkinson's Freezing of Gait Prediction
12030,124213568,1157.0,0.1069525811520628,0,3,/sireesh/fog-lab1,Parkinson's Freezing of Gait Prediction
12031,127546015,1079.0,,4,27,/viji1609/fog-prediction-data-visualization-tfdv,Parkinson's Freezing of Gait Prediction
12032,126451798,1107.0,,0,1,/vickyhaney/notype-data-visualization,Parkinson's Freezing of Gait Prediction
12033,121716020,1166.0,,1,7,/kretes/eda-distributions-of-acc-w-r-t-event-type,Parkinson's Freezing of Gait Prediction
12034,125952141,1174.0,0.1611394885884946,0,1,/roncam/fog-fog,Parkinson's Freezing of Gait Prediction
12035,125926084,1226.0,0.1069525811520628,0,2,/cherrytomatech/dummy-zero-submission-for-kaggle-beginners,Parkinson's Freezing of Gait Prediction
12036,126415560,1133.0,0.1520261348447554,0,1,/mahadali/gait-prediction,Parkinson's Freezing of Gait Prediction
12037,125843875,1143.0,,0,0,/ashlynncrisp/notebookad312fa2f1,Parkinson's Freezing of Gait Prediction
12038,126603044,1203.0,,0,0,/josephriv1/pd-fog-ml-class-xgboost-rivera,Parkinson's Freezing of Gait Prediction
12039,126556953,1187.0,,2,27,/lbsbmsu/parkinson-s-freezing-r,Parkinson's Freezing of Gait Prediction
12040,131042018,1141.0,0.1069525811520628,0,1,/venaabdallah/lstm-gait-classifier,Parkinson's Freezing of Gait Prediction
12041,125716989,1222.0,0.1069525811520628,0,1,/travismerrill/rtmsubmission,Parkinson's Freezing of Gait Prediction
12042,131558481,1193.0,0.1457533469008979,2,18,/alexanderskachkov/fog-f-for-forest,Parkinson's Freezing of Gait Prediction
12043,126076731,1248.0,,0,1,/stephstoll/ss-parkinson-s-freezing-of-gait-prediction,Parkinson's Freezing of Gait Prediction
12044,132076959,1208.0,,0,0,/nkl990/notebook1ec376a28f,Parkinson's Freezing of Gait Prediction
12045,132816586,1232.0,0.1420702169486191,0,0,/cameronpresley/parkinsons-fog-eda-and-rf-classifier-prediction,Parkinson's Freezing of Gait Prediction
12046,135511096,1227.0,,0,1,/abhhom/defog-ensemble-data-train,Parkinson's Freezing of Gait Prediction
12047,128613776,1240.0,,0,0,/urizlotkin/parkinson-fog,Parkinson's Freezing of Gait Prediction
12048,126066030,1246.0,0.1168250933275756,0,1,/zacharypainter5/painter-ml-comp,Parkinson's Freezing of Gait Prediction
12049,141109699,1213.0,,3,20,/dishaasinghi/fog-prediction,Parkinson's Freezing of Gait Prediction
12050,126602826,1288.0,,0,2,/ajax96/fog-challenge,Parkinson's Freezing of Gait Prediction
12051,126213113,1375.0,0.1041765743994613,0,1,/bstricks/notebook6ad087f10b,Parkinson's Freezing of Gait Prediction
12052,126070955,1282.0,0.1058263715659159,0,1,/briansss/notebookec37cdb5ea,Parkinson's Freezing of Gait Prediction
12053,132147861,1290.0,0.1103012245219216,1,7,/ceyhunsahin/eda-hypotesis-tests-and-optuna,Parkinson's Freezing of Gait Prediction
12054,132147861,1290.0,,1,7,/ceyhunsahin/eda-hypotesis-tests-and-optuna,Parkinson's Freezing of Gait Prediction
12055,132147861,1290.0,,1,7,/ceyhunsahin/eda-hypotesis-tests-and-optuna,Parkinson's Freezing of Gait Prediction
12056,132147861,1290.0,0.1088680855487845,1,7,/ceyhunsahin/eda-hypotesis-tests-and-optuna,Parkinson's Freezing of Gait Prediction
12057,130537982,1301.0,,0,0,/kseniaslivkina/notebook1127797ef2,Parkinson's Freezing of Gait Prediction
12058,121642292,1276.0,,0,12,/ghrangel/read-data-and-merge,Parkinson's Freezing of Gait Prediction
12059,133109135,1279.0,,0,4,/evgeniidvornikov/catboost-vs-lightgbm-vs-xgboost,Parkinson's Freezing of Gait Prediction
12060,136754530,1296.0,,0,2,/rohitdileep/fork-of-freezing-of-gait-lgbm,Parkinson's Freezing of Gait Prediction
12061,136754530,1296.0,,0,2,/rohitdileep/fork-of-freezing-of-gait-lgbm,Parkinson's Freezing of Gait Prediction
12062,126356049,1281.0,0.1069525811520628,0,3,/mathewsarti/parkinson-fog-prediction,Parkinson's Freezing of Gait Prediction
12063,126175308,1265.0,,0,3,/noam1977/simple-test,Parkinson's Freezing of Gait Prediction
12064,122017720,1359.0,,0,3,/averma111/simplified-parkinson-s-fog-prediction-beta,Parkinson's Freezing of Gait Prediction
12065,126467736,1270.0,0.106935611321955,0,1,/gabys1/notebook6c12e6fe9b,Parkinson's Freezing of Gait Prediction
12066,127892903,1298.0,0.1075416405439514,0,1,/addictedby/notebook5307c2da99,Parkinson's Freezing of Gait Prediction
12067,123568311,1297.0,,2,7,/archishmanbiswas2000/time-series-visualization,Parkinson's Freezing of Gait Prediction
12068,130878311,1214.0,,0,3,/williammcintoshpdx/utilityfogrectangulardataset,Parkinson's Freezing of Gait Prediction
12069,126245084,1324.0,0.1069525811520628,2,18,/donottalk/data-experiment-eda-and-two-models-fog-vs-age,Parkinson's Freezing of Gait Prediction
12070,126595165,1326.0,0.1069525811520628,0,1,/jamiebot/notebook0885db2925,Parkinson's Freezing of Gait Prediction
12071,126608088,1327.0,0.1069525811520628,0,1,/vinnyr12/vinny-fog-ml-competition,Parkinson's Freezing of Gait Prediction
12072,130660112,1336.0,0.1069525811520628,1,18,/suvarnayandapalli/parkinson-s-freezing-of-gait-prediction,Parkinson's Freezing of Gait Prediction
12073,129522387,1342.0,,0,4,/konstantinsamolinov/tdcsfog-defog-compare,Parkinson's Freezing of Gait Prediction
12074,134993448,1236.0,0.1069154525584026,0,0,/bimal0007/fog-model-final,Parkinson's Freezing of Gait Prediction
12075,126566494,1371.0,,0,2,/qianqianjin606/parkinson-xgboost,Parkinson's Freezing of Gait Prediction
12076,122446750,12.0,,2,5,/johnzhuang90/ink-detection-pytorch,Vesuvius Challenge - Ink Detection
12077,136649537,3.0,,0,2,/traptinblur/3rd-place-ensemble-576-8-384-6-224-8,Vesuvius Challenge - Ink Detection
12078,129477904,9.0,,18,34,/hengck23/lb0-56-one-fold-tta-encoder-pooled-uet-resnet34d,Vesuvius Challenge - Ink Detection
12079,130075007,84.0,,4,12,/raki21/surface-map-visualization,Vesuvius Challenge - Ink Detection
12080,124521268,11.0,0.4184422563490642,29,143,/tanakar/2-5d-segmentaion-baseline-inference,Vesuvius Challenge - Ink Detection
12081,127333386,33.0,,4,26,/lucasvw/0-11-simplest-possible-solution-submit-testmask,Vesuvius Challenge - Ink Detection
12082,133680404,13.0,0.758979548487145,0,1,/mkotyushev/scrolls-inference-agg,Vesuvius Challenge - Ink Detection
12083,124398572,81.0,0.1063269389061867,0,7,/honishi1/pytorch-unet-combinedloss,Vesuvius Challenge - Ink Detection
12084,127919385,402.0,,0,2,/synset/vesuvius-data-trn-val-tst,Vesuvius Challenge - Ink Detection
12085,125019115,379.0,,14,48,/samfc10/vesuvius-challenge-3d-resnet-training,Vesuvius Challenge - Ink Detection
12086,129687219,380.0,0.3697885993499734,4,14,/elvenmonk/training-no-trimming,Vesuvius Challenge - Ink Detection
12087,124777351,76.0,,0,11,/davidrouyre/interactive-visualization,Vesuvius Challenge - Ink Detection
12088,123515851,145.0,0.1129508367928077,3,25,/bibanh/pytorch-0-12-deeplabv3-bceloss,Vesuvius Challenge - Ink Detection
12089,125475158,172.0,,8,26,/lonnieqin/vesuvius-challenge-gif-animation,Vesuvius Challenge - Ink Detection
12090,131132454,205.0,0.0,1,6,/servipcpanama/hidden-ink-challenge,Vesuvius Challenge - Ink Detection
12091,130424042,210.0,0.1137607349460488,0,1,/mirenaborisova/vesuvius-challenge-rle-albumentations-0-11,Vesuvius Challenge - Ink Detection
12092,129166016,279.0,0.0,0,0,/hungyishuoe24091027/vesuvius-challenge-ink-detection-tutorial,Vesuvius Challenge - Ink Detection
12093,134600674,317.0,,0,3,/thenoodleninja/exploratory-data-analysis,Vesuvius Challenge - Ink Detection
12094,125275172,378.0,,3,21,/hughsando/visualize-the-3d-fragment-height,Vesuvius Challenge - Ink Detection
12095,133583657,521.0,0.6029863967809183,0,2,/gpreda/inheritance-multiple-network-architectures-submit,Vesuvius Challenge - Ink Detection
12096,129251750,490.0,,0,0,/raphaelrolland/simple-test-notebookd80b0e7c2f,Vesuvius Challenge - Ink Detection
12097,129255994,491.0,0.5287276308563043,0,4,/krishnaharish/2-5d-segmentaion-model-with-rotate-tta,Vesuvius Challenge - Ink Detection
12098,126555637,529.0,,0,8,/sherkt1/vesuvius-histograms-of-each-sample-object,Vesuvius Challenge - Ink Detection
12099,132227820,530.0,0.4184422563490642,0,0,/hsinnosuke/2-5d-segmentaion-baseline-inference,Vesuvius Challenge - Ink Detection
12100,128456145,566.0,,0,2,/stephendemjanenko/x-ray-stats-mean-and-variance,Vesuvius Challenge - Ink Detection
12101,124637094,448.0,,2,29,/kotaiizuka/faster-rle,Vesuvius Challenge - Ink Detection
12102,122564198,614.0,,0,11,/ayushmankumar7/some-useful-insights-eda,Vesuvius Challenge - Ink Detection
12103,122594969,630.0,0.0,0,8,/benjenkins96/vesuvius-challenge-eda-baseline-model,Vesuvius Challenge - Ink Detection
12104,128261539,679.0,,0,2,/rainfalllove/dataset-make-stacked-tile-dataset,Vesuvius Challenge - Ink Detection
12105,129951067,709.0,0.4184422563490642,0,1,/canobliviate0/2-5d-segmentaion-baseline-inference-qzh-jnu,Vesuvius Challenge - Ink Detection
12106,131555646,710.0,0.0383989358454585,0,0,/jyueyuyao/submit-testmask,Vesuvius Challenge - Ink Detection
12107,126325554,575.0,,4,1,/jeffborack/vesuvius-tf-not-learning-thoughts,Vesuvius Challenge - Ink Detection
12108,125916891,854.0,,0,1,/itberrios6/convert-to-pointcloud,Vesuvius Challenge - Ink Detection
12109,125596853,819.0,,0,2,/jiaxinpan0624/ink-test,Vesuvius Challenge - Ink Detection
12110,125313351,952.0,,1,4,/fpeccia/evaluation-metric-for-keras,Vesuvius Challenge - Ink Detection
12111,124295699,972.0,,5,34,/leventelippenszky/vesuvius-challenge-animation-of-letters,Vesuvius Challenge - Ink Detection
12112,122708440,988.0,,5,43,/chenyh368/0-16-pytorch-unet-bce-baseline,Vesuvius Challenge - Ink Detection
12113,123137978,880.0,,3,14,/viktorfairuschin/ink-detektion-tutorial-with-tensorflow,Vesuvius Challenge - Ink Detection
12114,129429345,1022.0,0.0358751004067908,0,0,/dimkko/my-submission,Vesuvius Challenge - Ink Detection
12115,131798266,1054.0,0.0,0,6,/vinitkp/vesuvius-ink-detection-try-parameters,Vesuvius Challenge - Ink Detection
12116,132265744,1051.0,,0,1,/kyo0802/unet-ink-detection-ans,Vesuvius Challenge - Ink Detection
12117,124892159,1172.0,,0,4,/jocelyndumlao/vesuvius-challenge-ink-detection-tutorial,Vesuvius Challenge - Ink Detection
12118,126433725,1089.0,,0,2,/ajland/tensorflow-implementation-of-tutorial,Vesuvius Challenge - Ink Detection
12119,125084215,1235.0,0.0,1,4,/mr0106/vcid1,Vesuvius Challenge - Ink Detection
12120,125084215,1235.0,0.0,1,4,/mr0106/vcid1,Vesuvius Challenge - Ink Detection
12121,125084215,1235.0,0.0,1,4,/mr0106/vcid1,Vesuvius Challenge - Ink Detection
12122,125084215,1235.0,0.0,1,4,/mr0106/vcid1,Vesuvius Challenge - Ink Detection
12123,122616513,1223.0,,0,4,/colewelkins/vesuvius,Vesuvius Challenge - Ink Detection
12124,131223510,1202.0,,0,2,/chaitanyakohli678/u-net-with-3dinput-and-2d-output,Vesuvius Challenge - Ink Detection
12125,128868889,1082.0,0.0,0,1,/sachinkumar413/vesuvius-challenge-ink-detection-tutorial,Vesuvius Challenge - Ink Detection
12126,130719725,1044.0,0.0,0,0,/nvasilevn/check1,Vesuvius Challenge - Ink Detection
12127,133510386,1143.0,0.0,0,4,/sabahesaraki/vesuvius-ink-detection-pytorch-segmentation,Vesuvius Challenge - Ink Detection
12128,123103850,2.0,0.3017854421873411,0,2,/dongjun819/pgs3-11-eda-feature-importances,Regression with a Tabular Media Campaign Cost Dataset
12129,122796787,37.0,,0,19,/mattop/playground-series-s3-e11-eda-tsne-pca,Regression with a Tabular Media Campaign Cost Dataset
12130,123354706,81.0,0.2987633339931209,1,32,/iqbalsyahakbar/ps3e11-simple-eda-fe-and-model-for-beginners,Regression with a Tabular Media Campaign Cost Dataset
12131,123088608,35.0,0.2940782679578193,6,13,/ashenranaweera/automl-model-ps-s03e11,Regression with a Tabular Media Campaign Cost Dataset
12132,123229900,17.0,0.293034654030039,30,66,/shashwatraman/eda-adversarial-validation-and-simple-xgboost,Regression with a Tabular Media Campaign Cost Dataset
12133,124282142,65.0,,10,37,/nikitagrec/top-1-catboost-0-2947-loss-trick,Regression with a Tabular Media Campaign Cost Dataset
12134,124062785,23.0,0.2951107482884481,0,3,/ashtcoder/pg-se-e11-eda-feateng-ensemble,Regression with a Tabular Media Campaign Cost Dataset
12135,124360651,15.0,0.2926836113474418,0,9,/omarvivas/cb-tpgs-s3e11-v1,Regression with a Tabular Media Campaign Cost Dataset
12136,124459441,19.0,,0,0,/tttrrraaahhh/notebooke85df3b5d9,Regression with a Tabular Media Campaign Cost Dataset
12137,124384057,10.0,0.3008963622411651,2,10,/satyaprakashshukl/simple-model-boost,Regression with a Tabular Media Campaign Cost Dataset
12138,123345546,5.0,0.2933276646647033,8,22,/paddykb/ps-s3e11-pump-up-the-gam,Regression with a Tabular Media Campaign Cost Dataset
12139,123576088,86.0,,0,4,/airqualityanthony/playground-series-3-episode-11-xgboost-hyperopt,Regression with a Tabular Media Campaign Cost Dataset
12140,123093043,507.0,,0,7,/arlle26/s3e11-eda-multi-model-xgb-tunning-lb0-298,Regression with a Tabular Media Campaign Cost Dataset
12141,123943620,102.0,0.2974250091032682,0,5,/arunpurakkatt/adversarial-validation-xgb,Regression with a Tabular Media Campaign Cost Dataset
12142,123692077,69.0,0.2932908399660565,0,0,/keerthanas57/playground-series,Regression with a Tabular Media Campaign Cost Dataset
12143,122975346,147.0,,11,26,/kimmik123/starter-notebook-ps-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12144,125140469,56.0,,0,0,/nickseader/s3e11-media-cost,Regression with a Tabular Media Campaign Cost Dataset
12145,126601989,82.0,,6,44,/aonzahaha/ps3e11-xgboost-tuning-permutation-importance,Regression with a Tabular Media Campaign Cost Dataset
12146,124472508,138.0,0.2972321799340462,1,5,/laurao/ps3e11-eda-data-prep-kfold-lgbm,Regression with a Tabular Media Campaign Cost Dataset
12147,122939037,59.0,0.2947573726445234,7,33,/tolgayan/simple-yet-effective-lb-0-29475,Regression with a Tabular Media Campaign Cost Dataset
12148,123143075,55.0,,0,6,/rutujab99/ps3e11-completeworkflow,Regression with a Tabular Media Campaign Cost Dataset
12149,122796373,141.0,,0,5,/qiaoningchen/eda-at-a-glance-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12150,124235872,129.0,0.2927570384080362,2,22,/syerramilli/ps3e11-xgboost-bayesopt,Regression with a Tabular Media Campaign Cost Dataset
12151,123326288,124.0,0.2931127349563512,0,11,/yimingliang/pss3-e11-eda-lgbm-feature-importance,Regression with a Tabular Media Campaign Cost Dataset
12152,124459548,155.0,0.3026580668747381,1,10,/dillanwilliams/ps-3-11,Regression with a Tabular Media Campaign Cost Dataset
12153,124459548,155.0,0.3039643981072149,1,10,/dillanwilliams/ps-3-11,Regression with a Tabular Media Campaign Cost Dataset
12154,123364793,126.0,,0,10,/hlgdatascience/intuitive-understanding-of-rmsle,Regression with a Tabular Media Campaign Cost Dataset
12155,135347762,163.0,,19,45,/mohammadrazeghi/playgrounds3e11-simple-eda-regressionmodeling,Regression with a Tabular Media Campaign Cost Dataset
12156,123164336,183.0,,1,9,/loki003/s3ep11viz,Regression with a Tabular Media Campaign Cost Dataset
12157,122760411,175.0,,2,7,/camillagretschel/tps-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12158,123403248,174.0,0.2927769434930832,4,11,/killershoaib/pse11-eda-xgboost,Regression with a Tabular Media Campaign Cost Dataset
12159,123403248,174.0,0.2927769434930832,4,11,/killershoaib/pse11-eda-xgboost,Regression with a Tabular Media Campaign Cost Dataset
12160,123617875,168.0,,2,7,/tmleyncodes/playground-series-season-3-episode-11,Regression with a Tabular Media Campaign Cost Dataset
12161,123928372,195.0,0.2929017727391471,11,28,/ndeperrois/sklearn-for-newbies-regression-boosting,Regression with a Tabular Media Campaign Cost Dataset
12162,122795349,182.0,,2,21,/mpwolke/cost-of-media-campaign-h2oautoml,Regression with a Tabular Media Campaign Cost Dataset
12163,124485063,186.0,0.4803849564439513,0,2,/chiragksharma/linear-lasso-dt-randomforest-xgboost,Regression with a Tabular Media Campaign Cost Dataset
12164,123389215,194.0,0.3159797586779868,0,0,/kumarsakshat22/playground-series-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12165,123225340,419.0,,0,2,/bradywagner/initial-eda-and-modeling,Regression with a Tabular Media Campaign Cost Dataset
12166,123084209,215.0,0.3081686823104357,1,7,/thedwong/s3-e11-eda-base-models,Regression with a Tabular Media Campaign Cost Dataset
12167,123677625,222.0,,0,11,/callumrafter/ps3-11-submission,Regression with a Tabular Media Campaign Cost Dataset
12168,123788859,220.0,0.2957408797953718,20,50,/sujaykapadnis/s3e11-eda,Regression with a Tabular Media Campaign Cost Dataset
12169,122843402,210.0,,1,14,/bonniehall/ps3-e11-initial-eda-baseline-models,Regression with a Tabular Media Campaign Cost Dataset
12170,124464021,316.0,0.2931537170043294,2,9,/sharvalishinde/ps-s3e11-basic-eda-fe-xgb-lgbm-ensemble,Regression with a Tabular Media Campaign Cost Dataset
12171,124464021,316.0,0.2931537170043294,2,9,/sharvalishinde/ps-s3e11-basic-eda-fe-xgb-lgbm-ensemble,Regression with a Tabular Media Campaign Cost Dataset
12172,122902197,224.0,0.2979805853794893,0,9,/belati/media-campaign-cost-pseudo-labelling,Regression with a Tabular Media Campaign Cost Dataset
12173,123226091,233.0,0.2978853863005694,0,18,/docxian/ps-s3-e11-media-campaign-cost,Regression with a Tabular Media Campaign Cost Dataset
12174,123226091,233.0,0.2976804717115894,0,18,/docxian/ps-s3-e11-media-campaign-cost,Regression with a Tabular Media Campaign Cost Dataset
12175,123934925,239.0,0.2933319373880761,0,5,/edwardhuangtw/top-19-ps-s3-ep11-auto-ml,Regression with a Tabular Media Campaign Cost Dataset
12176,125561963,236.0,,0,1,/cristobalchavez/xgboost-drop-columns-and-tuning-with-optuna,Regression with a Tabular Media Campaign Cost Dataset
12177,122833697,243.0,,1,11,/christrandata/interactive-eda-baseline-model,Regression with a Tabular Media Campaign Cost Dataset
12178,124482757,254.0,0.2962402551246374,0,10,/sahilkumar101/ps3-e11-nn,Regression with a Tabular Media Campaign Cost Dataset
12179,122856310,274.0,0.3010231215751923,3,31,/ridwanakmal/eda-lgbm-baseline,Regression with a Tabular Media Campaign Cost Dataset
12180,123916982,283.0,0.3032496171392689,0,14,/espjames/ps3e11-catboost,Regression with a Tabular Media Campaign Cost Dataset
12181,122970157,291.0,0.2947573726445234,0,8,/sanandachowdhury/simple-yet-effective-lb-0-29475,Regression with a Tabular Media Campaign Cost Dataset
12182,122970157,291.0,0.2947573726445234,0,8,/sanandachowdhury/simple-yet-effective-lb-0-29475,Regression with a Tabular Media Campaign Cost Dataset
12183,123832575,284.0,0.2949636162483592,21,28,/eleonoraricci/pgs-s3e11-pytorch-implementation,Regression with a Tabular Media Campaign Cost Dataset
12184,123974239,288.0,0.2948988705169537,0,0,/brolak/e11-eda-catboost-hypertuning,Regression with a Tabular Media Campaign Cost Dataset
12185,123017749,301.0,,1,7,/rgowerbruh/optuna-for-beginners,Regression with a Tabular Media Campaign Cost Dataset
12186,124404999,311.0,0.2954805457333275,11,30,/charunumesh/ps-s3-e11-eda-xgb,Regression with a Tabular Media Campaign Cost Dataset
12187,123260941,322.0,0.3016614461104266,0,0,/marceliussteven/ps3e11-eda-data-preprocessing-modeling,Regression with a Tabular Media Campaign Cost Dataset
12188,124527704,324.0,,0,4,/sunyoungyoun/mini-project-playground-se3-ep-11,Regression with a Tabular Media Campaign Cost Dataset
12189,124354248,326.0,,0,6,/kavishchaudhary1003/playground-s3-e11-optuna-xgb-lgbm-catboost,Regression with a Tabular Media Campaign Cost Dataset
12190,124517432,343.0,,0,0,/horikk/playground-pjt-xgboost,Regression with a Tabular Media Campaign Cost Dataset
12191,128251652,342.0,,0,0,/rozddh/mlproj-model-adaboost,Regression with a Tabular Media Campaign Cost Dataset
12192,122920543,333.0,0.2959031972670466,0,6,/andreychubin/pg3e11-eda-and-lgbm-optuna,Regression with a Tabular Media Campaign Cost Dataset
12193,131151502,334.0,,4,10,/gkitchen/predicting-supermarket-campaign-costs,Regression with a Tabular Media Campaign Cost Dataset
12194,124474432,331.0,,3,9,/timothylincoln2/s3-e11-ps-cost-prediction-with-eda,Regression with a Tabular Media Campaign Cost Dataset
12195,124298949,330.0,0.2959847705186148,7,15,/helmynaufal/media-campaign-cost-prediction,Regression with a Tabular Media Campaign Cost Dataset
12196,123622840,340.0,0.2960038416931543,2,17,/panini92/playground-series-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12197,123622840,340.0,0.2960038416931543,2,17,/panini92/playground-series-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12198,123298223,348.0,,0,6,/ryangreiner/s3-e11-initial-eda,Regression with a Tabular Media Campaign Cost Dataset
12199,123680693,347.0,0.2960319251581805,1,6,/kirillka95/s3e11-eda-models-test-optuna-ensemble,Regression with a Tabular Media Campaign Cost Dataset
12200,124435424,356.0,,0,1,/baokar7/ps-s3e11-xgb-with-feature-importance-and-optuna,Regression with a Tabular Media Campaign Cost Dataset
12201,123816985,353.0,0.3373560047979402,0,1,/nakulshahdadpuri314/basic-feature-engineering-with-xgboost-optuna,Regression with a Tabular Media Campaign Cost Dataset
12202,123893449,370.0,,0,6,/sofiamatias/playground-s3e11-regression-with-auto-sklearn,Regression with a Tabular Media Campaign Cost Dataset
12203,123615356,366.0,0.3014812773817564,0,4,/macklinshanahan/notebook-ep11,Regression with a Tabular Media Campaign Cost Dataset
12204,123446447,364.0,,3,14,/tengluoxiyue/eda-report-catboost-solution,Regression with a Tabular Media Campaign Cost Dataset
12205,124507039,373.0,,0,1,/gabrielott/ep-11-medeiros,Regression with a Tabular Media Campaign Cost Dataset
12206,124083802,396.0,0.296675988231403,0,10,/grantgonnerman/ps-s3-e11-eda-and-model-comparisons,Regression with a Tabular Media Campaign Cost Dataset
12207,124083802,396.0,0.2982177309008427,0,10,/grantgonnerman/ps-s3-e11-eda-and-model-comparisons,Regression with a Tabular Media Campaign Cost Dataset
12208,124083802,396.0,0.297105853618509,0,10,/grantgonnerman/ps-s3-e11-eda-and-model-comparisons,Regression with a Tabular Media Campaign Cost Dataset
12209,124083802,396.0,0.2971370872464747,0,10,/grantgonnerman/ps-s3-e11-eda-and-model-comparisons,Regression with a Tabular Media Campaign Cost Dataset
12210,124083802,396.0,0.2963225925170066,0,10,/grantgonnerman/ps-s3-e11-eda-and-model-comparisons,Regression with a Tabular Media Campaign Cost Dataset
12211,123983262,390.0,,0,1,/raghulraj422/s3e11-eda-xgboostregressor,Regression with a Tabular Media Campaign Cost Dataset
12212,122901717,386.0,,0,8,/daltondencklau/ps3-ep11-eda-baseline-models,Regression with a Tabular Media Campaign Cost Dataset
12213,124497209,401.0,0.2963885953680411,0,3,/shiyunlong07/simple-baseline-with-catboost,Regression with a Tabular Media Campaign Cost Dataset
12214,122734072,410.0,,3,13,/ryotapy/simpleeda-simplemodel-xgb-lgb-cat-0-29694,Regression with a Tabular Media Campaign Cost Dataset
12215,124359186,428.0,0.2974895552558381,0,1,/andreaskaufmann/s3e11-dnn-cv,Regression with a Tabular Media Campaign Cost Dataset
12216,123233216,400.0,,1,9,/siddharthkumarsah/s3e11-playground-solution,Regression with a Tabular Media Campaign Cost Dataset
12217,122802447,422.0,,1,12,/gauravduttakiit/pss3e11-autoviz,Regression with a Tabular Media Campaign Cost Dataset
12218,124274102,430.0,,0,5,/abocadobaby/ps-3-ep-11-xgboost-regressor,Regression with a Tabular Media Campaign Cost Dataset
12219,124359075,445.0,0.2978589725777157,0,23,/zhukovoleksiy/ps3e11-ensemble-prediction,Regression with a Tabular Media Campaign Cost Dataset
12220,123571602,437.0,,0,10,/alvinmanojalex/p-s3-e11-data-analysis-outlier-analysis,Regression with a Tabular Media Campaign Cost Dataset
12221,123235845,460.0,0.2977870547488667,3,26,/francescoliveras/ps-s3-e11-eda-model-en-es,Regression with a Tabular Media Campaign Cost Dataset
12222,123905574,463.0,,0,1,/romrawinchumpu/ps-s3e11-quick-media-campaign-cost-dataset,Regression with a Tabular Media Campaign Cost Dataset
12223,122842892,455.0,0.3025929099393286,0,7,/seholeee/optuna-xgboost-lgbm-catboost-ensemble,Regression with a Tabular Media Campaign Cost Dataset
12224,124579468,435.0,,1,6,/davidhguerrero/230321-pss3-e11-media-campaign-cost,Regression with a Tabular Media Campaign Cost Dataset
12225,122850431,471.0,,3,22,/nancysamuel/pss-3-ep-11,Regression with a Tabular Media Campaign Cost Dataset
12226,123586159,467.0,,2,5,/okoloboga/pgs-s03e11-regression-nn,Regression with a Tabular Media Campaign Cost Dataset
12227,124168887,472.0,0.2985974306777145,2,4,/averma111/playground-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12228,124168887,472.0,0.2985974306777145,2,4,/averma111/playground-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12229,123181746,487.0,0.2983131715174909,0,2,/kasperlindmark/social-notebook,Regression with a Tabular Media Campaign Cost Dataset
12230,124475755,483.0,0.3016067416672362,0,1,/hamzaboulahia/ps3e11,Regression with a Tabular Media Campaign Cost Dataset
12231,123581886,499.0,0.2986079375784659,0,3,/paw27182/ps3e11-lightgbm-optuna-kfold,Regression with a Tabular Media Campaign Cost Dataset
12232,124444358,511.0,,0,2,/byronjehrke/byron-s-notebook,Regression with a Tabular Media Campaign Cost Dataset
12233,124022721,510.0,0.2989001128623876,0,0,/anaghanair06/media-cost,Regression with a Tabular Media Campaign Cost Dataset
12234,123680199,502.0,0.3195990695252361,0,6,/sumedhakoranga/ps-s3e11-dummy,Regression with a Tabular Media Campaign Cost Dataset
12235,124017407,521.0,,0,1,/vayllanvictordesouza/mid-sem-catboost-regressor,Regression with a Tabular Media Campaign Cost Dataset
12236,122911562,542.0,0.3011252230698308,0,7,/pe4eniks/lightgbm-catboost-xgboost-rmsle-no-eda,Regression with a Tabular Media Campaign Cost Dataset
12237,124453037,526.0,0.303637700091048,2,7,/amitabhanand21/basic-eda-and-model-implementation-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12238,123216582,535.0,,2,12,/akioonodera/ps-3-11-lgbm-reg,Regression with a Tabular Media Campaign Cost Dataset
12239,124456366,519.0,,1,14,/amarloni/pgs3e11,Regression with a Tabular Media Campaign Cost Dataset
12240,124484531,545.0,0.2992211273581057,0,1,/datascientistsohail/media-campaign-bayesian-lgbmregressor-se03ep11,Regression with a Tabular Media Campaign Cost Dataset
12241,123075418,543.0,0.2993641574077307,0,3,/barbagrande007/bbg007-s3e11-mediacost,Regression with a Tabular Media Campaign Cost Dataset
12242,124125383,560.0,,0,2,/lucasseiti/catboostregressor,Regression with a Tabular Media Campaign Cost Dataset
12243,124313920,550.0,,2,6,/iniyatj/playground-series-s3e11-xgb,Regression with a Tabular Media Campaign Cost Dataset
12244,122991191,575.0,0.2996322742665308,0,3,/japkeeratsingh/beginner-xgboost-optuna-kfold,Regression with a Tabular Media Campaign Cost Dataset
12245,123861008,564.0,,0,0,/shidhantrai/cia-3,Regression with a Tabular Media Campaign Cost Dataset
12246,123313424,576.0,,0,0,/next1011/use-lightautoml-ps3e11,Regression with a Tabular Media Campaign Cost Dataset
12247,123968454,574.0,,0,4,/mckayla/ps-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12248,122774185,590.0,,0,9,/alexandrepetit881234/s3e11-media-campaign-eda-and-benchmarking,Regression with a Tabular Media Campaign Cost Dataset
12249,123844276,568.0,0.3015387455455027,0,4,/bhavyagiri/ps-s3e11-eda-xgbregressor,Regression with a Tabular Media Campaign Cost Dataset
12250,123878239,591.0,,4,16,/itspavansatish/automl-vs-optuna,Regression with a Tabular Media Campaign Cost Dataset
12251,123626061,597.0,,0,12,/raphaelmarconato/s3e11-eda-and-machine-learning,Regression with a Tabular Media Campaign Cost Dataset
12252,124080731,599.0,,0,0,/alexbostick/cat-regressor-with-feature-engineering,Regression with a Tabular Media Campaign Cost Dataset
12253,123185707,602.0,0.3004617097438463,0,5,/boyochan/eda-catboost-with-optuna,Regression with a Tabular Media Campaign Cost Dataset
12254,123459965,637.0,0.3011534214255656,0,6,/krbharat/ps3-e11-eda-ensemble-model,Regression with a Tabular Media Campaign Cost Dataset
12255,123100983,632.0,,0,1,/glavianhcastelino/playground-series-season-3-episode-11playground,Regression with a Tabular Media Campaign Cost Dataset
12256,123262654,634.0,,0,1,/nguyenn95/playground-series-season-3-episode-11,Regression with a Tabular Media Campaign Cost Dataset
12257,124507592,631.0,0.3026688362855945,0,7,/klyushnik/episode-11,Regression with a Tabular Media Campaign Cost Dataset
12258,122957213,685.0,0.301478856215813,0,9,/chongjiaxu/easy-random-forest,Regression with a Tabular Media Campaign Cost Dataset
12259,123200922,669.0,,0,1,/takahironamatame/ps-s3e11-baseline-xgb,Regression with a Tabular Media Campaign Cost Dataset
12260,124081651,678.0,0.3016876328342015,0,1,/dongkyumoon/tabnet-with-optuna,Regression with a Tabular Media Campaign Cost Dataset
12261,124457437,691.0,,1,2,/kiran1204/eda-simple-xgb-regressor,Regression with a Tabular Media Campaign Cost Dataset
12262,123887354,704.0,0.3019949625656783,0,0,/ericdeuber/store-cost-predictions-playground-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12263,125992770,711.0,,6,7,/zonwie/s3e11-beginner-decisiontree,Regression with a Tabular Media Campaign Cost Dataset
12264,123424332,709.0,0.3026464912367076,0,11,/jeevabharathis/ps3e11-predicting-cost-and-subimission,Regression with a Tabular Media Campaign Cost Dataset
12265,123845108,708.0,0.3034409791527562,11,43,/keenanzhuo/ps3e11-basic-eda-regression-updated,Regression with a Tabular Media Campaign Cost Dataset
12266,125059688,712.0,,0,2,/swagatobhaskar/pg-s3-e11-media-campaign-cost-regression,Regression with a Tabular Media Campaign Cost Dataset
12267,123196979,715.0,0.302567616486754,0,3,/stpeteishii/pss3-ep11-visualize-importance,Regression with a Tabular Media Campaign Cost Dataset
12268,123292978,734.0,,3,20,/jarmos/comprehensive-eda-modelling-notebook,Regression with a Tabular Media Campaign Cost Dataset
12269,124437289,861.0,0.3159975661999503,0,0,/iamnotashutosh/xgb-lgbm-catboost-optuna,Regression with a Tabular Media Campaign Cost Dataset
12270,124346448,758.0,0.3040857333291198,0,0,/bwallyn/playground-s03-e11-model-catboost,Regression with a Tabular Media Campaign Cost Dataset
12271,124317598,762.0,,0,5,/pradeepsapparapu/playground-series-best-models,Regression with a Tabular Media Campaign Cost Dataset
12272,162282097,763.0,0.305243123360413,2,36,/kapturovalexander/kapturov-s-playground-series-s3-e11,Regression with a Tabular Media Campaign Cost Dataset
12273,124490868,777.0,0.3049019286906996,0,1,/marioshadjiantonis/playground-series-s03ep1,Regression with a Tabular Media Campaign Cost Dataset
12274,123977655,776.0,,0,1,/jankuper192/playground-3-11-h20-modellen,Regression with a Tabular Media Campaign Cost Dataset
12275,124492790,788.0,0.3166763966476193,0,4,/asadcuet/cold-spark-pc-1,Regression with a Tabular Media Campaign Cost Dataset
12276,123374343,802.0,,5,13,/pranaii/eda-fe-modelling-playground-series-s3-e11,Regression with a Tabular Media Campaign Cost Dataset
12277,124480359,813.0,0.3088655514545753,0,3,/blessingumoru/pgs3e11-ensemble-feature-eng,Regression with a Tabular Media Campaign Cost Dataset
12278,123107242,833.0,0.3103024948945734,0,5,/anoyan/a-random-forest-baseline,Regression with a Tabular Media Campaign Cost Dataset
12279,124373097,849.0,,0,3,/lunaayase1993/playground-series-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12280,123133509,848.0,0.3156244083162689,0,2,/cyberblack0/notebookf8a76f03ed,Regression with a Tabular Media Campaign Cost Dataset
12281,123236869,845.0,0.3129827056908112,0,0,/laraiki/bl-playground-series-s3e11,Regression with a Tabular Media Campaign Cost Dataset
12282,122785082,853.0,0.3136159819707385,0,7,/tracyporter/play-3-11-tf-dnn,Regression with a Tabular Media Campaign Cost Dataset
12283,124223806,867.0,0.315965982191728,0,66,/anushreek15/playground-series,Regression with a Tabular Media Campaign Cost Dataset
12284,123028347,869.0,0.3159912483637252,2,11,/hsin1022/s3e11-lm-model-in-r-using-caret-package,Regression with a Tabular Media Campaign Cost Dataset
12285,124278055,886.0,0.3160184894298973,0,1,/abolajiatobatele/notebook79195e5979,Regression with a Tabular Media Campaign Cost Dataset
12286,122887005,893.0,,0,9,/hongseoi/pss3e11-automl-using-autogluon,Regression with a Tabular Media Campaign Cost Dataset
12287,124493216,925.0,0.3416929336472429,0,11,/richeyjay/media-campaign-cost-xgbr-eda,Regression with a Tabular Media Campaign Cost Dataset
12288,133891088,927.0,,10,33,/warcoder/mlflow-hyperopt,Regression with a Tabular Media Campaign Cost Dataset
12289,123052095,937.0,,2,19,/micaeld/playground-series-s3e1-decisiontree,Regression with a Tabular Media Campaign Cost Dataset
12290,129800190,2.0,,0,1,/conjuring92/w03-stem-glossary,Benetech - Making Graphs Accessible
12291,135044571,1.0,0.8624109910612435,0,8,/kashiwaba/benetech-1st-place-inference,Benetech - Making Graphs Accessible
12292,134193781,35.0,,0,5,/cooleel/scatter-detection-inference-and-post-processing,Benetech - Making Graphs Accessible
12293,126910770,13.0,,0,1,/namgalielei/benetech-extract-meta,Benetech - Making Graphs Accessible
12294,131621493,40.0,,6,65,/cody11null/tuned-donut,Benetech - Making Graphs Accessible
12295,134068362,55.0,0.7125719828667545,0,0,/chchchch123/fork-of-fork-of-fork-of-fork-of-fork-of-not-288418,Benetech - Making Graphs Accessible
12296,130140975,76.0,,0,0,/yuto0712/create-chart-info-dataset,Benetech - Making Graphs Accessible
12297,132018363,31.0,,4,5,/tanjiroll/chart-classifier-fastai-99-9-accuracy,Benetech - Making Graphs Accessible
12298,131199357,20.0,,2,12,/samratthapa/99-7-accuracy-efficientnet-b2-chart-classify,Benetech - Making Graphs Accessible
12299,126587105,93.0,,0,8,/asarvazyan/benetech-visualize-with-annotations,Benetech - Making Graphs Accessible
12300,133868800,66.0,0.648364196346208,0,2,/kingkong153/pix2struct-v8-best-score,Benetech - Making Graphs Accessible
12301,134144611,128.0,,0,1,/gabtenimouhamed/fine-tuning-deplot-using-peft-lora,Benetech - Making Graphs Accessible
12302,129188842,212.0,,8,5,/takaito/benetech-deplot-validation-0-215,Benetech - Making Graphs Accessible
12303,129016252,140.0,,0,3,/koyyy0/benetech-annotation-parser,Benetech - Making Graphs Accessible
12304,131665139,201.0,,2,14,/gauravk123/resnet50-how-to-deep-learning-ai-course-99-8,Benetech - Making Graphs Accessible
12305,133208238,209.0,,0,7,/timofeyefimov/evaluation-metric-loss-function-code,Benetech - Making Graphs Accessible
12306,129589658,155.0,,0,1,/vinitkp/eda-r-graph,Benetech - Making Graphs Accessible
12307,133877220,382.0,,0,6,/satyaprakashshukl/benetech-mga-eda,Benetech - Making Graphs Accessible
12308,129549520,383.0,,0,9,/fadmadahouz/chart-classifier-using-fastai,Benetech - Making Graphs Accessible
12309,127147103,440.0,,0,4,/pragyanbo/cleaned-dataset-creator,Benetech - Making Graphs Accessible
12310,124060962,480.0,,0,5,/durvalslompojunior/start-here-challenge-benetech,Benetech - Making Graphs Accessible
12311,128622574,543.0,,3,19,/eleonoraricci/spell-check-on-tick-labels-using-bert,Benetech - Making Graphs Accessible
12312,131465997,547.0,,2,13,/sohyunsim/benetech-data-validation,Benetech - Making Graphs Accessible
12313,125464833,548.0,,1,17,/yoshikuwano/predict-plot-bb-coordinates,Benetech - Making Graphs Accessible
12314,123990270,554.0,0.2456561203740376,0,0,/theholycityweb/donut-infer-lb-0-42-benetech,Benetech - Making Graphs Accessible
12315,123024865,564.0,,0,11,/seshurajup/bmga-train-dataset-csv-meta,Benetech - Making Graphs Accessible
12316,122963368,595.0,,3,37,/bibanh/simple-submission-classification-99-training,Benetech - Making Graphs Accessible
12317,133093383,606.0,0.0,0,7,/ashishjagdishsharma/benetech-making-graphs-accessible,Benetech - Making Graphs Accessible
12318,133093383,606.0,0.0,0,7,/ashishjagdishsharma/benetech-making-graphs-accessible,Benetech - Making Graphs Accessible
12319,129003101,1.0,,9,9,/lucaznguyenofficial/fathomnet-simple-dnn-make-your-1st-submission,FathomNet 2023
12320,124499997,58.0,0.86,2,16,/lizhecheng/s3e12-catboost-baseline,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12321,124972564,319.0,0.8640000000000001,0,5,/omarvivas/lgbm-tpgs-s3e12-v1,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12322,126057301,427.0,0.8986666666666667,0,0,/slimreaper/random-forest-xgb-catboost-ensemble-t40,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12323,124599211,661.0,0.8680000000000001,1,9,/loki003/simple-estimating-equation-pygwalker,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12324,125012913,755.0,,1,6,/tonychirilus/ps-s3e12-eda-model-ensemble,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12325,126155924,813.0,,0,1,/yyazidd/kidney-stone-knn-ps-s3-e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12326,125292197,273.0,,1,11,/yzokulu/pss3-ep12-randomforest-xgboost-0-87,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12327,125821068,747.0,,4,12,/brysonje/basic-before-complex-ideas,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12328,124800779,137.0,,8,34,/nikitagrec/top-8-score-rf-rank-prediction-0-894,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12329,125848436,226.0,,0,2,/ksh9567/simple-nn-using-torch,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12330,125331343,130.0,,0,2,/yus002/tpss3e12-eda-in-r,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12331,125932490,440.0,0.7933333333333333,0,7,/johnycooly/random-forest-with-optuna,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12332,125766745,171.0,,1,4,/madhvendrasingh21/kidneystoneprediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12333,124816372,583.0,0.8933333333333333,0,10,/fatismajli/ps3e12-top-10-with-deeplearning,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12334,125001173,280.0,0.87,1,8,/drmwnnrafi/ps3e12-flaml-with-automl,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12335,135343340,555.0,,16,37,/mohammadrazeghi/s03e12-simpleeda-xgb-optuna-gridsearch,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12336,125817733,753.0,,7,9,/ramzanzdemir/ps-s3-e12-kidney-stones-94-roc-auc,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12337,125120478,39.0,0.8613333333333334,0,3,/abhinav16aero/pss3e12-ensemble-always-wins-score-0-86133,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12338,132619665,421.0,,18,79,/tumpanjawat/kidney-stone-eda-prediction-7-model-2-nn,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12339,125072609,292.0,0.8866666666666667,0,13,/abdelrahmanrabah/oop-lgbm-xgb-no-sk,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12340,126321393,231.0,0.8546666666666666,0,1,/percedal/s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12341,126321393,231.0,0.8220000000000001,0,1,/percedal/s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12342,125917986,558.0,0.872,0,4,/marioshadjiantonis/playground-s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12343,125917986,558.0,0.8733333333333334,0,4,/marioshadjiantonis/playground-s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12344,125912929,81.0,,0,0,/georgedoukas/play-12-23-flaml-ensemple-scored-0-878,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12345,125725882,220.0,0.8746666666666666,9,34,/akioonodera/ps-3-12-lgbm-bin,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12346,126029538,463.0,,0,0,/saeschtheflash/playground-series-season-3-episode-12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12347,124965949,11.0,0.8786666666666666,8,38,/samuelcortinhas/ps-s3e12-global-optimisation,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12348,124530719,14.0,,2,7,/baokar7/ps-s3e12-eda-with-baseline-xgb,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12349,125079649,195.0,0.8559999999999999,0,2,/datascientistsohail/bayesian-lgbmclassifier-se03-ep12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12350,125676593,577.0,,0,3,/praveensaik/ps3e12-eda-catboost-nn-0-8666,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12351,125342171,333.0,0.8693333333333334,12,29,/yogesh239/ps3e12-eda-rfc-lr-lgbm-xgb-kidney-stone-pred,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12352,125253778,258.0,0.8773333333333333,7,20,/naesalang/little-beautiful-notebook,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12353,125336036,564.0,0.868,0,1,/paw27182/ps3e12-tensorflow-optuna,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12354,125848600,184.0,,24,70,/iqbalsyahakbar/ps3e12-simple-eda-fe-and-model-for-beginners,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12355,125239665,283.0,,0,8,/priyanshu594/edaandsimplestmodels,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12356,125889287,678.0,0.868,1,3,/jankuper192/playground-12-gam-h20-en-caret-emsambling,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12357,125338485,8.0,0.864,0,12,/donatoriccio/ps3e12-simple-stacking-starter-with-vecstack,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12358,125045363,53.0,,0,6,/narendra1998/should-we-include-the-orginal-data-pgs-se3-e-12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12359,126094508,121.0,,0,0,/handeakn/s3e12-eda-preprocessing-cv-tuning-2models,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12360,126097836,472.0,0.8573333333333333,0,4,/bianchimario/kidney-stone-prediction-ps-s3-e12-svc,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12361,126282988,84.0,,0,1,/kasperlindmark/xgb-kedneystones,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12362,126357406,19.0,,0,0,/praeradawongsung/private-score-0-77-eda-ensemble-models,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12363,124495915,198.0,,0,4,/gauravduttakiit/pss3e12-lazypredict,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12364,124782116,709.0,0.8266666666666667,0,4,/neupane9sujal/ps3e12-simple-eda-and-model,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12365,124966886,302.0,,0,6,/zeeshanarif53/using-keras-to-build-a-deep-learning-model,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12366,126382629,5.0,,1,29,/antoinerogeau/5-place-ensemble-xgb-lr-rf-knn,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12367,126116031,578.0,0.8746666666666667,0,2,/rajarshikundu/s3e12-eda-models,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12368,126116031,578.0,0.8746666666666667,0,2,/rajarshikundu/s3e12-eda-models,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12369,125688712,179.0,0.8613333333333334,2,12,/enjoyingworld/simple-baseline-model-lgbm,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12370,125889728,221.0,0.8693333333333333,0,4,/xietaowang/s3e12-eda-gbms,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12371,124734216,535.0,0.8506666666666667,7,6,/blessingumoru/pgs3e12-with-features-definition-catboost,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12372,124983310,323.0,0.8453333333333334,0,9,/jimgruman/s3e12-kidney-stones-gam,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12373,125986049,448.0,0.8486666666666667,0,1,/andrusha95/s03e12-simpleeda-rf-xgb-knn-gridsearch,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12374,124510597,194.0,,0,3,/pomiro/ps-3-12-eda,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12375,124585130,372.0,0.8693333333333334,0,5,/stpeteishii/pss3-ep12-visualize-importance,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12376,124796789,317.0,0.8493333333333334,10,25,/patriciabrezeanu/epic-tuning-finding-the-perfect-random-forest,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12377,125751284,437.0,0.8580000000000001,4,7,/krbharat/ps3-e12-eda-ensemble-model,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12378,124610753,311.0,,0,2,/sylzys/playground-s3e12-eda-lofo-feat-importance,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12379,124945250,312.0,0.8706666666666667,2,12,/brendancarney24/quick-and-simple-xgboost-ps3-e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12380,124949136,270.0,0.8706666666666667,2,7,/barnesparker/tuning-random-forest-with-tidymodels,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12381,124722885,682.0,0.8506666666666668,0,2,/andreaskaufmann/s3e12-simple-dnn,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12382,125382036,211.0,0.8593333333333333,0,1,/hosshi/playground-3-12-xgbclassifier,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12383,126124858,456.0,0.8706666666666666,8,22,/francescoliveras/ps-s3-e12-eda-model-en-es,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12384,124986221,192.0,,1,8,/ridwanakmal/ps3e12-ensembling-gradboost-extratree-lgbm,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12385,125636537,631.0,0.8586666666666667,0,1,/askeeee/ep12-logis-pca-cv-0-790119542124542,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12386,126130547,593.0,0.8613333333333334,0,1,/deepakjeff/kidney-stone,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12387,124874798,373.0,0.8546666666666667,0,4,/syerramilli/ps3e12-r-gbm-hyperopt,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12388,125800975,679.0,,4,4,/albertgalimov/demo-on-overfitting,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12389,125935425,424.0,,0,1,/paulreiners/using-scikit-optimize-playground-series-season,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12390,125217496,120.0,,0,2,/sabinaabdurakhmanova/ps3-12-tabnet,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12391,125971965,116.0,0.8626666666666668,5,8,/charunumesh/ps-s3-e12-eda-ensemble,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12392,125949175,355.0,0.8626666666666667,0,12,/cv13j0/playground-series-s3-e12-ideas,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12393,125949175,355.0,0.8466666666666667,0,12,/cv13j0/playground-series-s3-e12-ideas,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12394,125073094,213.0,,0,3,/tiranzhao/kindey-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12395,125329028,665.0,,0,0,/brother2330/prototyping,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12396,126263478,17.0,,0,3,/demko1/17-place-solution-notebook-nan-filling,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12397,126119365,64.0,,0,0,/soraharada/play-s3e12-baseline,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12398,126108602,469.0,0.8666666666666667,0,1,/gsdeepakkumar/kidney-stone-prediction-469th-solution,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12399,126172858,364.0,0.8626666666666667,3,15,/docxian/ps-s3-e12-kidney-stones-visual-journey,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12400,124791605,601.0,0.8653333333333333,0,9,/sujaykapadnis/ps-s2e12-basic,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12401,133331298,367.0,,7,34,/lusfernandotorres/s03e12-stacking-tuned-models,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12402,124611930,38.0,0.864,0,5,/kdmitrie/pgs312-eda-models-test-with-optuna-blending,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12403,124611930,38.0,0.8493333333333334,0,5,/kdmitrie/pgs312-eda-models-test-with-optuna-blending,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12404,124611930,38.0,0.856,0,5,/kdmitrie/pgs312-eda-models-test-with-optuna-blending,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12405,124611930,38.0,0.8600000000000001,0,5,/kdmitrie/pgs312-eda-models-test-with-optuna-blending,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12406,124897193,52.0,,0,3,/bilashalder/playground-s3-e12-eda-and-multimodel-predictions,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12407,125854262,16.0,0.8426666666666667,13,14,/sarvallerd/ps-s3-e12-catboost-xgb-lgbm-eda,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12408,126177994,244.0,,2,3,/joochaicoski/quick-analysis-hyperopt-tuning-xgb-rf-knn,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12409,130511950,281.0,,2,4,/nyagami/kidney-stones-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12410,124882580,516.0,0.8613333333333334,1,9,/chetantalele/simple-logistic-regression-kidney-stone-ds-pg-srs,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12411,124952320,517.0,,0,3,/bibhumohapatra18/kidney-stone-prediction-using-urine-datasets,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12412,125997703,802.0,,1,1,/davidhguerrero/230304-pss3-e12-kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12413,125304439,394.0,0.86,0,3,/stefanmayer2006/season-3-e-12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12414,125829589,335.0,0.7799999999999999,0,0,/matthewsfarmer/kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12415,124565297,65.0,,5,30,/seascape/target-calc,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12416,124715027,569.0,0.5,0,7,/sumedhakoranga/ps-s3-e12-dummy,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12417,125614310,603.0,,0,2,/caiocsn2/catboost-cluster-analysis,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12418,131081160,878.0,0.8066666666666669,1,11,/gkitchen/kidney-stones-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12419,125891658,534.0,0.8493333333333334,0,3,/adaubas/pss3e12-eda-svc-knn-and-more,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12420,124963608,667.0,,0,4,/okoloboga/pgs-s03e12-dense-nn-win-as-usual,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12421,125949643,746.0,,0,2,/ricardorios/ps-s3-ep12-eda-inference,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12422,124508388,532.0,,8,21,/mattop/playground-series-s3-e12-eda-tsne-pca,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12423,124617633,614.0,,0,9,/pranay20485/ps-s3-e12-choosing-best-classification-algorithm,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12424,124554917,490.0,,0,4,/laurao/ps3e12-simple-eda-catboost-kfold,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12425,125071305,660.0,,0,14,/panini92/playground-s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12426,124522491,582.0,0.852,1,5,/yimingliang/pss3-e12-eda-modeling,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12427,126178822,551.0,,0,3,/tgamstaetter/tidy-stones,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12428,125235681,722.0,,2,8,/ayushmehraa/ps3-kidney-stone-prediction-eda-xgb,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12429,125361983,63.0,0.848,0,3,/scirpus/gp-wee,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12430,125444443,917.0,0.7933333333333333,0,2,/barbagrande007/bbg007-s3-e12-kidneystones,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12431,125106091,688.0,,1,9,/hiroshikurokawa/p3s12-lgb-catb-xgb-ensemble,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12432,124831937,626.0,0.844,0,11,/abhinavmangalore/s3e12-kidney-stone-prediction-binary-classifier,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12433,125210186,296.0,,14,39,/eyadgk/kidney-stone-eda-ann-modeling,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12434,126017642,524.0,,39,95,/richeyjay/kidney-stone-prediction-eda-binary-classification,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12435,124790028,616.0,,2,8,/sharvalishinde/ps3-e12-eda-xgb-baseline,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12436,125833524,365.0,0.8426666666666667,0,4,/rishabhkamboj2003/kidneystone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12437,125910749,531.0,0.8413333333333333,2,4,/aasnegha/just-xgboost,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12438,124867287,636.0,,2,7,/abocadobaby/ps-s3e12-binary-classifier-rf-ada-xgb-cat-lgbm,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12439,127375195,349.0,,0,2,/acdundore/s3-e12-eda-risk-factors-xgb,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12440,124625887,446.0,0.8386666666666667,0,0,/hamzaboulahia/s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12441,124794137,780.0,0.6466666666666667,2,4,/ndeperrois/scikit-learn-for-newbies-ps-s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12442,125398163,715.0,0.8386666666666667,0,1,/tarikh93/kidney-stone-prediction-using-rfc,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12443,125649793,992.0,0.81,1,8,/amarloni/psg3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12444,128546490,434.0,,0,2,/kavishchaudhary1003/playground-s3-e12-optuna-xgb-lgbm-catboost,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12445,124953365,98.0,0.76,0,1,/smiles28/eda-and-flaml,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12446,124704416,825.0,0.8226666666666667,0,1,/tracyporter/play-3-12-tf,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12447,124562617,872.0,,2,6,/pradeepsapparapu/playground-series-12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12448,124974553,732.0,0.81,0,6,/edomingo/kidney-stones-eda-xgb-svm-ps3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12449,124798742,966.0,,1,4,/zonwie/s3e12-beginner-logistic-decision-random,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12450,125298866,867.0,,0,0,/ignaciodelcuvillo/academic-comeback,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12451,126379455,740.0,,0,4,/michakurcewicz/playground-series-season-3-episode-12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12452,125832514,708.0,0.7866666666666667,0,2,/animeshrockn/playground-3-12-logistic-regression,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12453,126431007,958.0,,0,2,/strategos2/playground-series-season-3-episode-12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12454,126194677,960.0,0.8266666666666667,2,3,/nandomartinez/hello-dataset,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12455,124921286,841.0,0.8166666666666667,0,5,/chrispanourgias/kidney-stone-pred,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12456,126095290,971.0,0.8166666666666667,1,1,/swagatobhaskar/pg-s3-e12-kidneystone-classification,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12457,124906688,798.0,,0,1,/jacksontangqunyao/playground-series-kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12458,130530182,987.0,0.8373333333333334,0,1,/mehulgoyal49/notebookfd0ad0906b,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12459,125083272,772.0,0.81,3,7,/averma111/pg-s3e12-xgboost-lgbm-randomforest-no-nn-used,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12460,125114111,923.0,0.6833333333333332,0,10,,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12461,125114111,923.0,0.7900000000000001,0,10,,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12462,125114111,923.0,0.81,0,10,,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12463,125507588,773.0,0.7900000000000001,0,1,/amitabhanand21/beginner-friendly-models,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12464,126060715,927.0,0.8066666666666669,0,1,/robertturro/ps-3-12-basic-logistic-regression-model,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12465,125631443,1004.0,0.7986666666666666,9,16,/vikramshankar18/xgboost-kf,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12466,124895723,721.0,,0,7,/chooyeanchan/playground-beginner-230407,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12467,124819978,851.0,0.7946666666666666,0,2,/bohdantsynalievskyi/binary-classifications-practice,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12468,125405317,1052.0,0.796,0,4,/wepasabyrow/binary-classification-with-a-kidney-stone-predicti,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12469,124785102,910.0,0.7933333333333333,6,10,/nandini1007/playground-series-kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12470,124774055,1050.0,0.7566666666666667,0,3,/tayfungrlevik/playground-series-s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12471,124878645,1039.0,0.7900000000000001,0,0,/rafiromolo/kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12472,125352786,951.0,0.71,0,2,/kavinkv/kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12473,125654563,956.0,,0,1,/kiran1204/kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12474,126403304,1066.0,,3,7,/jagadishrcz/kidney-stone-predictions,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12475,127910234,1026.0,,0,7,/alexbostick/xgbooooost-kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12476,124855678,1006.0,,6,24,/burhanuddinlatsaheb/s3-e12-eda-px-v-s-sns-randomforest-lgbm-xgb,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12477,125044801,1045.0,,1,5,/shubhamgupta012/playground-s312,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12478,125463773,695.0,0.7866666666666667,0,6,/kkhandekar/top-10-algorithms-for-binary-classification,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12479,162509346,853.0,,2,33,/kapturovalexander/kapturov-s-playground-series-s3-e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12480,124729157,1021.0,,1,9,/venkatganesh98/ps-s3-e12-kidney-stone-prediction-rfc,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12481,133122988,929.0,,0,6,/iqmansingh/kidney-stone-classification,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12482,126314951,831.0,,0,2,/ssankarr/kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12483,125293310,777.0,0.7700000000000001,0,5,/brolak/s03e12-eda-baseline-ensemble,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12484,125768878,888.0,0.7533333333333334,1,7,/obinna11/kidney-stone-urine-analysis,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12485,127877509,918.0,,0,1,/burakarslan1/playground-series-3-12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12486,125527068,1038.0,0.7666666666666667,0,1,/mohamedafsal007/kidney-playgroundseries,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12487,125348144,990.0,,2,11,/shuvojitdas/kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12488,126138555,1057.0,,0,0,/zeenatwaseem/kidney-stone-urine-analysis,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12489,124584342,1010.0,,7,10,/suzukifelipe/randomforestclassifier-playground-s3e12,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12490,125631200,1077.0,0.35,0,2,/unstoppablesk/kidney-stone-prediction,Binary Classification with a Tabular Kidney Stone Prediction Dataset
12491,134597131,7.0,,1,2,/alexanderveicht/imc2023-from-repo,Image Matching Challenge 2023
12492,133485423,5.0,,0,1,/maxchen303/imc2023-test-notes,Image Matching Challenge 2023
12493,143228921,29.0,,0,2,/motono0223/imagematching-dkm-example,Image Matching Challenge 2023
12494,129794236,174.0,,1,11,/thomasrochefort/how-to-offline-depth-estimation-with-midas-dpt,Image Matching Challenge 2023
12495,133356240,180.0,,0,9,/suraj520/superpoint-magicleap-as-a-local-feature-extractor,Image Matching Challenge 2023
12496,128167362,399.0,,0,1,/pawchen/perf-checking-between-cv-and-pil,Image Matching Challenge 2023
12497,128501149,377.0,,3,3,/benormal/pytorch-base,Image Matching Challenge 2023
12498,128715489,402.0,,0,3,/yoyobar/get-cameras-parameter,Image Matching Challenge 2023
12499,130310155,477.0,,2,2,/sathishkumartheta/dataloader-for-imc-2023-ipynb,Image Matching Challenge 2023
12500,129568070,454.0,0.0011140798451378,0,13,/averma111/pytorch-image-matching,Image Matching Challenge 2023
12501,129830325,482.0,0.0,5,32,/jessevanderlinden/image-matching-data-discovery-and-sift-features,Image Matching Challenge 2023
12502,130912293,491.0,4.912073563900776e-06,0,12,/jocelyndumlao/sift-image-matching-challenge,Image Matching Challenge 2023
12503,127181038,247.0,,0,9,/belati/vector-borne-disease-eda-why-our-model-sucks,Classification with a Tabular Vector Borne Disease Dataset
12504,126442286,309.0,0.4105960264900663,9,19,/nlztrk/naive-voting-ensembler,Classification with a Tabular Vector Borne Disease Dataset
12505,127133246,527.0,,0,1,/erokhinvitaly/ps-s3e13-cleaning-the-ensemble-better-score,Classification with a Tabular Vector Borne Disease Dataset
12506,127438770,505.0,0.3929359823399559,0,6,/omarvivas/cb-tpgs-s3e13-v1,Classification with a Tabular Vector Borne Disease Dataset
12507,128014397,310.0,0.3719646799116999,0,3,/act18l/ps-s3e13-denoise-autoencoder-nn-cv-0-48-pb-0-44,Classification with a Tabular Vector Borne Disease Dataset
12508,126493783,5.0,0.4105960264900664,6,61,/zhukovoleksiy/ps-s3e13-simple-eda-ensemble-baseline,Classification with a Tabular Vector Borne Disease Dataset
12509,126902307,19.0,0.3719646799116999,0,2,/owendossett/conversion-of-tetsu2131-solution-to-map-3,Classification with a Tabular Vector Borne Disease Dataset
12510,127845520,539.0,0.2350993377483443,0,2,/jazivxt/swag-bourne-identity,Classification with a Tabular Vector Borne Disease Dataset
12511,128026857,58.0,,0,1,/rasoulisaeid/vector-borne-diseases-prediction,Classification with a Tabular Vector Borne Disease Dataset
12512,126323012,206.0,,0,7,/pietromaldini1/simple-baseline-using-idf-and-knn,Classification with a Tabular Vector Borne Disease Dataset
12513,126929814,22.0,0.4150110375275939,7,35,/paddykb/ps-s3e13-keras-haz-prognosis,Classification with a Tabular Vector Borne Disease Dataset
12514,127875513,486.0,0.3002207505518763,16,46,/nazimcherpanov/s3e13-xgboost-catboost,Classification with a Tabular Vector Borne Disease Dataset
12515,127854049,327.0,0.3774834437086093,0,6,/aonzahaha/ps-ss3-e13-xgb,Classification with a Tabular Vector Borne Disease Dataset
12516,128336565,371.0,,2,5,/shashankjat10/roti-sabji-vector-borne-predictions,Classification with a Tabular Vector Borne Disease Dataset
12517,127917612,273.0,0.3807947019867551,0,2,/lenferdetroud/ps-ss3-e13-eda,Classification with a Tabular Vector Borne Disease Dataset
12518,126673324,77.0,,0,1,/baokar7/ps-s3e13-why-the-columns-shouldn-t-be-dropped,Classification with a Tabular Vector Borne Disease Dataset
12519,127802245,23.0,,2,13,/eryaww/mapk-ensembling-submissions,Classification with a Tabular Vector Borne Disease Dataset
12520,127921685,149.0,0.4072847682119206,0,1,/ricopue/s3-p13-siamese,Classification with a Tabular Vector Borne Disease Dataset
12521,127857098,35.0,,0,3,/neosh11/help-data-engineering-catboost,Classification with a Tabular Vector Borne Disease Dataset
12522,127892896,361.0,0.370860927152318,2,6,/ytharth/tabular-vector-born-disease,Classification with a Tabular Vector Borne Disease Dataset
12523,126815948,214.0,0.3686534216335542,1,1,/kenjif/ps-3-13-0422-xgboost,Classification with a Tabular Vector Borne Disease Dataset
12524,128004723,31.0,,3,14,/tolgayan/31-solution-language-modeling-for-tabular-data,Classification with a Tabular Vector Borne Disease Dataset
12525,128092268,99.0,,0,4,/jmascacibar/tabular-vector-borne-disease-private-score-0-49561,Classification with a Tabular Vector Borne Disease Dataset
12526,126458447,458.0,0.391832229580574,2,8,/mahsazamanifard/s03e13-eda-single-model-baseline,Classification with a Tabular Vector Borne Disease Dataset
12527,127811396,28.0,,0,0,/masayamitsushio/baseline,Classification with a Tabular Vector Borne Disease Dataset
12528,127987852,119.0,,0,0,/oksanalutz/ps-s3e13-fe-and-catboost-keep-all,Classification with a Tabular Vector Borne Disease Dataset
12529,127740675,277.0,0.3432671081677705,1,24,/cv13j0/classification-with-a-tabular-vbd-using-gbdt,Classification with a Tabular Vector Borne Disease Dataset
12530,126895553,196.0,,1,1,/jenifar/episode-13-votingclassifier,Classification with a Tabular Vector Borne Disease Dataset
12531,127601023,451.0,0.3565121412803533,0,0,/animeshrockn/playground-3-13-lrmodel,Classification with a Tabular Vector Borne Disease Dataset
12532,127060218,234.0,,0,2,/smjishanulislam/classification-with-a-tabular-vector-borne-disease,Classification with a Tabular Vector Borne Disease Dataset
12533,126886039,89.0,,2,7,/eleonoraricci/feature-selection-mutual-information-score,Classification with a Tabular Vector Borne Disease Dataset
12534,127312117,64.0,,0,9,/demko1/logisticregression-symptom-importances,Classification with a Tabular Vector Borne Disease Dataset
12535,128025497,328.0,,0,2,/irda22/ps-s3e13-svc-model,Classification with a Tabular Vector Borne Disease Dataset
12536,129304670,629.0,0.380794701986755,0,6,/rfeng12/s3e13-basic-solution-with-decent-error,Classification with a Tabular Vector Borne Disease Dataset
12537,127540113,506.0,,6,35,/iqbalsyahakbar/ps3e13-simple-eda-pca-and-model-for-beginners,Classification with a Tabular Vector Borne Disease Dataset
12538,126870605,255.0,0.381898454746137,2,11,/docxian/ps-s3-e13-disease-classifier-visuals-glm-in-r,Classification with a Tabular Vector Borne Disease Dataset
12539,126199220,585.0,,1,14,/gauravduttakiit/pss3e13-lazypredict,Classification with a Tabular Vector Borne Disease Dataset
12540,127848521,497.0,0.3940397350993379,0,0,/carlosaugustomar/episode-13-classification-with-a-tabular-vector,Classification with a Tabular Vector Borne Disease Dataset
12541,126444950,596.0,,8,34,/mattop/ps-s3-e13-important-features-for-each-disease,Classification with a Tabular Vector Borne Disease Dataset
12542,127789958,341.0,0.3918322295805741,0,0,/albertgalimov/now-i-have-new-phobias,Classification with a Tabular Vector Borne Disease Dataset
12543,126674291,284.0,0.3587196467991171,0,1,/keitashimizu21/firsteda-playground-series-season-3-episode-13,Classification with a Tabular Vector Borne Disease Dataset
12544,127888549,172.0,0.391832229580574,0,9,/jonasvanvinckenroye/s3e13-simple-svc-classifier,Classification with a Tabular Vector Borne Disease Dataset
12545,126556864,165.0,0.3907284768211922,0,4,/iniyatj/ps-s3e13-basic-notebook-logisticregression,Classification with a Tabular Vector Borne Disease Dataset
12546,128023859,11.0,0.381898454746137,0,3,/larsmadsen/11th-place-in-competition,Classification with a Tabular Vector Borne Disease Dataset
12547,127501780,82.0,0.3841059602649008,0,0,/eniidras/testing-several-classification-models,Classification with a Tabular Vector Borne Disease Dataset
12548,126645655,507.0,,4,15,/patriciabrezeanu/eda-feature-engineering-and-model-submission,Classification with a Tabular Vector Borne Disease Dataset
12549,127868415,547.0,0.3763796909492274,0,3,/rmcabato/s3e13-removing-features-with-low-variance,Classification with a Tabular Vector Borne Disease Dataset
12550,126928740,43.0,,5,5,/charunumesh/ps-s3-e13-eda-modeling,Classification with a Tabular Vector Borne Disease Dataset
12551,128000263,276.0,,0,0,/tolgaik/ps-s3-e13-xgbclassifier-score-0-47368,Classification with a Tabular Vector Borne Disease Dataset
12552,126322559,415.0,0.337748344370861,0,1,/daskoushik/ps-s3-e13,Classification with a Tabular Vector Borne Disease Dataset
12553,127004071,461.0,,3,6,/alessandrozanette/s3e13-eda-and-xgboost-with-r,Classification with a Tabular Vector Borne Disease Dataset
12554,127790964,118.0,0.3730684326710818,0,4,/anantbansal1223/s3-e13-vector-borne-prediction,Classification with a Tabular Vector Borne Disease Dataset
12555,126694769,56.0,0.3807947019867551,0,0,/andreaskaufmann/s3e13-models-svc,Classification with a Tabular Vector Borne Disease Dataset
12556,127372364,140.0,,0,2,/caiocsn2/clustering-symptoms-patterns,Classification with a Tabular Vector Borne Disease Dataset
12557,127949125,109.0,0.3620309050772627,0,4,/abhinavmangalore/s3-e13-vector-borne-prediction-simple-ann,Classification with a Tabular Vector Borne Disease Dataset
12558,127889948,455.0,0.3785871964679912,6,5,/neupane9sujal/ps3e13-ensemble-cb-xgb-lgbm-rf,Classification with a Tabular Vector Borne Disease Dataset
12559,127527406,173.0,0.3830022075055189,0,4,/mewmlelswm/s3e13-xgboost-v2-cv0-38300,Classification with a Tabular Vector Borne Disease Dataset
12560,127789001,528.0,0.3830022075055188,0,4,/slythe/alternative-libraries-multiclass-xbnet-pyod,Classification with a Tabular Vector Borne Disease Dataset
12561,128217309,4.0,,1,8,/mateuszgrzybpl/4-solution-randomforrest-optuna-oob-score,Classification with a Tabular Vector Borne Disease Dataset
12562,162516003,653.0,0.3543046357615895,0,34,/kapturovalexander/kapturov-s-playground-series-s3-e13,Classification with a Tabular Vector Borne Disease Dataset
12563,127359304,151.0,0.3543046357615894,4,5,/d3stron/disease-prediction-using-pytorch-and-neural-nets,Classification with a Tabular Vector Borne Disease Dataset
12564,126684554,436.0,0.3719646799116999,0,0,/bianchimario/vector-borne-disease-dataset-ps-s3-e13-svc,Classification with a Tabular Vector Borne Disease Dataset
12565,126806542,189.0,,1,8,/deshram/ps-s3-e13-simple-eda-submission,Classification with a Tabular Vector Borne Disease Dataset
12566,127847215,75.0,0.3543046357615895,0,4,/mnokno/vectorbornediseaseprediction,Classification with a Tabular Vector Borne Disease Dataset
12567,126419973,417.0,0.3697571743929361,0,4,/aasnegha/simple-dimensionreduction-modelselection,Classification with a Tabular Vector Borne Disease Dataset
12568,127500676,249.0,0.3741721854304637,0,2,/ivanvaccari/voting-approach-with-tuning-algorithm,Classification with a Tabular Vector Borne Disease Dataset
12569,126454933,642.0,,0,3,/nakulshahdadpuri314/basic-eda-with-sample-submission,Classification with a Tabular Vector Borne Disease Dataset
12570,126252097,622.0,0.3730684326710817,0,6,/abocadobaby/does-oversampling-improve-model-performance,Classification with a Tabular Vector Borne Disease Dataset
12571,127434586,159.0,,6,7,/vishweshhampali/ps-s3e13-one-vs-rest-using-logistic-regression,Classification with a Tabular Vector Borne Disease Dataset
12572,127871244,69.0,0.3686534216335542,0,1,/furstenwald/xgboost-optuna-vector-borne-disease,Classification with a Tabular Vector Borne Disease Dataset
12573,127184742,583.0,,1,8,/jankuper192/map-k-in-r-umap-h20-medical-approach-idf,Classification with a Tabular Vector Borne Disease Dataset
12574,126958114,623.0,0.3355408388520972,2,9,/jimgruman/season3episode13,Classification with a Tabular Vector Borne Disease Dataset
12575,127397673,676.0,0.359823399558499,0,3,/kaizen97/v0-predictions,Classification with a Tabular Vector Borne Disease Dataset
12576,127199908,498.0,,0,1,/yusuphmustaphaladi/multiple-algorithms-and-feature-engineering,Classification with a Tabular Vector Borne Disease Dataset
12577,126892377,215.0,,0,4,/sourabhk382/ps-s3-13-simple-xgb-10-new-features,Classification with a Tabular Vector Borne Disease Dataset
12578,126961472,651.0,,0,0,/marvy00/tabular-vector-borne-disease,Classification with a Tabular Vector Borne Disease Dataset
12579,126411610,620.0,0.3543046357615895,2,6,/yashgoo018/kneighbours-with-map-3-and-feature-selection,Classification with a Tabular Vector Borne Disease Dataset
12580,138159277,662.0,,3,17,/gkitchen/vector-borne-disease-prediction,Classification with a Tabular Vector Borne Disease Dataset
12581,126581952,600.0,0.3476821192052981,0,6,/paulreiners/xgb-classifier-playground-series-s3e13,Classification with a Tabular Vector Borne Disease Dataset
12582,126300414,17.0,,6,22,/mpwolke/small-bite-0n-vector-borne-diseases,Classification with a Tabular Vector Borne Disease Dataset
12583,128077727,548.0,,0,0,/burakarslan1/s3e13,Classification with a Tabular Vector Borne Disease Dataset
12584,126368137,580.0,0.3498896247240619,0,1,/hosseinbehjat/lightgbm-hp-optimization-optuna-repeatedkfold,Classification with a Tabular Vector Borne Disease Dataset
12585,129242696,228.0,,10,30,/akioonodera/ps-3-13-lgbm-multiclass,Classification with a Tabular Vector Borne Disease Dataset
12586,158506063,592.0,,8,18,/keenanzhuo/pss3e13-disease-prediction-for-n00bz,Classification with a Tabular Vector Borne Disease Dataset
12587,127698366,844.0,0.3355408388520972,0,0,/matthewsfarmer/ps-s3-13,Classification with a Tabular Vector Borne Disease Dataset
12588,127147303,492.0,0.2980132450331126,1,5,/sahilkumar101/ps3e13-nn,Classification with a Tabular Vector Borne Disease Dataset
12589,126699265,444.0,0.3233995584988963,1,22,/jonbown/feature-testing-pipeline-ps-s3e13,Classification with a Tabular Vector Borne Disease Dataset
12590,126306166,550.0,,18,114,/wlifferth/generating-map-k-predictions,Classification with a Tabular Vector Borne Disease Dataset
12591,126571090,803.0,,0,4,/saketh2992/stacking-and-other-ml-models,Classification with a Tabular Vector Borne Disease Dataset
12592,127855047,474.0,,0,14,/robikscube/tabular-playground-quickeda,Classification with a Tabular Vector Borne Disease Dataset
12593,127533423,656.0,0.3245033112582781,0,4,/nishantdahal/classification-with-a-tabular-vector-borne-disease,Classification with a Tabular Vector Borne Disease Dataset
12594,126664290,337.0,0.3200883002207506,2,1,/harrshsinghhh/notebook345fdf9aad,Classification with a Tabular Vector Borne Disease Dataset
12595,126293716,845.0,0.2913907284768212,0,3,/crimsoneer/initial-exploration-and-rf-classification,Classification with a Tabular Vector Borne Disease Dataset
12596,127157387,866.0,0.1854304635761589,0,4,/muhriddinmalik/classification-with-a-tvbd-notebook,Classification with a Tabular Vector Borne Disease Dataset
12597,127959533,799.0,,1,4,/soraharada/play-s3e13-modeling,Classification with a Tabular Vector Borne Disease Dataset
12598,126548894,781.0,0.2582781456953642,0,3,/tracyporter/play-3-13-tf-dnn,Classification with a Tabular Vector Borne Disease Dataset
12599,127392367,774.0,0.2582781456953642,0,2,/smritirani/s3e13,Classification with a Tabular Vector Borne Disease Dataset
12600,127088040,771.0,0.2317880794701986,0,0,/vladlee/s3e13-rfc-optuna,Classification with a Tabular Vector Borne Disease Dataset
12601,126774094,836.0,,0,8,/jeevabharathis/ps-s3e13-eda-and-submission,Classification with a Tabular Vector Borne Disease Dataset
12602,126821661,730.0,,0,1,/averma111/ps3e13-map-k-tensorflow,Classification with a Tabular Vector Borne Disease Dataset
12603,127841947,906.0,0.2240618101545253,0,2,/barbagrande007/bbg007-s3e3-diseases,Classification with a Tabular Vector Borne Disease Dataset
12604,128177016,728.0,,0,3,/dhlongg/classification-with-a-tabular-vector-borne-disease,Classification with a Tabular Vector Borne Disease Dataset
12605,126254611,779.0,,8,16,/dekomorisanae09/pse13-simple-eda-and-randomforrest,Classification with a Tabular Vector Borne Disease Dataset
12606,129071932,788.0,0.0,0,1,/dharshinisankarraj/classification-with-a-vector-borne-disease,Classification with a Tabular Vector Borne Disease Dataset
12607,126451316,762.0,,0,15,/panini92/playground-s3e13-eda-random-forest,Classification with a Tabular Vector Borne Disease Dataset
12608,127389268,797.0,0.0794701986754966,0,4,/stpeteishii/pss3-ep13-visualize-importance,Classification with a Tabular Vector Borne Disease Dataset
12609,127127040,722.0,,0,2,/aman7kumar/vector-borne-disease-multi,Classification with a Tabular Vector Borne Disease Dataset
12610,127830873,759.0,0.2185430463576159,8,21,/richeyjay/classification-of-vector-borne-disease-s-eda,Classification with a Tabular Vector Borne Disease Dataset
12611,127772531,849.0,,0,0,/romrawinchumpu/ps-s3e13-vector-borne-diseases,Classification with a Tabular Vector Borne Disease Dataset
12612,126935944,888.0,,0,5,/jaloeffe92/vector-borne-disease-dataset-baselinesubmission,Classification with a Tabular Vector Borne Disease Dataset
12613,127945865,790.0,,0,1,/yagelosergey/classification-with-a-tabular-vector-borne-disease,Classification with a Tabular Vector Borne Disease Dataset
12614,126570881,927.0,,2,2,/pradeepsapparapu/ps-s3-ep13-eda-modeling-submission,Classification with a Tabular Vector Borne Disease Dataset
12615,135458405,4.0,,0,0,/adarshr/get-pubmed-ids-of-protein-sequences-test,CAFA 5 Protein Function Prediction
12616,155625443,13.0,,0,2,/ogurtsov/esm2-correct-embeds,CAFA 5 Protein Function Prediction
12617,134529074,14.0,,2,39,/szabo7zoltan/combineembeddings,CAFA 5 Protein Function Prediction
12618,133918711,18.0,,4,84,/thedrcat/cafa-5-protein-function-prediction-eda,CAFA 5 Protein Function Prediction
12619,127872367,29.0,,0,13,/andreylalaley/esm-embeds-calculation,CAFA 5 Protein Function Prediction
12620,126825105,35.0,,3,10,/insiyajafferji/cafa5-protein-data-explore,CAFA 5 Protein Function Prediction
12621,134713801,38.0,,0,6,/lnalinaf/protein-localization-and-organism-cafa5,CAFA 5 Protein Function Prediction
12622,137012724,68.0,,2,6,/hiroshikono/create-top1000-eda-about-term-frequency,CAFA 5 Protein Function Prediction
12623,134814805,72.0,,1,29,/bibanh/lb-0-53171-tuning-merge-datasets-w-higher-top,CAFA 5 Protein Function Prediction
12624,140502751,76.0,0.5348533333333333,0,1,/abhranta/merge-datasets-76,CAFA 5 Protein Function Prediction
12625,136205048,106.0,,0,0,/xiaofanglzu/info442-team1-data-eda,CAFA 5 Protein Function Prediction
12626,147695865,122.0,,0,34,/siddhvr/cafa-5-t5-embeds,CAFA 5 Protein Function Prediction
12627,136224003,127.0,,0,3,,CAFA 5 Protein Function Prediction
12628,140620327,129.0,,0,3,/kononenko/cafa5-competition-statistics,CAFA 5 Protein Function Prediction
12629,138671685,132.0,,0,8,/sebastian157/pytorch-01-basics-3a6104,CAFA 5 Protein Function Prediction
12630,143621383,157.0,,0,2,/kumarmukul03/protein-function-prediction-dataset,CAFA 5 Protein Function Prediction
12631,132824523,177.0,,0,8,/dplg007/cafa-5-2,CAFA 5 Protein Function Prediction
12632,138303429,187.0,,0,5,/ilyasokolov/pytorch-01-basics,CAFA 5 Protein Function Prediction
12633,131796435,195.0,,6,19,/joonyoungjang/multi-input-model-with-t5-taxonomy,CAFA 5 Protein Function Prediction
12634,155895817,247.0,,1,3,/vipin20/cafa-5-leaderboard-shakeup,CAFA 5 Protein Function Prediction
12635,131422427,290.0,,0,6,/horikitasaku/linernet-for-protein-pytorch-prott5-embeddings,CAFA 5 Protein Function Prediction
12636,126598655,350.0,,6,11,/nhgiang/prepare-data-for-proteinbert,CAFA 5 Protein Function Prediction
12637,133881804,366.0,,0,5,/ancaco12/eda-of-embeddings-clustering-t5-and-ems2,CAFA 5 Protein Function Prediction
12638,127513515,382.0,,0,10,/asiknow/load-and-explore-taxonomy-information,CAFA 5 Protein Function Prediction
12639,127589779,392.0,,0,22,/viktorfairuschin/extracting-esm-2-embeddings-from-fasta-files,CAFA 5 Protein Function Prediction
12640,136494182,419.0,,0,0,/junglebeastds/vectorize-go-labels-cco,CAFA 5 Protein Function Prediction
12641,127152871,424.0,,1,31,/geraseva/keops-knn,CAFA 5 Protein Function Prediction
12642,135141939,442.0,0.49481,0,16,/kirilldubovik/cafa5-tuning-merge-datasets,CAFA 5 Protein Function Prediction
12643,135184183,443.0,,0,2,/anyuanay/first-eda-of-cafa-5-protein-function-data,CAFA 5 Protein Function Prediction
12644,126903640,460.0,,5,43,/danofer/cafa-protein-implicit-tfrs-recommender-baseline,CAFA 5 Protein Function Prediction
12645,130172988,494.0,,2,5,/salmaneunus/molecular-machine-learning-with-deep-chem-part-1,CAFA 5 Protein Function Prediction
12646,135895623,506.0,0.4931766666666666,0,12,/nikolenkosergei/cafa-5,CAFA 5 Protein Function Prediction
12647,137732971,513.0,0.4931766666666666,1,7,/directioner/cafa-5-one,CAFA 5 Protein Function Prediction
12648,134063325,537.0,,5,31,/daehunbae/esm-2-3b-embeddings-with-three-pooling-methods,CAFA 5 Protein Function Prediction
12649,137532566,555.0,,0,0,/mimiqiu/notebook5654d8f5f6,CAFA 5 Protein Function Prediction
12650,136308763,571.0,,0,3,/haiiele/eda-of-cafa-5-protein-function-data-w1,CAFA 5 Protein Function Prediction
12651,128091695,590.0,,1,7,/aesoptacit/en-ja-simple-data-check,CAFA 5 Protein Function Prediction
12652,154521630,703.0,,0,4,/holmes0610/cafa5-baseline,CAFA 5 Protein Function Prediction
12653,135171261,735.0,,0,0,/yaram26/simple-mlp-v1,CAFA 5 Protein Function Prediction
12654,138665608,811.0,,0,1,/willrankine/cafa-5-protein-function-with-tensorflow,CAFA 5 Protein Function Prediction
12655,139866478,840.0,,0,2,/suzzystranger/cafa-eda-subset-for-transfer-learning,CAFA 5 Protein Function Prediction
12656,137242603,842.0,,81,207,/henriupton/proteinet-pytorch-ems2-t5-protbert-embeddings,CAFA 5 Protein Function Prediction
12657,138087097,844.0,,0,7,/ednaadissu/cafa-5-protein-function-practice,CAFA 5 Protein Function Prediction
12658,131666649,848.0,,0,5,/cafelatte1/cafa-eda-target-v1,CAFA 5 Protein Function Prediction
12659,140641862,878.0,,0,1,/giorgosfoukarakis/cafa5-prott5-embeddings-clustering-prediction,CAFA 5 Protein Function Prediction
12660,130918903,894.0,,0,3,/stomar21/eda-cafa-5-protein-function-analysis,CAFA 5 Protein Function Prediction
12661,140725873,910.0,,0,1,/santanubanerjee9/proteins-mapped-to-go-tree-tf-keras-cafa-5,CAFA 5 Protein Function Prediction
12662,127302864,939.0,,0,5,/mohamedmaattallah/cafa-protein-prediction,CAFA 5 Protein Function Prediction
12663,136860451,954.0,,0,2,/matthewrenze/cafa5-attempt-1b,CAFA 5 Protein Function Prediction
12664,129079694,982.0,0.4671,0,10,/ganeshborkar31/protein-function-prediction,CAFA 5 Protein Function Prediction
12665,139272407,1042.0,,0,6,/connorbost/lnn-and-cnn-for-cafa-5-challenge,CAFA 5 Protein Function Prediction
12666,126881431,1047.0,,1,8,/visualcomments/uniprot-description-embeddings,CAFA 5 Protein Function Prediction
12667,131525885,1097.0,,6,23,/averma111/pytorch-cafa-5-prediction,CAFA 5 Protein Function Prediction
12668,140609045,1131.0,0.4601633333333333,0,2,/liamkell/cafa5-esm2-embed-pytorch,CAFA 5 Protein Function Prediction
12669,140609045,1131.0,0.4601633333333333,0,2,/liamkell/cafa5-esm2-embed-pytorch,CAFA 5 Protein Function Prediction
12670,139197956,1139.0,0.4589366666666666,0,2,/shivaiyer129/cafa-5-protein-function-prediction,CAFA 5 Protein Function Prediction
12671,134865863,1148.0,,0,7,/dmitryshibaev/get-terms-by-ngram-statistics,CAFA 5 Protein Function Prediction
12672,135180318,1168.0,,0,2,/abhay005/cafa-5-protein-function-with-tensorflow,CAFA 5 Protein Function Prediction
12673,138261598,1189.0,,0,3,/dustinthewind/validation-set-that-mimicks-the-evaluation-set-up,CAFA 5 Protein Function Prediction
12674,126907695,1214.0,,1,17,/dhruvkhatri/naive-submission-afa,CAFA 5 Protein Function Prediction
12675,134603337,1249.0,,0,7,/rachanabisht/cafa-comprehensive-eda,CAFA 5 Protein Function Prediction
12676,135878804,1253.0,,0,3,/sriramm2010/baseline-solution,CAFA 5 Protein Function Prediction
12677,130890090,1265.0,,0,3,/krishnanshagarwal/notebooke07f311747,CAFA 5 Protein Function Prediction
12678,130671737,1310.0,,34,210,/gusthema/cafa-5-protein-function-with-tensorflow,CAFA 5 Protein Function Prediction
12679,136207590,1405.0,,0,8,/pranavatote/go-protein-prediction-models,CAFA 5 Protein Function Prediction
12680,131293674,1411.0,,1,12,/vinitkp/r-eda-protein,CAFA 5 Protein Function Prediction
12681,137095128,1416.0,0.37477,0,3,/likhithadurusoju/cafa-5-protein-function-with-tensorflow,CAFA 5 Protein Function Prediction
12682,138899711,1423.0,,0,2,/jwk323/tokenizing-cafa5-dataset,CAFA 5 Protein Function Prediction
12683,135708247,1454.0,0.2927466666666666,0,11,/ashishjagdishsharma/cafa-5-protein-function-prediction,CAFA 5 Protein Function Prediction
12684,133631035,1466.0,,1,5,/tardism/simple-embedding-with-tensorflow,CAFA 5 Protein Function Prediction
12685,129734462,1482.0,,1,6,/anhquangphan/kpc-protein-component,CAFA 5 Protein Function Prediction
12686,130716018,1490.0,,0,4,/alexanderpov/cafa-5-protein-niasia-alexander-isa-e-eduardo,CAFA 5 Protein Function Prediction
12687,133118992,1500.0,,0,2,/piquenopadawan/notebookc6436ae147,CAFA 5 Protein Function Prediction
12688,128011561,1513.0,,7,48,/yash161101/simple-naive-approach-make-your-first-submission,CAFA 5 Protein Function Prediction
12689,127769217,1514.0,0.1781266666666666,0,5,/rookieaj1234/basic-eda-on-train-terms,CAFA 5 Protein Function Prediction
12690,140605917,1540.0,0.14035,0,1,/preethipoov/cafa5-protein-function-prediction-using-dnn,CAFA 5 Protein Function Prediction
12691,137413976,1565.0,,0,3,/n3n77i/cafa5-init,CAFA 5 Protein Function Prediction
12692,140198001,1620.0,,0,8,/alijalali4ai/cafa5-sequence-feature-extraction-by-r-packages,CAFA 5 Protein Function Prediction
12693,139316588,2.0,0.725746231003653,2,10,/theoviel/contrails-inference-comb,Google Research - Identify Contrails to Reduce Global Warming
12694,140674380,3.0,0.7165904446823003,0,0,/yoichi7yamakawa/later-sub-y-223-227v2-241-237-240-234-228etc,Google Research - Identify Contrails to Reduce Global Warming
12695,139410600,1.0,0.7194728839330968,0,4,/junkoda/contrails-submit,Google Research - Identify Contrails to Reduce Global Warming
12696,130777557,11.0,0.4942623154855251,5,40,/phoenix9032/inference-unet-effnetb0-on-ash-v2-baseline,Google Research - Identify Contrails to Reduce Global Warming
12697,133853344,5.0,,0,0,/wuliaokaola/icrgw-train-single-ash-768-512-efv2l-0617,Google Research - Identify Contrails to Reduce Global Warming
12698,140172785,4.0,0.7104371607004367,0,5,/selimsef/kdl-unet-768-inference-contrails,Google Research - Identify Contrails to Reduce Global Warming
12699,133322959,24.0,0.6184196464829974,11,76,/egortrushin/gr-icrgw-pytorch-lightning-baseline-unet-resnest,Google Research - Identify Contrails to Reduce Global Warming
12700,139432132,9.0,0.7130129303959537,0,12,/tascj0/contrail-submit,Google Research - Identify Contrails to Reduce Global Warming
12701,134162499,33.0,,7,30,/sergiosaharovskiy/google-contrails-2023-eda,Google Research - Identify Contrails to Reduce Global Warming
12702,136134456,26.0,,6,90,/shashwatraman/simple-unet-pytorch-baseline-train,Google Research - Identify Contrails to Reduce Global Warming
12703,139486256,52.0,,0,4,/allunia/potential-leakage-between-folds-and-test,Google Research - Identify Contrails to Reduce Global Warming
12704,132485058,124.0,,0,6,/mawanda/mdice-metric-pure-pytorch,Google Research - Identify Contrails to Reduce Global Warming
12705,129197000,30.0,,0,9,/edomingo/identify-contrails-quick-file-exploration,Google Research - Identify Contrails to Reduce Global Warming
12706,133962227,95.0,,0,6,/takaito/gr-icrgw-make-table-data,Google Research - Identify Contrails to Reduce Global Warming
12707,140447868,73.0,,0,1,/raki21/multi-scale-ensembler-inference,Google Research - Identify Contrails to Reduce Global Warming
12708,136166079,28.0,,0,2,/welshonionman/dataset-ashcolor-4labels,Google Research - Identify Contrails to Reduce Global Warming
12709,130181011,63.0,,6,18,/patchef/hdf5-dataset-google-contrails-v2,Google Research - Identify Contrails to Reduce Global Warming
12710,138586658,137.0,,3,31,/tomokihirose/visualize-metadata-by-convert-to-lat-lon,Google Research - Identify Contrails to Reduce Global Warming
12711,130612163,150.0,,0,0,/hsdistefa/contrails-naive-submission,Google Research - Identify Contrails to Reduce Global Warming
12712,134687856,109.0,0.6045819828619633,4,22,/myso1987/ic2rgw-pytorch-baseline-train-inference,Google Research - Identify Contrails to Reduce Global Warming
12713,139292594,318.0,,0,1,/jordibeltranperello/model-predictions-visualization-test-dice-0-66,Google Research - Identify Contrails to Reduce Global Warming
12714,139437816,188.0,0.6551899181178132,0,15,/royalacecat/pesudo-shake-shake-up,Google Research - Identify Contrails to Reduce Global Warming
12715,130055258,248.0,0.0025931883780743,0,0,/ksmcg90/dummy-sub,Google Research - Identify Contrails to Reduce Global Warming
12716,138102745,174.0,0.6490634540803697,0,0,/waechter/identify-contrail-submit-stack,Google Research - Identify Contrails to Reduce Global Warming
12717,129662422,438.0,,0,7,/alabibojesomo/extreme-dataset-and-sample-loading-for-contrails,Google Research - Identify Contrails to Reduce Global Warming
12718,135346238,516.0,0.3090999914714232,2,16,/manishkumar7432698/baseline-ml-score-0-413,Google Research - Identify Contrails to Reduce Global Warming
12719,136337200,436.0,,0,3,/cmsm12/contrails-mmsegmentation-dataset-notebook,Google Research - Identify Contrails to Reduce Global Warming
12720,130846923,172.0,,2,25,/thomasrochefort/contrails-pytorch-dataloader-example,Google Research - Identify Contrails to Reduce Global Warming
12721,133027664,381.0,,0,5,/melgor/benchmark-numpy-vs-jpeg,Google Research - Identify Contrails to Reduce Global Warming
12722,132989746,593.0,,0,10,/giriprasad512/contrails-preprocessing-with-hsv,Google Research - Identify Contrails to Reduce Global Warming
12723,137503011,702.0,,0,3,/fynnjunge/contrails-apply-model-on-all-timesteps,Google Research - Identify Contrails to Reduce Global Warming
12724,132470107,288.0,0.5521208897294955,0,9,/egorfokin/contrails-tensorflow-train-submission-public,Google Research - Identify Contrails to Reduce Global Warming
12725,130444745,754.0,,1,17,/lupin11/40min-data-preprocess,Google Research - Identify Contrails to Reduce Global Warming
12726,132441504,691.0,,0,36,/janhuebi/unet-pytorch-baseline-lb-0-608-training,Google Research - Identify Contrails to Reduce Global Warming
12727,139310330,679.0,,12,25,/suraj520/manet-multi-attention-network-for-remote-sensing,Google Research - Identify Contrails to Reduce Global Warming
12728,134776281,622.0,,4,23,/bibanh/lb-0-623-resnet26d-unet-training,Google Research - Identify Contrails to Reduce Global Warming
12729,135587560,707.0,0.6047812595603339,1,0,/yumemita/predict-unet,Google Research - Identify Contrails to Reduce Global Warming
12730,133571113,775.0,,0,11,/byungeunhwang/simple-unet-baseline-with-comments-added,Google Research - Identify Contrails to Reduce Global Warming
12731,136624103,789.0,0.3933064467585626,0,3,/crustacean/inference-fastai-baseline,Google Research - Identify Contrails to Reduce Global Warming
12732,136624103,789.0,0.4409118846734089,0,3,/crustacean/inference-fastai-baseline,Google Research - Identify Contrails to Reduce Global Warming
12733,131999878,788.0,,0,5,/kalyansekhar07/pytorch-deeplabv3-model-with-submission,Google Research - Identify Contrails to Reduce Global Warming
12734,132410701,800.0,,2,11,/dinowun/eda-simplified-identifying-contrails-en-zh,Google Research - Identify Contrails to Reduce Global Warming
12735,129917380,827.0,,4,10,/soumyadeepkhandual/essentials-dataloader-plots-metrics-submission,Google Research - Identify Contrails to Reduce Global Warming
12736,132532797,843.0,,0,2,/fubusch/threshold-optimization,Google Research - Identify Contrails to Reduce Global Warming
12737,135125919,853.0,0.3095728094792641,0,2,/theadig/aditya,Google Research - Identify Contrails to Reduce Global Warming
12738,130486430,881.0,,1,11,/stpeteishii/contrails-data-view,Google Research - Identify Contrails to Reduce Global Warming
12739,130064609,900.0,,1,6,/proteekchaudhuri/unet-model-creation-and-submission-w-tensorflow,Google Research - Identify Contrails to Reduce Global Warming
12740,140110110,939.0,,0,2,/dominicimbuga/impact-on-climate-change,Google Research - Identify Contrails to Reduce Global Warming
12741,141352695,1.0,,0,1,/darraghdog/asl-fingerspelling-preprocessing-train,Google - American Sign Language Fingerspelling Recognition
12742,141916943,2.0,,0,0,/hoyso48/aslfr-create-tfr,Google - American Sign Language Fingerspelling Recognition
12743,141128987,3.0,,0,1,/goldenlock/3rd-place-step-6-inference,Google - American Sign Language Fingerspelling Recognition
12744,136162623,9.0,,1,10,/rafiko1/aslfr-animated-visualization,Google - American Sign Language Fingerspelling Recognition
12745,133726408,12.0,,6,24,/shlomoron/aslfr-parquets-to-tfrecords-cleaned,Google - American Sign Language Fingerspelling Recognition
12746,140975137,11.0,,0,0,/baohaoliao/aslfr-data-preprocessing,Google - American Sign Language Fingerspelling Recognition
12747,137149776,64.0,,0,1,/liuyixijia/notebook7de733580f,Google - American Sign Language Fingerspelling Recognition
12748,133281337,83.0,,0,8,/jiangjixiang/for-pytorch-summit,Google - American Sign Language Fingerspelling Recognition
12749,140991916,80.0,,0,3,/fritzcremer/asl-shakeup,Google - American Sign Language Fingerspelling Recognition
12750,131305294,100.0,,9,46,/irohith/aslfr-preprocess-dataset,Google - American Sign Language Fingerspelling Recognition
12751,139020943,136.0,,8,67,/mbmmurad/gaslfr-eda-visualization-evaluation-metric,Google - American Sign Language Fingerspelling Recognition
12752,132094787,178.0,,0,4,/something4kag/aslfr-transformer-irohith-tflite-runtime-2-14-0,Google - American Sign Language Fingerspelling Recognition
12753,133119677,313.0,,1,5,/seonokrkim/process-supplemental-dataset,Google - American Sign Language Fingerspelling Recognition
12754,139102499,320.0,0.6829046928487574,0,3,/doggeyoung/aslfr-ctc-based-on-prev-comp-1st-place-test,Google - American Sign Language Fingerspelling Recognition
12755,136784123,298.0,,3,4,/matthewkey/visual-google-asl-simple-animation-hands-only,Google - American Sign Language Fingerspelling Recognition
12756,138879608,123.0,,1,27,/embeddedravi/eda-visualize-asl-parquet-data-using-matplotlib,Google - American Sign Language Fingerspelling Recognition
12757,133680678,126.0,,14,133,/markwijkhuizen/aslfr-eda-preprocessing-dataset,Google - American Sign Language Fingerspelling Recognition
12758,136470040,499.0,,2,6,/greysky/levenshtein-distance-implementation,Google - American Sign Language Fingerspelling Recognition
12759,134497766,532.0,,0,4,/superb20/data-preprocessing-template-notebook,Google - American Sign Language Fingerspelling Recognition
12760,131574077,575.0,,0,1,/stk2666/aslfr-numpydatapreprocess-train,Google - American Sign Language Fingerspelling Recognition
12761,136096152,587.0,,1,0,/arieldrabkin/landmarks-to-images,Google - American Sign Language Fingerspelling Recognition
12762,130822779,816.0,0.0272721891739915,0,9,/longyikim/finger-first,Google - American Sign Language Fingerspelling Recognition
12763,131256722,609.0,,5,58,/anokas/static-greedy-baseline-0-157-lb,Google - American Sign Language Fingerspelling Recognition
12764,136128486,654.0,,0,7,/m4nugnzl/preprocessing-explained-in-spanish,Google - American Sign Language Fingerspelling Recognition
12765,136377035,697.0,,0,1,/mizaazir/asl-preprocessing,Google - American Sign Language Fingerspelling Recognition
12766,131598995,694.0,,0,1,/youssefouertani/data-gathering,Google - American Sign Language Fingerspelling Recognition
12767,132102463,718.0,,5,17,/mdecoster/edge-cases-and-local-inference,Google - American Sign Language Fingerspelling Recognition
12768,132615365,746.0,,0,0,/wenshuochen123/parquet,Google - American Sign Language Fingerspelling Recognition
12769,136017070,931.0,,0,6,/ahmedxc4/asl-fingerspelling-recognition-data,Google - American Sign Language Fingerspelling Recognition
12770,130826155,957.0,0.0,3,44,/wonderingalice/working-sample-submission-and-inference,Google - American Sign Language Fingerspelling Recognition
12771,138160805,958.0,,0,1,/noelsjacob/aslfr-tfrecord-datacleaning,Google - American Sign Language Fingerspelling Recognition
12772,132042221,1218.0,0.157136938056764,0,2,/ylogicmachine/american-fingers,Google - American Sign Language Fingerspelling Recognition
12773,134315178,1222.0,,2,15,/victordumetz/gaslfr-svg-visualisation,Google - American Sign Language Fingerspelling Recognition
12774,131786580,1246.0,,0,8,/vinitkp/r-eda-sign-language,Google - American Sign Language Fingerspelling Recognition
12775,130835950,1263.0,,4,9,/alexis1024/fixed-random-dummy-submission,Google - American Sign Language Fingerspelling Recognition
12776,131314285,1284.0,0.0,10,32,/jocelyndumlao/asl-fingerspelling-accuracy-w-levenshtein-dist,Google - American Sign Language Fingerspelling Recognition
12777,132176795,1290.0,,0,8,/stoonbelly/fingerspelling-exploratory-analyses,Google - American Sign Language Fingerspelling Recognition
12778,130729395,1291.0,,1,6,/smackcrane/gasfr-simple-animated-visualization,Google - American Sign Language Fingerspelling Recognition
12779,130753675,806.0,0.2790633352795671,31,133,/cdeotte/rapids-cuml-svc-baseline-lb-0-27-cv-0-35,ICR - Identifying Age-Related Conditions
12780,139642290,805.0,0.2246186824406202,2,21,/vitalykudelya/gold-medal-top-4-8-18-lines-of-code-late-sub,ICR - Identifying Age-Related Conditions
12781,130152943,6309.0,,0,6,/shivamanhar/first-model-submission,ICR - Identifying Age-Related Conditions
12782,131211193,2404.0,,29,131,/raddar/convert-icr-data-to-integers,ICR - Identifying Age-Related Conditions
12783,131355411,4747.0,,1,43,/ulrich07/tabfpn-and-xgboost-cv-0-19-lb-0-17,ICR - Identifying Age-Related Conditions
12784,138519019,6268.0,1.9445930807858949,0,1,,ICR - Identifying Age-Related Conditions
12785,134053689,5969.0,,1,27,/abhranta/permutation-testing-validation-of-learning,ICR - Identifying Age-Related Conditions
12786,137690300,4952.0,,0,0,/aruaru0/icr-pycaret-infer-only,ICR - Identifying Age-Related Conditions
12787,131214251,5752.0,1.5127735596926497,4,6,/tomonorisasaki/prediction-and-comprehensive-eda,ICR - Identifying Age-Related Conditions
12788,130253447,6093.0,0.1889426600182272,14,122,/maverickss26/icr-age-related-conditions-eda-modelling,ICR - Identifying Age-Related Conditions
12789,137697318,412.0,0.0629443882884968,0,0,/zskagcomp/xgboost-tabpfn,ICR - Identifying Age-Related Conditions
12790,139527800,5728.0,0.8608300120665145,0,2,/gh0sthunter/missing-value-imputation,ICR - Identifying Age-Related Conditions
12791,133112496,6158.0,,0,6,/hechtjp/icr-eda-catboost-baseline,ICR - Identifying Age-Related Conditions
12792,133983702,5968.0,1.6399483814732307,0,0,/dplg007/icr-catboostclassifier-with-gridsearchcv,ICR - Identifying Age-Related Conditions
12793,139548191,3611.0,0.1797343096967446,1,5,/hideyukizushi/icr-train-inf-featurewiz-lgb-xgb-tabpfn,ICR - Identifying Age-Related Conditions
12794,139501144,4513.0,0.0645796363554881,0,0,/seojinpark2001/icr-iarc-greeks-prediction,ICR - Identifying Age-Related Conditions
12795,139213434,4457.0,0.1608751984137531,0,2,/shengxin/notebookd1f82bf363,ICR - Identifying Age-Related Conditions
12796,137624944,2625.0,0.8252748425671992,0,20,/chensilin/icr-eda-lightgbm-xgboost-optuna-lb-0-21,ICR - Identifying Age-Related Conditions
12797,136924324,5787.0,0.2866632303576822,0,0,/leehann/automl-icr,ICR - Identifying Age-Related Conditions
12798,130004583,5296.0,0.2109205448356781,1,8,/vinayaktiwari28/icr-first-version-with-some-tuning,ICR - Identifying Age-Related Conditions
12799,137149326,5546.0,0.2895999865278384,2,0,/ternarystorm/xgb-cv-0-24-lb-0-25,ICR - Identifying Age-Related Conditions
12800,133362860,6054.0,0.3534430172102507,0,9,/yuriao/icr-aging-with-lgbm,ICR - Identifying Age-Related Conditions
12801,131659521,3967.0,,14,43,/kenzi1323/note-how-to-solve-submission-error,ICR - Identifying Age-Related Conditions
12802,130548738,6069.0,,0,17,/henriupton/feature-selection-pytorch-mlp,ICR - Identifying Age-Related Conditions
12803,140702049,3345.0,0.2189129761305124,4,6,/gimgoon/icr-single-catboost-private-0-272-late-sub,ICR - Identifying Age-Related Conditions
12804,138077119,3160.0,0.2467937205103709,6,16,/christph/automl-full-workflow,ICR - Identifying Age-Related Conditions
12805,135477858,6246.0,0.0661340316511021,5,61,/byungeunhwang/added-comments-to-the-highest-scoring-public-codes,ICR - Identifying Age-Related Conditions
12806,134017578,4833.0,,38,111,/vaibhavjain2004/public-krni-pdi,ICR - Identifying Age-Related Conditions
12807,155111254,6238.0,,2,9,/siddhvr/icr-0-16-ensemble-fine-tune,ICR - Identifying Age-Related Conditions
12808,132564724,6174.0,0.1958787021581391,0,1,/jabreal/icr-age-related-disease-prediction,ICR - Identifying Age-Related Conditions
12809,138287549,6250.0,0.0659661094620338,0,21,/abhinavmangalore/icr-tabpfn-and-xgboost-ensemble,ICR - Identifying Age-Related Conditions
12810,138474792,6255.0,0.2114606748397849,0,0,/romanbraunstingl/icr-iarc-mk-ii-with-lbgm,ICR - Identifying Age-Related Conditions
12811,139546951,5375.0,0.0659661094620338,0,1,/mirenaborisova/icr-2,ICR - Identifying Age-Related Conditions
12812,137116600,2667.0,0.3837553957323016,0,0,/fivcan2/public-krni-pdi-with-two-additional-models,ICR - Identifying Age-Related Conditions
12813,135105288,2.0,,12,48,/opamusora/changed-threshold,ICR - Identifying Age-Related Conditions
12814,135466101,3778.0,0.0661340316511021,44,132,/vadimkamaev/postprocessin-ensemble,ICR - Identifying Age-Related Conditions
12815,138425308,633.0,,0,4,/kaggleqrdl/postprocessin-ensemble,ICR - Identifying Age-Related Conditions
12816,134734990,5955.0,0.7946156775369937,0,4,/shadowbrightness/icr-search,ICR - Identifying Age-Related Conditions
12817,139306075,17.0,0.1876809767372307,0,1,/markdjadchenko/slightly-modified-tabpfn,ICR - Identifying Age-Related Conditions
12818,134561732,5685.0,0.3894969814509861,4,4,/swapnilchowdhury/beginner-hyperparamter-tuned-xgboost-lb-0-35,ICR - Identifying Age-Related Conditions
12819,135526227,5916.0,0.8079124139094316,0,3,/lonnieqin/icr-prediction-with-keras,ICR - Identifying Age-Related Conditions
12820,131959659,5958.0,0.3834269593518709,2,9,/olemagnushiback/baseline-ensemble-model-with-tensorflow,ICR - Identifying Age-Related Conditions
12821,134748036,3087.0,,0,2,/timofeyefimov/framework-for-model-optimization,ICR - Identifying Age-Related Conditions
12822,132659898,1733.0,0.1172488660950111,10,28,/youneseloiarm/simple-tabpfn-approach-for-score-of-15-in-1-min,ICR - Identifying Age-Related Conditions
12823,132628072,5610.0,,0,5,/jiawen9/0-16-lgb,ICR - Identifying Age-Related Conditions
12824,132414416,5803.0,0.3234217849208096,4,1,/sharkyun/first-attempt-with-random-forest,ICR - Identifying Age-Related Conditions
12825,134887460,2970.0,0.3504425675396352,0,4,/yapwh1208/icr-competition-simple,ICR - Identifying Age-Related Conditions
12826,131112962,5821.0,,5,43,/nomuraryota/icr-identify-age,ICR - Identifying Age-Related Conditions
12827,135698046,5826.0,0.3263356061654824,0,0,/ejjjjjjjj/identifying-age-related-conditions-w-tfdf-a,ICR - Identifying Age-Related Conditions
12828,159514494,5829.0,,0,3,/volodymyrpivoshenko/ensemble-umap-tabfn-xgboost-catboost,ICR - Identifying Age-Related Conditions
12829,129488980,5100.0,0.4301444392165398,0,4,/muhammadishaque/filling-missing-values-and-adjusting-outliers,ICR - Identifying Age-Related Conditions
12830,137901871,769.0,,0,12,/asimandia/all-zeros-sub,ICR - Identifying Age-Related Conditions
12831,139583143,138.0,0.2102578452504648,0,2,/conradkrueger/6-depth-test,ICR - Identifying Age-Related Conditions
12832,136635649,5870.0,,7,24,/gokifujiya/icr-identifying-age-related-conditions-baseline,ICR - Identifying Age-Related Conditions
12833,133420384,4097.0,0.1172488701502303,0,0,/mengdeyu/icr-identify-age-0-11,ICR - Identifying Age-Related Conditions
12834,131324776,5849.0,0.2329394151041594,0,9,/smnuruzzaman/icr-catboost,ICR - Identifying Age-Related Conditions
12835,129388297,4556.0,,8,24,/jillanisofttech/baseline-with-best-accuracy,ICR - Identifying Age-Related Conditions
12836,138037960,5315.0,,3,7,/dinowun/eda-simplified-icr-age-rel-conditions-en-zh,ICR - Identifying Age-Related Conditions
12837,129259286,5856.0,0.3308106792635703,0,2,/andtaichi/icr-lightgbm-baseline,ICR - Identifying Age-Related Conditions
12838,131196999,1549.0,,0,3,/ryosukeyakura/230521-eda-optuna-lightgbm,ICR - Identifying Age-Related Conditions
12839,134664069,1098.0,0.5387221225645554,2,7,/renatoreggiani/xgb-blend,ICR - Identifying Age-Related Conditions
12840,134838118,2456.0,0.6645157651779788,0,1,/nkenyor/dream-model-icr,ICR - Identifying Age-Related Conditions
12841,135797185,507.0,0.4369934603686912,1,6,/diyorarti/predict-age-related-conditions,ICR - Identifying Age-Related Conditions
12842,139114422,2194.0,,2,35,/cody11null/icr-exploratory-data-analysis,ICR - Identifying Age-Related Conditions
12843,136274232,854.0,,20,50,/ravi20076/icr-bestpublicscore-metriccorrected,ICR - Identifying Age-Related Conditions
12844,139604741,2325.0,,0,9,/nihilisticneuralnet/icr-leaderboard-analysis,ICR - Identifying Age-Related Conditions
12845,134444235,2156.0,,1,2,/koreansim/new-baseline-0-23,ICR - Identifying Age-Related Conditions
12846,135916849,6101.0,0.1906405255837396,0,0,/romanleo2003/postprocessing-ensemble,ICR - Identifying Age-Related Conditions
12847,134800090,5174.0,0.0933356243197041,0,12,/bibanh/lb-0-08-7-folds-tabpfn-postprocessing,ICR - Identifying Age-Related Conditions
12848,133886454,5342.0,,0,1,/paidakang/xgb-lgb,ICR - Identifying Age-Related Conditions
12849,134635931,1600.0,,0,2,/stajdi/outliers-clusters-and-brute-force-features-extd,ICR - Identifying Age-Related Conditions
12850,135549507,5978.0,,0,1,/abdelkaderdebbaghi/two-steps-prediction,ICR - Identifying Age-Related Conditions
12851,136571472,4985.0,2.5437763721054525,0,3,/hinepo/icr-1-01,ICR - Identifying Age-Related Conditions
12852,136413241,6164.0,0.0661340316511021,0,30,/eishkaran/ensembling,ICR - Identifying Age-Related Conditions
12853,133527298,6168.0,,1,2,/jiangwendong/notebook0afaf21a25,ICR - Identifying Age-Related Conditions
12854,134729965,5237.0,0.3687890071864838,0,1,/teerrru/eda-random-forest,ICR - Identifying Age-Related Conditions
12855,130947162,6172.0,,0,8,/wksdnr123/let-s-gogo,ICR - Identifying Age-Related Conditions
12856,138275159,4569.0,0.8508341382867907,0,0,/ernestbeardlypani/icr-identifying-age-related-conditions-eda,ICR - Identifying Age-Related Conditions
12857,138834343,5897.0,1.8129533343426776,0,1,,ICR - Identifying Age-Related Conditions
12858,136233405,5616.0,0.3263356061654824,0,3,/bobber/identifying-age-related-conditions-w-tfdf,ICR - Identifying Age-Related Conditions
12859,133550682,3136.0,0.1762523078131371,3,15,/bilalafzal255/baseline-lightgbm,ICR - Identifying Age-Related Conditions
12860,136203348,2626.0,0.1732423921324604,0,0,/masahirofuruta/icr-20230629-f,ICR - Identifying Age-Related Conditions
12861,137590089,5655.0,,2,8,/awesomeharris/feature-selection-using-rfecv,ICR - Identifying Age-Related Conditions
12862,129918203,1662.0,,0,12,/aiaiaidavid/icr-baseline-xgboost-random-forest-and-shap,ICR - Identifying Age-Related Conditions
12863,136656704,967.0,,2,11,/glipko/class-imbalance-approaches-comparison,ICR - Identifying Age-Related Conditions
12864,137098663,6027.0,0.3058283506977849,0,7,/stefanouccelli/identifying-age-related-conditions-using-ensambles,ICR - Identifying Age-Related Conditions
12865,135873017,565.0,0.2223893078126239,53,107,/bennyfung/icr-0-17-knn-smote-xgboost-lgbm,ICR - Identifying Age-Related Conditions
12866,133814113,5597.0,,0,1,/ksevta/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
12867,137477452,2338.0,,3,8,/andreytikhomirov/icr-leaveoneout-cv,ICR - Identifying Age-Related Conditions
12868,139126003,672.0,,1,27,/samu2505/bagging,ICR - Identifying Age-Related Conditions
12869,130803891,5318.0,,0,0,/chenjiexu/icr-optimized-lgb,ICR - Identifying Age-Related Conditions
12870,139969143,1194.0,,0,7,/timetoti/icr-sample-impact-analysis,ICR - Identifying Age-Related Conditions
12871,137825586,2461.0,,0,0,/jabeva99/teci-diagnostico,ICR - Identifying Age-Related Conditions
12872,135757258,270.0,,0,5,/tsuyoshifujii/icr-eda-and-baseline,ICR - Identifying Age-Related Conditions
12873,139572161,1090.0,0.2384696415602387,0,1,/mrgarlicshrimp/icr-simple-lightgbm-private-lb-0-4,ICR - Identifying Age-Related Conditions
12874,139681325,2423.0,,2,11,/ammarahmadqazi/private-v-s-public-lb-data,ICR - Identifying Age-Related Conditions
12875,130492164,3400.0,0.3473143464432719,0,8,/leehomhuang/simple-xgb-without-greeks,ICR - Identifying Age-Related Conditions
12876,139294498,6216.0,0.0661340316511021,0,2,/yeuuuf/ensemble-try,ICR - Identifying Age-Related Conditions
12877,139862362,5932.0,0.2101249529985421,0,7,/rushali2406/icr-ensemble-with-optuna,ICR - Identifying Age-Related Conditions
12878,139573261,2287.0,,8,82,/emphymachine/private-gold-solution-svm-rf-xgb-kfold-ensemble,ICR - Identifying Age-Related Conditions
12879,130432285,1466.0,,0,9,/benjenkins96/icr-comprehensive-analysis,ICR - Identifying Age-Related Conditions
12880,134558175,636.0,0.3330208491344498,2,12,/pranavatote/xgboost-model-icr-prediction,ICR - Identifying Age-Related Conditions
12881,133693463,5085.0,,2,5,/tonychenxyz/feature-importance-eda,ICR - Identifying Age-Related Conditions
12882,132936027,2408.0,0.7399596054004621,7,51,/xb12345/icr-improve-based-on-icr-first-version,ICR - Identifying Age-Related Conditions
12883,152734297,4757.0,,4,20,/risakashiwabara/eda-sklearn-heatmap,ICR - Identifying Age-Related Conditions
12884,136865849,5993.0,,0,3,/johnabe/understanding-the-competition-cost-function,ICR - Identifying Age-Related Conditions
12885,138340805,1292.0,,0,6,/nathenwang/lgbm-and-data-augment,ICR - Identifying Age-Related Conditions
12886,139160301,5995.0,0.0920287692809296,0,0,/dannylin714/optimized-0-06-f5f34f,ICR - Identifying Age-Related Conditions
12887,138849222,3153.0,,7,29,/suraj520/soft-voting-strat-k-fold-optuna-rf-lgbm-xgb,ICR - Identifying Age-Related Conditions
12888,137354983,986.0,,1,7,/retroflake/elementary-eda,ICR - Identifying Age-Related Conditions
12889,137829658,5452.0,0.5373408821868517,0,15,/polyakovstepan/model-building,ICR - Identifying Age-Related Conditions
12890,132332115,5765.0,0.2449371729846211,0,0,/abdotohamy/icr-identify-age,ICR - Identifying Age-Related Conditions
12891,131570493,1410.0,0.4340037492647137,0,2,/mohamed3abdelrazik/icr-2023-baseline,ICR - Identifying Age-Related Conditions
12892,136348422,1757.0,0.1816643557696386,1,7,/yuezhoul/icr-xgb-tpn-with-cv-private-0-36-public-0-16,ICR - Identifying Age-Related Conditions
12893,136998372,4546.0,,1,1,/nyeongmin/public-krni-pdi-2xgb-2tabpfn,ICR - Identifying Age-Related Conditions
12894,139461255,4900.0,0.3433717877432626,1,3,/mohammedzayyad/lb-0-16-tf-xgboost,ICR - Identifying Age-Related Conditions
12895,130493477,6022.0,14.312594684739697,0,9,/umesalma/icr-logistic-regression-model,ICR - Identifying Age-Related Conditions
12896,130062985,110.0,,23,226,/datafan07/icr-simple-eda-baseline,ICR - Identifying Age-Related Conditions
12897,130531295,5138.0,0.2188152723208468,0,18,/haroldmei/simple-h2o-automl-solution,ICR - Identifying Age-Related Conditions
12898,134072917,5292.0,1.0617889947488792,0,0,/alex8554/normalizing-data,ICR - Identifying Age-Related Conditions
12899,129841476,612.0,0.2284213605695942,7,69,/tauilabdelilah/simple-baseline,ICR - Identifying Age-Related Conditions
12900,136378702,2359.0,,0,1,/murugesann/icr-bestpublicscore-metriccorrected-full-dataset,ICR - Identifying Age-Related Conditions
12901,132400765,3722.0,0.3113562755977675,0,0,/meiyuxin/notebook4ec6c171f0,ICR - Identifying Age-Related Conditions
12902,135176117,5462.0,,0,3,/dmitriygakh/icr-arc-beginner-xgboost,ICR - Identifying Age-Related Conditions
12903,131504524,2370.0,0.1969766771484532,9,53,/tatudoug/logistic-regression-baseline,ICR - Identifying Age-Related Conditions
12904,134904103,5491.0,0.0887747556317296,0,1,/finlay/public-krni-pdi-with-four-additional-models,ICR - Identifying Age-Related Conditions
12905,133592035,3457.0,,0,5,/charleschuang/baseline-randomforest-0-34-lb,ICR - Identifying Age-Related Conditions
12906,133202952,886.0,0.3964012079005156,0,3,/naiku007/age-ml-base-1,ICR - Identifying Age-Related Conditions
12907,133255025,2116.0,,2,13,/propriyam/icr-tabpfn-lgb-xgb-lb-0-17-cv-0-16,ICR - Identifying Age-Related Conditions
12908,137591333,1150.0,0.0946665836593566,0,7,/pentakrishnakishore/ncr-note3,ICR - Identifying Age-Related Conditions
12909,136007581,3629.0,,7,24,/junbai2022/the-interesting-things-about-beta-in-greeks,ICR - Identifying Age-Related Conditions
12910,132993480,5224.0,,0,3,/poskok/icrcompetition-dataanalysis,ICR - Identifying Age-Related Conditions
12911,134986804,1699.0,0.165600364862176,0,6,/hiroshisakiyama/icr-80-sim-tabpfn-privatelb-0-35,ICR - Identifying Age-Related Conditions
12912,135017767,357.0,0.113204097933701,0,1,/mohdsufiyan095/notebooka11cab4235,ICR - Identifying Age-Related Conditions
12913,130610073,1539.0,0.4939145839677029,0,4,/miyawakiyoshifumi/baseline-tabnet-model,ICR - Identifying Age-Related Conditions
12914,135004008,3109.0,,0,0,/act18l/smac-hyperparameter-tuning,ICR - Identifying Age-Related Conditions
12915,139303242,3317.0,0.1338583491015937,1,7,/pixelshooter/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
12916,137500458,4591.0,0.2007649816122501,5,14,/aliasgherman/logisticregression-and-catboost-simple-code,ICR - Identifying Age-Related Conditions
12917,134179874,23.0,,2,0,/yamitomo/please-help-my-cv-and-lb-are-different,ICR - Identifying Age-Related Conditions
12918,134322888,1813.0,0.1164997171952577,0,0,/manabiulina/tabpfn-postprocessing,ICR - Identifying Age-Related Conditions
12919,130467965,5286.0,,0,0,/mueid20/icr-preprocessed,ICR - Identifying Age-Related Conditions
12920,131627703,4916.0,0.4333242345333221,0,0,/evgeniyvigurskiy/icr-with-optuna-ipynb,ICR - Identifying Age-Related Conditions
12921,130928820,5113.0,,0,2,/ziwenwang0705/identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
12922,132070530,2435.0,,0,3,/adaubas/why-is-tabpfn-so-slow-to-do-predictions,ICR - Identifying Age-Related Conditions
12923,139503761,130.0,0.2090655032333394,0,0,/takumuwakamatsu/notebook152647201f,ICR - Identifying Age-Related Conditions
12924,129432179,2277.0,,3,24,/docxian/icr-visuals-lasso-model-in-r,ICR - Identifying Age-Related Conditions
12925,140214288,371.0,0.224086504290782,0,3,/torayeff/clean-and-simple-undersampler-for-gold-medal,ICR - Identifying Age-Related Conditions
12926,131961336,4508.0,0.3829298273544213,0,0,/avieldanin/notebookefa23fc016,ICR - Identifying Age-Related Conditions
12927,133107826,3399.0,,0,2,/yuyaterasawa/icr-model,ICR - Identifying Age-Related Conditions
12928,133361400,1481.0,0.2494025953638504,0,4,/irasalsabila/icr-identify-age,ICR - Identifying Age-Related Conditions
12929,147151480,1096.0,,0,16,/joebeachcapital/icr-logistic-regression,ICR - Identifying Age-Related Conditions
12930,129397540,798.0,0.3615195365851495,2,8,/andreierofeev/voting-ensemble-xgb-rf-knn,ICR - Identifying Age-Related Conditions
12931,133599509,818.0,,0,0,/ayanamy/icr-eda,ICR - Identifying Age-Related Conditions
12932,138830153,2555.0,,2,15,/tilii7/data-splitting,ICR - Identifying Age-Related Conditions
12933,129203146,1148.0,,0,12,/gunesevitan/icr-identifying-age-related-conditions-lightgbm,ICR - Identifying Age-Related Conditions
12934,129842766,1080.0,0.2953647067536284,0,5,/hamzaghanmi/icr-lightgbm,ICR - Identifying Age-Related Conditions
12935,133742327,1544.0,0.4241114194177511,0,3,/neutrino404/icr-tabpfn,ICR - Identifying Age-Related Conditions
12936,137315719,1532.0,0.7029051758932024,0,3,/xiaohu2200/lgb-baseline-41e760,ICR - Identifying Age-Related Conditions
12937,132038209,1.0,0.1444540271970065,4,69,/room722/icr-adv-model,ICR - Identifying Age-Related Conditions
12938,137235085,1670.0,0.9732302903932556,0,0,/trymybest20/lgb-baseline,ICR - Identifying Age-Related Conditions
12939,131308137,1176.0,,13,151,/muelsamu/simple-tabpfn-approach-for-score-of-15-in-1-min,ICR - Identifying Age-Related Conditions
12940,136988559,1132.0,0.7609017702629497,0,3,/zzoo2200/lgb-baseline,ICR - Identifying Age-Related Conditions
12941,140020677,3015.0,,0,6,/danpietrow/private-lb-0-352-p9-the-one-that-got-away,ICR - Identifying Age-Related Conditions
12942,137696243,1289.0,0.1736683579090099,0,0,/sharoncampos/lgb-baseline-with-687049,ICR - Identifying Age-Related Conditions
12943,138163013,984.0,0.1994521436136744,1,3,/nikki213/lgb-baseline-with-all-fix-multi-label,ICR - Identifying Age-Related Conditions
12944,137372136,649.0,0.1762470976300078,0,4,/katrinaandersond/lgb-baseline-with,ICR - Identifying Age-Related Conditions
12945,137467816,1220.0,,0,0,/maximecapelle/ensemble-xgboost-tabpfn-without-normalization,ICR - Identifying Age-Related Conditions
12946,139663441,2539.0,,0,2,/yasso1/public-0-22-private-0-35,ICR - Identifying Age-Related Conditions
12947,137930729,909.0,0.1676435698323468,0,0,/lisa3871/lgb-baseline-with-38-fixed,ICR - Identifying Age-Related Conditions
12948,139567713,1574.0,0.3267905400491494,0,3,/kononenko/icr-one-cell-linear-regression,ICR - Identifying Age-Related Conditions
12949,137334420,2477.0,0.1712439667206862,0,0,/heijui/lgb-baseline-with,ICR - Identifying Age-Related Conditions
12950,138109999,1012.0,,0,0,/leosv100/alpha-lgbm-0-4-private-lb,ICR - Identifying Age-Related Conditions
12951,129538624,3743.0,0.3653325149752724,0,5,/saurabhsawhney/01-quick-data-to-submission,ICR - Identifying Age-Related Conditions
12952,139569725,588.0,0.2743162730417968,0,0,/gzguevara/icr-lgbm-submission,ICR - Identifying Age-Related Conditions
12953,137339586,1294.0,0.1573498279594176,0,0,/elizabeth912/lgb-baseline-with,ICR - Identifying Age-Related Conditions
12954,132294064,917.0,0.4494206433895222,2,5,/rzatemizel/a-quick-baseline-pipeline-with-flaml-smote,ICR - Identifying Age-Related Conditions
12955,135570308,98.0,,4,26,/nnjjpp/epsilon-eda-for-icr-competition,ICR - Identifying Age-Related Conditions
12956,130990675,2829.0,1.472170383863249,0,0,/kostasskantzis/notebookb441c175ba,ICR - Identifying Age-Related Conditions
12957,135612115,3.0,0.2154596571641507,0,18,/junyang680/icr-lightgbmbaseline,ICR - Identifying Age-Related Conditions
12958,139654148,406.0,,0,1,/blackitten13/multilabelstratifiedkfold-scam-you-need-ohe,ICR - Identifying Age-Related Conditions
12959,134187284,2876.0,5.9356975066096895,0,2,/nivedithavudayagiri/icr-problem-analysis-eda-baseline,ICR - Identifying Age-Related Conditions
12960,136574664,1330.0,,0,0,/moisesmgft/csi22,ICR - Identifying Age-Related Conditions
12961,133416207,864.0,,0,2,/michaelwolff/comparing-unb-bal-log-loss-with-binary-all-classes,ICR - Identifying Age-Related Conditions
12962,129844263,387.0,0.2446609185980007,0,0,/ashlerjohnherrick/catboost,ICR - Identifying Age-Related Conditions
12963,138495813,2306.0,,4,11,/giuseppegarigliano/using-alpha-as-target,ICR - Identifying Age-Related Conditions
12964,138555987,5373.0,0.1550178732031793,6,30,/pablo94/xgb-public-score-0-15,ICR - Identifying Age-Related Conditions
12965,137309154,1681.0,0.157314554301306,6,36,/sinanozdemir/icr-identifying-age-related-conditions-xgboost,ICR - Identifying Age-Related Conditions
12966,139542530,143.0,,2,3,/abhisekdash37/rank-146-xgboost-logistic-regression,ICR - Identifying Age-Related Conditions
12967,137298512,2203.0,7.756226460891853,0,1,/bencefogel/icr01,ICR - Identifying Age-Related Conditions
12968,130478677,559.0,,0,6,/tomokihirose/lightgbm-visualize-tree-structure,ICR - Identifying Age-Related Conditions
12969,139637559,153.0,,0,4,/wisawesome/icr-identity-157th-place-prelim,ICR - Identifying Age-Related Conditions
12970,133956402,2117.0,,0,0,/siliva1799/identifying-age-related-conditions-w-tfdf,ICR - Identifying Age-Related Conditions
12971,139789236,4.0,0.3633099299879985,1,12,/andrejvetrov/4rd-place-solution,ICR - Identifying Age-Related Conditions
12972,134059762,1559.0,0.3943433183764474,2,15,/gloomychan/tabnet-baseline,ICR - Identifying Age-Related Conditions
12973,129463838,376.0,0.227589130534147,15,98,/takaito/icr-iarc-gradient-boosting-ensemble-lb-0-22,ICR - Identifying Age-Related Conditions
12974,129209428,2952.0,,0,4,/ulisesmontoyacanales/icr-identifying-age-related-conditions-eda,ICR - Identifying Age-Related Conditions
12975,137512727,2661.0,0.1633744341587124,0,0,/zizh3ngzhang/modified-tabpfr,ICR - Identifying Age-Related Conditions
12976,130278225,701.0,0.9675794020680152,0,1,/ks160050056/icr-balanced-log-loss-implementation-baseline,ICR - Identifying Age-Related Conditions
12977,133717739,1772.0,,0,5,/korbenwong/greeks-eda,ICR - Identifying Age-Related Conditions
12978,133980334,2782.0,0.1882376324211259,0,0,/meisa0/feature-selection-by-using-null-importance,ICR - Identifying Age-Related Conditions
12979,136334747,460.0,0.1957899947618044,0,0,/wadgek/top-8-solution-on-icr-challenge,ICR - Identifying Age-Related Conditions
12980,130621010,2131.0,2.316832027907039,0,4,/ziadelassal/icr-yeo-johnson-transformation-eda-modelling,ICR - Identifying Age-Related Conditions
12981,135738885,607.0,,6,22,/leiwong/icr-eda-xgb-baseline-pipeline-explaination,ICR - Identifying Age-Related Conditions
12982,131468817,1145.0,,27,96,/chaitanyagiri/icr-2023-single-lgbm-0-12-cv-0-16-lb,ICR - Identifying Age-Related Conditions
12983,139381942,2866.0,0.7547208186079244,19,54,/nemanjagojkovic/using-advanced-feature-engineering-with-featurewiz,ICR - Identifying Age-Related Conditions
12984,139272835,42.0,0.2509448682665892,0,0,/aydarkhisamov/iarc-gb-nn-lr-stack,ICR - Identifying Age-Related Conditions
12985,132209546,2326.0,,0,23,/junjitakeshima/icr-easy-improvement-for-beginner-eng,ICR - Identifying Age-Related Conditions
12986,135248655,3063.0,0.3281801365585632,0,0,/renaldohermawan/icr-competition-automl-mljar-multiclass,ICR - Identifying Age-Related Conditions
12987,139637011,3085.0,0.5675722988777072,0,9,/eivolkova/simple-logistic-regression,ICR - Identifying Age-Related Conditions
12988,136604663,3618.0,0.3229729239089602,1,3,/putrorohmawan/identifying-age-related-condition,ICR - Identifying Age-Related Conditions
12989,139141049,1665.0,,0,0,/ppujari/icr2023-xgboost,ICR - Identifying Age-Related Conditions
12990,139308127,1325.0,0.1946860105178465,0,0,/smarkbhb/icr-submit,ICR - Identifying Age-Related Conditions
12991,129387462,2178.0,,0,12,/harshitkmr/lgbm-classifier-icr,ICR - Identifying Age-Related Conditions
12992,155391220,2186.0,,0,0,/nikitkastr/ndr-model,ICR - Identifying Age-Related Conditions
12993,138848794,2897.0,0.3302574019136831,3,7,/carol292/xgb-lgb-final,ICR - Identifying Age-Related Conditions
12994,132990579,973.0,,2,10,/bowaka/icr-how-to-really-use-early-stopping-with-lgb,ICR - Identifying Age-Related Conditions
12995,135706021,515.0,0.1954004544958627,0,0,/kazumayoshida/notebook8c1d02ecae,ICR - Identifying Age-Related Conditions
12996,139577473,93.0,,1,3,/seungjunlim/95th-solution,ICR - Identifying Age-Related Conditions
12997,137436806,248.0,,10,8,/taruto1215/icr-chatgpt-code-interpreter-xgboost-lb0-4,ICR - Identifying Age-Related Conditions
12998,137865540,2591.0,,8,28,/atsushiiwasaki/icr-lgbm-baseline-with-optuna-cv-0-19-lb-0-23,ICR - Identifying Age-Related Conditions
12999,130197809,7.0,0.1811377151612326,0,7,/manthanbhagat/simple-baseline-add-greeks-features,ICR - Identifying Age-Related Conditions
13000,140514809,585.0,0.1812927239209497,1,7,/lukaszsztukiewicz/bronze-medal-solution-11-cells-clean,ICR - Identifying Age-Related Conditions
13001,132254978,3472.0,0.2321940267982935,0,0,/cristiandeblasis/icr-inicial-lgbm-cv,ICR - Identifying Age-Related Conditions
13002,133294249,1261.0,,0,7,/carlmcbrideellis/icr-condition-d-in-the-public-and-private-dataset,ICR - Identifying Age-Related Conditions
13003,142111487,159.0,,1,3,/jovanchua/159th-ranked-bagging-voting-classifier-lb-0-39,ICR - Identifying Age-Related Conditions
13004,134286427,452.0,0.1879006503144156,0,16,/kailex/ic-r-lightgbm-downsampling,ICR - Identifying Age-Related Conditions
13005,130848171,952.0,0.9373008954690346,0,2,/camillagretschel/improve-based-on-icr-first-version,ICR - Identifying Age-Related Conditions
13006,136050886,3097.0,,3,7,/levdvernik/logisticregression-icr,ICR - Identifying Age-Related Conditions
13007,135893387,126.0,0.2209871190865713,0,0,/ungsikkim/2023-06-23-icr,ICR - Identifying Age-Related Conditions
13008,141818237,637.0,0.294547406926455,0,2,/hendriknebel/pub-0-29-priv-0-48-kernel-for-icr-glmnet-xgbm,ICR - Identifying Age-Related Conditions
13009,139624561,1441.0,,14,15,/elcaiseri/icr-multiheads-ensemble-baseline-cv-0-23-eda,ICR - Identifying Age-Related Conditions
13010,131089755,1462.0,0.1889801626454542,10,21,/maddalasravani/identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13011,129741598,1484.0,0.565146322694448,0,7,/vibhorsharma111/icr-the-simple-the-better,ICR - Identifying Age-Related Conditions
13012,130663631,1446.0,0.1890104933796589,0,7,/keerthanasujitha/icrnb,ICR - Identifying Age-Related Conditions
13013,130387037,1448.0,,4,11,/tenffe/icr-age-eda-hypergbm-automl,ICR - Identifying Age-Related Conditions
13014,139596578,329.0,0.1919671875812014,0,1,/erijoel/icr-solution,ICR - Identifying Age-Related Conditions
13015,136318152,855.0,,0,3,/dky7376/icr-identifying-age-related-conditions-w-rf,ICR - Identifying Age-Related Conditions
13016,138683625,109.0,0.1938673051284372,0,1,/yasarc4/109-place-solution-publiclb-0-19-privatelb-0-38,ICR - Identifying Age-Related Conditions
13017,134677557,3140.0,,0,1,/steadyfox2/easy-lgbm-optuna,ICR - Identifying Age-Related Conditions
13018,140212454,2684.0,0.2197671364233678,11,57,/gkitchen/predicting-age-related-conditions,ICR - Identifying Age-Related Conditions
13019,143438954,1443.0,,0,1,/dbzadnen/icr-using-darts-regression-and-svmsmote,ICR - Identifying Age-Related Conditions
13020,140030521,1082.0,,0,1,/sotamiki/icr-submission,ICR - Identifying Age-Related Conditions
13021,138942248,1102.0,0.2981536889831221,1,5,/clarkelee/my-icr-comp-note-book,ICR - Identifying Age-Related Conditions
13022,133848222,2237.0,0.3328922259187243,1,2,/danielphalen/icr-mlp-model,ICR - Identifying Age-Related Conditions
13023,140295935,186.0,,0,1,/shriekingwanderer/top-186-solution-silver,ICR - Identifying Age-Related Conditions
13024,131033266,787.0,0.7065290859280275,0,0,/jacoballessio/ensemble-randomundersampler,ICR - Identifying Age-Related Conditions
13025,129450726,1282.0,0.6576687134432782,0,8,/mmoore23/icr-baseline-random-forest,ICR - Identifying Age-Related Conditions
13026,137558305,292.0,0.200385439852797,2,2,/mohneesh7/tabpfn-xgb-with-stratifiedkf-cv,ICR - Identifying Age-Related Conditions
13027,137023419,610.0,,0,1,/dhritiverma/icr-rf-lr-tabpfn-ensemble-lb-0-20,ICR - Identifying Age-Related Conditions
13028,138464769,1068.0,0.2825649243992698,1,3,/sho124/icr-with-lightgbm-crossvalidation,ICR - Identifying Age-Related Conditions
13029,137475371,6.0,0.2196978238010128,0,8,/diegosilvadefrana/6rd-position-icr-identifying-age-related,ICR - Identifying Age-Related Conditions
13030,139404020,629.0,,2,1,/anotherbadcode/icr-ensemble,ICR - Identifying Age-Related Conditions
13031,139437112,3191.0,,2,3,/dmtrrr/ensemble-xgboost-only-0-2-lb,ICR - Identifying Age-Related Conditions
13032,137910577,1037.0,0.2729026774274001,0,0,/fivcam/tabfpn,ICR - Identifying Age-Related Conditions
13033,138698359,4707.0,0.6762226201106887,0,1,/tianbaiyutoby/use-tensorflow-keras-predict-age-related-condition,ICR - Identifying Age-Related Conditions
13034,133454112,101.0,0.2084214981815194,0,7,/ryanbarretto/103rd-place-solution,ICR - Identifying Age-Related Conditions
13035,130534096,14.0,0.2345370276291504,0,14,/keitashimizu21/en-ja-first-firsteda-baseline-icr,ICR - Identifying Age-Related Conditions
13036,134992095,4411.0,0.3561565116780332,0,0,/kingogamer/icr-xgboost-algorithm,ICR - Identifying Age-Related Conditions
13037,139583792,3449.0,,0,2,/hli111111/tabpfn-gbm-stackings,ICR - Identifying Age-Related Conditions
13038,130652147,2414.0,0.2260365997457178,0,11,/dngngy/icr-classification-with-convnet,ICR - Identifying Age-Related Conditions
13039,136609865,1786.0,0.2109189424328683,1,7,/pedrokim00/icr-exame-csi22,ICR - Identifying Age-Related Conditions
13040,129528500,520.0,,7,29,/dzisandy/icr-first-version,ICR - Identifying Age-Related Conditions
13041,140683505,622.0,0.1461354605114344,0,1,/jiehuatan/private-lb-0-29377-feature-selection-model-trained,ICR - Identifying Age-Related Conditions
13042,141057084,5.0,0.2202313192773881,0,22,/celiker/icr-5-place-solution,ICR - Identifying Age-Related Conditions
13043,139656212,1661.0,,0,0,/eeecee/icr-identify-age-related-conditions-lgbm,ICR - Identifying Age-Related Conditions
13044,136222230,12.0,0.2297196354863287,0,0,/nabhanda1239/icr-competition-final-solution,ICR - Identifying Age-Related Conditions
13045,139570165,670.0,,0,1,/abdullahkavakli/icr-700th-place-lgbm-catboost-qda-lda,ICR - Identifying Age-Related Conditions
13046,139557732,1392.0,0.2545854201532738,8,29,/theodorospsarras/ensemble-xgb-tabpfn-lgbm-stratified-kfold,ICR - Identifying Age-Related Conditions
13047,129871076,826.0,,11,38,/mattop/icr-identifying-age-related-conditions-eda,ICR - Identifying Age-Related Conditions
13048,130640859,40.0,0.2286489746227194,2,2,/stenford23/icr-inference-contrastive-retriever,ICR - Identifying Age-Related Conditions
13049,140271477,204.0,,0,0,/owerbat/catboost-baseline-silver-medal-top-4,ICR - Identifying Age-Related Conditions
13050,138349631,571.0,0.2192216005874374,0,1,/carlosgaravatti/icr-top9,ICR - Identifying Age-Related Conditions
13051,136138817,598.0,0.3612909926342035,0,0,/bzeniti/icr-modelling,ICR - Identifying Age-Related Conditions
13052,139562722,1339.0,0.2605637890259193,0,0,/simonhol/icr-comp-final,ICR - Identifying Age-Related Conditions
13053,139632316,2322.0,,2,10,/thomaswrightanderson/identifying-age-related-conditions-kaggle-comp,ICR - Identifying Age-Related Conditions
13054,129536226,91.0,0.3213147504740554,0,0,/jakubrogulski/ensemble-of-4-models,ICR - Identifying Age-Related Conditions
13055,135630604,3247.0,0.2212698159927334,0,0,/javes1111/invitro-cell-research,ICR - Identifying Age-Related Conditions
13056,133710166,142.0,,0,3,/shivamsingh17072001/notebookdcc12221ba,ICR - Identifying Age-Related Conditions
13057,135394541,3529.0,0.2860218921379976,15,23,/vcode1509/icr-rf-classifier-svm-lgbm,ICR - Identifying Age-Related Conditions
13058,133435692,277.0,,1,6,/shoabahamed/icr-eda-logistic-regression-model,ICR - Identifying Age-Related Conditions
13059,131426656,47.0,0.2244485425408413,0,0,/manavgarg663/icr-competition,ICR - Identifying Age-Related Conditions
13060,136189488,2188.0,0.5677112165360769,0,0,/horon12345/icr-2023-05-08,ICR - Identifying Age-Related Conditions
13061,139527281,74.0,,1,1,/andrewkilo/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13062,129836329,75.0,,0,1,/jonblanchard/icr-eda-and-baseline-model,ICR - Identifying Age-Related Conditions
13063,135439595,1254.0,,0,0,/vynokurovyegor/predict,ICR - Identifying Age-Related Conditions
13064,129406154,13.0,0.3161904079580701,0,2,/ryotaichikawa/icr-01-eda-simple-lightgbm-baseline,ICR - Identifying Age-Related Conditions
13065,132897927,224.0,0.2250466076098324,0,4,/benidictusgalihmp/icr-eda-optuna-xgb-lgbm,ICR - Identifying Age-Related Conditions
13066,130369781,148.0,0.2282583063508504,0,0,/dlaststark/icr-new-dawn,ICR - Identifying Age-Related Conditions
13067,140638391,441.0,,3,8,/yan0022/icr-stacking-with-sklearn,ICR - Identifying Age-Related Conditions
13068,137032858,4331.0,0.3336591064693252,0,23,/iqbalsyahakbar/icr-eda-and-ensemble-for-starters,ICR - Identifying Age-Related Conditions
13069,139304923,2226.0,0.3173567800950765,9,54,/kacperrabczewski/age-related-conditions,ICR - Identifying Age-Related Conditions
13070,130121267,658.0,0.2343060784125676,0,6,/stripe/r-icr-03-lgb-weight-add,ICR - Identifying Age-Related Conditions
13071,129370551,206.0,,0,10,/e271828ai/icr-arc-01-simplebaseline-en-jp-20230512,ICR - Identifying Age-Related Conditions
13072,133089276,733.0,1.197832768793448,0,0,/mehulgoyal49/notebookdcf7a7d933,ICR - Identifying Age-Related Conditions
13073,130110055,753.0,0.7149646792247719,0,5,/piehtvh/icr-iarc-simple-modeling,ICR - Identifying Age-Related Conditions
13074,143187896,262.0,,0,0,/evgenykazenov/icr-solution,ICR - Identifying Age-Related Conditions
13075,131089244,3631.0,0.2303095308989718,0,3,/ncmurali/icr-notebook,ICR - Identifying Age-Related Conditions
13076,130797475,2584.0,0.3067708177332664,4,11,/nicobarea/icr-with-tidymodels,ICR - Identifying Age-Related Conditions
13077,132659585,2718.0,,0,5,/barun2104/icr-age-related-conditions-eda,ICR - Identifying Age-Related Conditions
13078,139586689,684.0,,0,0,/deborshi18/catboost-solution-public-0-25-private-0-43,ICR - Identifying Age-Related Conditions
13079,139591514,767.0,,0,1,/lucasboesen/xgb-cv-0-37-private-0-43-public-0-23,ICR - Identifying Age-Related Conditions
13080,131085786,3753.0,,0,2,/kalyansekhar07/baseline-submission-with-optuna,ICR - Identifying Age-Related Conditions
13081,130894679,660.0,,0,2,/reneeschmidt/icr-data-visualization,ICR - Identifying Age-Related Conditions
13082,140277798,322.0,,0,0,/shaharyarsajid/top-6-percent-xgboost-with-optuna-optimization,ICR - Identifying Age-Related Conditions
13083,137914322,1029.0,0.2343067478377603,0,0,/whiskeyyankee/notebook06df57f4df,ICR - Identifying Age-Related Conditions
13084,130528060,1007.0,0.2915756200827481,2,15,/ndeperrois/scikit-learn-for-newbies-age-related-conditions,ICR - Identifying Age-Related Conditions
13085,129398027,464.0,,0,11,/shivanshuman/lightgbm-optuna-baseline,ICR - Identifying Age-Related Conditions
13086,132149542,2110.0,0.3736375527277724,0,1,/diegomachado/icr-simple-logistic-regression-baseline,ICR - Identifying Age-Related Conditions
13087,135338684,482.0,0.2434010374164337,0,3,/yzokulu/lightgbm-baseline-improved-score-0-23,ICR - Identifying Age-Related Conditions
13088,139518074,1211.0,,0,3,/prasad970/icr-notebook,ICR - Identifying Age-Related Conditions
13089,134940822,3401.0,0.2395415940575883,13,38,/michal71/classification-with-neural-network,ICR - Identifying Age-Related Conditions
13090,134940822,3401.0,0.2682295052237308,13,38,/michal71/classification-with-neural-network,ICR - Identifying Age-Related Conditions
13091,137030394,1374.0,0.2401033917178729,5,29,/prasad22/icr-competition-submission,ICR - Identifying Age-Related Conditions
13092,131260466,602.0,0.2410688200021231,0,0,/josemariasabater/xgboost-age,ICR - Identifying Age-Related Conditions
13093,140699576,202.0,0.2443315381576063,0,3,/andrsvercesi/icr-eda-and-modeling-silver-medal,ICR - Identifying Age-Related Conditions
13094,134853215,1614.0,,0,2,/jinyrdream/1st-draft,ICR - Identifying Age-Related Conditions
13095,135896991,3775.0,,4,13,/damathajorisaxel/icr-age-eda-pca-vs-feature-selection,ICR - Identifying Age-Related Conditions
13096,134847440,1006.0,,0,4,/robertturro/icr-feature-visuals,ICR - Identifying Age-Related Conditions
13097,130842280,793.0,0.2450161542399501,0,6,/aditya1064/icr-age-related-condition,ICR - Identifying Age-Related Conditions
13098,129714047,1768.0,0.4639833420948917,0,6,/qiaoningchen/agerelatedconditions-simpleensemble,ICR - Identifying Age-Related Conditions
13099,131030094,425.0,0.96757831881852,0,67,/dan3dewey/icr-2023-balanced-log-loss,ICR - Identifying Age-Related Conditions
13100,133094041,1141.0,0.2498845675779281,0,4,/mohamedouchir/icr-catboost,ICR - Identifying Age-Related Conditions
13101,133094041,1141.0,0.2498845675779281,0,4,/mohamedouchir/icr-catboost,ICR - Identifying Age-Related Conditions
13102,130638816,3777.0,0.4368023036036136,0,1,/myliew/simple-stacked-cat-lgbm,ICR - Identifying Age-Related Conditions
13103,134252052,4119.0,,0,1,/hemanthx99/icr-identify-age-related-conditions,ICR - Identifying Age-Related Conditions
13104,131364797,3074.0,,29,100,/sugataghosh/icr-the-devil-is-in-the-greeks,ICR - Identifying Age-Related Conditions
13105,130453801,3332.0,0.3333702774486775,3,15,/samuelabatnehendalie/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13106,130453801,3332.0,0.3458904093975972,3,15,/samuelabatnehendalie/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13107,135247121,2674.0,0.2638122790614037,0,0,/pear2jam/icr-baseline,ICR - Identifying Age-Related Conditions
13108,135496008,2835.0,0.2553907903951342,0,0,/reckylurker/personal-icr,ICR - Identifying Age-Related Conditions
13109,137005915,4599.0,0.2634958547887388,0,17,/jominjae/icr-lr-dt-rf-lgbm-with-knn-smote,ICR - Identifying Age-Related Conditions
13110,139958830,760.0,0.2653722016422556,0,3,/sarthakmehra03/icr-analysis-and-modelling,ICR - Identifying Age-Related Conditions
13111,135370823,1435.0,0.4809252616434438,0,2,/ilyaelper/svm-rf-knn-ensemble,ICR - Identifying Age-Related Conditions
13112,134833450,1747.0,0.2666896892904689,0,2,/maniceet/catboost-eda,ICR - Identifying Age-Related Conditions
13113,136382585,3489.0,0.4056313639190231,0,1,/kennyrc/icr-baseline-from-oner-to-random-forests,ICR - Identifying Age-Related Conditions
13114,139401383,578.0,0.3182642932588724,0,0,/manuelnkegoum/competition-age-related,ICR - Identifying Age-Related Conditions
13115,137627919,127.0,0.2679953137021518,0,0,/lorenzoarcioni/icr-analysis-and-models,ICR - Identifying Age-Related Conditions
13116,138653441,2941.0,,0,2,/barshaagrawal/icr-easy-eda-xgboost-lightgbm-w-tuning,ICR - Identifying Age-Related Conditions
13117,130726516,1752.0,0.4234757564522336,0,0,/suryaprakashmusunuri/icr-age,ICR - Identifying Age-Related Conditions
13118,138499488,1300.0,0.2698873682170748,0,2,/aliliaymenabderraouf/notebook-icr,ICR - Identifying Age-Related Conditions
13119,130983017,2561.0,,0,1,/ficklemaverick/balancing-data-xgboost,ICR - Identifying Age-Related Conditions
13120,129656015,3600.0,0.2715789612826882,0,0,/itnaava/icr-classification-problem,ICR - Identifying Age-Related Conditions
13121,161896656,1179.0,0.633672683748833,0,1,/johnycoder/icr-inference,ICR - Identifying Age-Related Conditions
13122,134881726,4529.0,0.4362242750818622,0,1,/shubham219/basic-nn,ICR - Identifying Age-Related Conditions
13123,131821918,1657.0,0.3282736523528493,20,83,/nazimcherpanov/icr-xgboot-and-lgb-voting-stacking,ICR - Identifying Age-Related Conditions
13124,138613928,2977.0,0.2738674076262369,0,0,/antonprisyazhnyuk/notebookdd96c7279c,ICR - Identifying Age-Related Conditions
13125,133364494,2988.0,0.32838932547811,0,3,/wamateusz/icr-naive-approach-xgb-weighted-classes,ICR - Identifying Age-Related Conditions
13126,134178813,1190.0,3.38531431165998,0,0,/shengxiongbenliu/notebook213fd9ab9a,ICR - Identifying Age-Related Conditions
13127,137875308,3538.0,,0,7,/gauravduttakiit/icr-lazypredict,ICR - Identifying Age-Related Conditions
13128,136726375,2922.0,0.3298414422237853,0,0,/vinitkp/quick-eda-xgboost,ICR - Identifying Age-Related Conditions
13129,135202477,2108.0,0.3497702237306267,0,2,/yeemeitsang/age-related-conditions-xgboost,ICR - Identifying Age-Related Conditions
13130,137115275,2376.0,0.2790633352795671,0,15,/kdsharma/rapids-cuml-svc-baseline-lb-cv-0-35,ICR - Identifying Age-Related Conditions
13131,135194791,2957.0,0.3810554103093132,0,0,/rizkykiky/baseline-icr,ICR - Identifying Age-Related Conditions
13132,139468347,2251.0,0.4011455496457232,0,5,/nfls1215/icr-xgboost-ensemble,ICR - Identifying Age-Related Conditions
13133,136213491,3146.0,0.287470888401779,8,37,/iqmansingh/icr-optuna-xgb-lgbm-rf-ensemble-eda,ICR - Identifying Age-Related Conditions
13134,134356368,3232.0,0.2833917776385735,0,0,/harishgehlot/icr-xgboost,ICR - Identifying Age-Related Conditions
13135,138636272,1739.0,0.3844251206638427,0,4,/jefflin97/icr-identify-age-related-conditions-competition,ICR - Identifying Age-Related Conditions
13136,135571368,4028.0,,0,0,/almaheekhan/notebookb7387bf413,ICR - Identifying Age-Related Conditions
13137,135327049,2546.0,0.3658184489118914,0,0,/aerofreak/fas-fas-submit-krna-hai,ICR - Identifying Age-Related Conditions
13138,132402692,2466.0,0.4025793656271835,0,0,/romanmarygin/icr-logregr,ICR - Identifying Age-Related Conditions
13139,137224398,3653.0,0.2907983460911726,0,0,/bytestorm/simple-tabpfn,ICR - Identifying Age-Related Conditions
13140,140018736,449.0,0.7190910212664243,0,5,/ceyhunsahin/rus-gridsearch-private-score-0-4,ICR - Identifying Age-Related Conditions
13141,130500122,3887.0,,0,1,/manojkumarpentapalli/icr-manoj,ICR - Identifying Age-Related Conditions
13142,138943134,2245.0,0.2918173782558091,0,1,/cheekati1/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13143,136158427,3030.0,,2,5,/nikkitha8/icr-competition-age-related-classification,ICR - Identifying Age-Related Conditions
13144,138107876,456.0,0.3182851876999724,0,3,/dalecap/first-pass,ICR - Identifying Age-Related Conditions
13145,137661714,2172.0,0.3331844790774029,1,5,/natayakusheva/identify-it-analysis-and-forecasting,ICR - Identifying Age-Related Conditions
13146,137990812,4196.0,0.2976002038047662,0,1,/yasithakavishka/logistic-regression2,ICR - Identifying Age-Related Conditions
13147,135319910,2954.0,9.759561195956472,0,0,/hsuweiho/notebook1e9f23de89,ICR - Identifying Age-Related Conditions
13148,134735919,555.0,0.2996923918580503,0,3,/pratul007/icr-identify-age-related-conditions,ICR - Identifying Age-Related Conditions
13149,137850898,1129.0,0.317333958185362,0,1,/allenrussell/icr-random-forest-fine-tune,ICR - Identifying Age-Related Conditions
13150,139706085,158.0,0.3567604381113384,2,13,/jano123/icr-by-symbolic-regression,ICR - Identifying Age-Related Conditions
13151,138493842,3078.0,0.366829340202018,0,1,/sombrahacker/catboostclassifier-and-optuna,ICR - Identifying Age-Related Conditions
13152,137450975,3982.0,,0,5,/greyisbetter/icr-wide-dataset,ICR - Identifying Age-Related Conditions
13153,137640666,3064.0,,0,3,/cemduru/eda-and-simple-lgbmclassifier-base,ICR - Identifying Age-Related Conditions
13154,133598416,3264.0,0.3028330544858745,2,12,/panini92/icr-eda-model-comparison-submission,ICR - Identifying Age-Related Conditions
13155,134861146,4204.0,18.37275229956189,0,0,/zyh123454321/icr-tabpfn-xgboost,ICR - Identifying Age-Related Conditions
13156,131466086,2151.0,,11,19,/oles04/pycaret-model-evaluation,ICR - Identifying Age-Related Conditions
13157,131695919,2989.0,0.3529868613794374,0,1,/lordxerxes/just-the-beginning,ICR - Identifying Age-Related Conditions
13158,140255198,355.0,,0,2,/hwhuynguyen/icr-base-line,ICR - Identifying Age-Related Conditions
13159,138758117,1036.0,0.4099426859058607,7,9,/kcwong5/icr-pruner-for-lightgbm,ICR - Identifying Age-Related Conditions
13160,129421232,3231.0,,0,9,/airqualityanthony/icr-xgboost-optuna-optimised-0-31,ICR - Identifying Age-Related Conditions
13161,133361191,600.0,0.31193220333707,2,16,/quangnhatbui/icr-eda-and-model-selection-xgb-randomforest,ICR - Identifying Age-Related Conditions
13162,129892970,3733.0,0.3122705660271955,0,0,/minhnghacan/notebook295e8a82dd,ICR - Identifying Age-Related Conditions
13163,139569590,3387.0,0.6204368807547829,0,7,/shiyuandong/icr-neural-network,ICR - Identifying Age-Related Conditions
13164,136463614,3853.0,,0,8,/moneebarifbbs/icr-age-releated-by-ensemble,ICR - Identifying Age-Related Conditions
13165,136056493,2982.0,0.3514779419138054,0,6,/alarchemn/the-importance-of-prob-calibration-cv-and-metrics,ICR - Identifying Age-Related Conditions
13166,135062270,4230.0,,0,0,/ohocamoe/catboost-best,ICR - Identifying Age-Related Conditions
13167,136579859,1137.0,0.3188562848863521,1,3,/tomaszszyrowski/icr-data-exploratory,ICR - Identifying Age-Related Conditions
13168,130063710,4272.0,0.3165530923021308,0,1,/soupmonster/icr-simple-lightgbm-baseline,ICR - Identifying Age-Related Conditions
13169,132938925,3564.0,0.3789442724365346,0,1,/panmingxia/competition-icr,ICR - Identifying Age-Related Conditions
13170,132205713,1773.0,0.3726168565011916,0,0,/saurograndi/xgboost-classifier,ICR - Identifying Age-Related Conditions
13171,138740162,1071.0,,1,4,/lukasschaub/icr-final-prediction,ICR - Identifying Age-Related Conditions
13172,140368902,218.0,,0,0,/almeid4/icr-random-forest-with-smote,ICR - Identifying Age-Related Conditions
13173,131374407,3425.0,0.3170555219810322,0,9,/ailafelixa/icr-iarc-pre-process-cat-boost-classifier,ICR - Identifying Age-Related Conditions
13174,135604831,1056.0,,0,0,/kashishmukheja/icr-prediction-initial-model,ICR - Identifying Age-Related Conditions
13175,135232526,3515.0,0.5878666605028147,0,3,/livioludolff/random-forest-hyperparameter-tuning,ICR - Identifying Age-Related Conditions
13176,135655316,1384.0,0.3185620918895727,0,0,/maximilianogalindo/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13177,136263432,1385.0,0.3185620918895727,3,15,/naveenkumar20bps1137/icr-tensorflow-decision-forest,ICR - Identifying Age-Related Conditions
13178,131703158,2800.0,0.3344599267764326,0,1,/mousemice/icr-flaml-automl-lgbm,ICR - Identifying Age-Related Conditions
13179,139445502,550.0,0.3191401324187018,0,0,/mrlalitmjoshi/icr-with-randomforest-and-adaboost,ICR - Identifying Age-Related Conditions
13180,131605865,3199.0,0.3191964699977634,0,4,/shivanshuverma/ideal-notebook-for-beginners-easy-to-understand,ICR - Identifying Age-Related Conditions
13181,129218316,2998.0,,1,11,/mobenmo/quick-eda-xgboost-0-31-score,ICR - Identifying Age-Related Conditions
13182,131014092,2205.0,0.6978241465775953,0,5,/tmkartikeypillay/tensor-flow-base-line,ICR - Identifying Age-Related Conditions
13183,131355593,3612.0,0.321808725803334,0,4,/thirumalaraom/icr-notebook,ICR - Identifying Age-Related Conditions
13184,135266121,2917.0,,0,7,/rahulj0shi/auxiliary-learning-method-for-icr,ICR - Identifying Age-Related Conditions
13185,135269579,2149.0,0.3228562499452928,0,15,/kevinmontes/baseline-submission-logisticregression,ICR - Identifying Age-Related Conditions
13186,139552445,1982.0,1.5231681419915564,6,8,/chris36/icr-analysis-python,ICR - Identifying Age-Related Conditions
13187,134342883,2656.0,0.3254256233568338,0,3,/ajinkyawalunj/icr-rf-gscv,ICR - Identifying Age-Related Conditions
13188,137579768,4375.0,,0,3,/muhannadmansour/icr-analysis-and-predict,ICR - Identifying Age-Related Conditions
13189,131711092,1610.0,0.386451171541614,0,2,/srijansrivastava01/icr-xgb,ICR - Identifying Age-Related Conditions
13190,132362655,1792.0,0.3263356061654824,93,382,/gusthema/identifying-age-related-conditions-w-tfdf,ICR - Identifying Age-Related Conditions
13191,136174663,1178.0,0.4699152077984439,0,0,/dagneazene/icr-gboostedtree-starter-code,ICR - Identifying Age-Related Conditions
13192,136473589,1930.0,0.3263356061654824,0,6,/merveoztiryaki/identifying-age-related-conditions-tr,ICR - Identifying Age-Related Conditions
13193,136343670,1986.0,,0,1,/diogofs/icr-first-attempt-8882,ICR - Identifying Age-Related Conditions
13194,137563148,1997.0,0.3263356061654824,0,0,/asjad2024/iclr-health-hack,ICR - Identifying Age-Related Conditions
13195,138074646,2029.0,0.3263356061654824,0,0,/mahakalbhakt/notebookd11601f7dc,ICR - Identifying Age-Related Conditions
13196,138074646,2029.0,0.3263356061654824,0,0,/mahakalbhakt/notebookd11601f7dc,ICR - Identifying Age-Related Conditions
13197,138074646,2029.0,0.3263356061654824,0,0,/mahakalbhakt/notebookd11601f7dc,ICR - Identifying Age-Related Conditions
13198,139502829,2051.0,,0,1,/kopkritsaikhiao/identifying-age-related-conditions-clean-data,ICR - Identifying Age-Related Conditions
13199,139086165,2065.0,0.3263356061654824,0,0,/uom239340t/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13200,132494648,2078.0,,4,5,/amitmalhotra03/disease-prediction,ICR - Identifying Age-Related Conditions
13201,130874615,4202.0,0.326363048562139,0,0,/devanshu12122/xgboost-icr-01-hyperp,ICR - Identifying Age-Related Conditions
13202,137660544,3331.0,0.3264495491761834,0,1,/mohit2512/icr-identify-age-related-conditions,ICR - Identifying Age-Related Conditions
13203,135897359,1379.0,0.326696059531003,0,12,/ishanpurohit/icr-prediction-tfdf,ICR - Identifying Age-Related Conditions
13204,137636926,3276.0,0.3267228635781949,0,3,/ericcwh/6-models-for-icr,ICR - Identifying Age-Related Conditions
13205,131052318,3650.0,0.3729324744976463,0,0,/shenyiqin/icr-lightgbm,ICR - Identifying Age-Related Conditions
13206,138288266,4112.0,0.3279697836474427,0,2,/hhoinjung/pu-learning,ICR - Identifying Age-Related Conditions
13207,137512019,788.0,0.3475131419017709,0,2,/apoorvg1709/lgbm-bagging-lr-bagging-knn,ICR - Identifying Age-Related Conditions
13208,153695304,4278.0,,0,0,/samuelkabati1/identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13209,129590293,2732.0,0.3326581995974941,0,13,/louisbunuel/icr-lgbm-clf-optuna,ICR - Identifying Age-Related Conditions
13210,139135840,2512.0,0.333389024191029,0,8,/farzonaeraj/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13211,135959946,2716.0,0.3704881948006392,0,8,/smokeyscraper/icrnb,ICR - Identifying Age-Related Conditions
13212,135000044,1578.0,0.4063524005490018,0,0,/kheireddineattala/help-them-ogs,ICR - Identifying Age-Related Conditions
13213,138444105,4782.0,0.416740180329474,0,0,/alexanderheyuan/notebook709e0762fe,ICR - Identifying Age-Related Conditions
13214,135781197,3703.0,1.7874177231238957,0,3,/paulbuono/first-attempt-2,ICR - Identifying Age-Related Conditions
13215,138456640,1192.0,0.3435668543686049,0,4,/drsamkano/notebookaf7d8c7c3e,ICR - Identifying Age-Related Conditions
13216,130368845,2768.0,0.3493301877743823,0,0,/timryall/simple-random-forests-age-related-conditions,ICR - Identifying Age-Related Conditions
13217,136894311,3021.0,0.3842779738336331,0,2,/mohit19/icr-age-related-code,ICR - Identifying Age-Related Conditions
13218,132833429,3275.0,0.5348662512177715,0,2,/cyc2023i/stackimh,ICR - Identifying Age-Related Conditions
13219,134452856,3177.0,0.343576244360139,0,2,/sakthinarayanan/icr-competition,ICR - Identifying Age-Related Conditions
13220,138843744,2345.0,0.3510250977360393,0,0,/dorianglon/icr-notebook,ICR - Identifying Age-Related Conditions
13221,129705508,2754.0,0.3437733629089927,2,7,/dustinober/age-related-conditions,ICR - Identifying Age-Related Conditions
13222,137632473,4461.0,,0,7,/shashaalam/icr-xg-cb-lg-tfdf-fa,ICR - Identifying Age-Related Conditions
13223,138402329,2241.0,0.6861956649389481,0,0,/mirabirhossain/age-competition,ICR - Identifying Age-Related Conditions
13224,129740026,4268.0,0.349755355189421,0,5,/opcris/icr-v4,ICR - Identifying Age-Related Conditions
13225,131635385,4139.0,0.349755355189421,0,3,/ktahn207272/xgboost-play,ICR - Identifying Age-Related Conditions
13226,133068784,3569.0,1.5086993280540997,0,6,/kishore3914/icr-solver,ICR - Identifying Age-Related Conditions
13227,133089242,4282.0,,0,4,/nataliekalina/simple-eda-model-selection-submission-icr,ICR - Identifying Age-Related Conditions
13228,136311442,2572.0,0.3511868242443514,0,2,/abeheshti/intro-to-solution-1-without-greeks,ICR - Identifying Age-Related Conditions
13229,132966249,970.0,,0,4,/oluwasegunodunlami/icr-project-with-adaboost,ICR - Identifying Age-Related Conditions
13230,135624311,2928.0,,0,4,/mfattah/complete-view-of-outlier,ICR - Identifying Age-Related Conditions
13231,133779401,2770.0,,0,3,/tarkhon/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13232,133941523,3667.0,0.357879402479791,0,8,/kirtanmatalia26/identifying-age-related-conditions-using-xgboost,ICR - Identifying Age-Related Conditions
13233,134015199,3428.0,0.5042955709538156,0,0,/zhuo0710/icr-identifying-age-related-conditions-lgbm,ICR - Identifying Age-Related Conditions
13234,136955359,2850.0,,0,0,/ivanzayarsky/icr-random-forest,ICR - Identifying Age-Related Conditions
13235,131671155,3441.0,,0,2,/rajatborkar/icr-age-related-conditions,ICR - Identifying Age-Related Conditions
13236,130471980,3523.0,0.4607622125082901,0,1,/mohammadjavadpk/notebook6b8d98767f,ICR - Identifying Age-Related Conditions
13237,136315939,822.0,0.7798220141287294,0,0,/mayurdushetwar/predicting-age-related-conditions-icr,ICR - Identifying Age-Related Conditions
13238,160011479,4292.0,0.4063929454493555,3,25,/cybersimar08/icr-xgb-adaboost-lgbm,ICR - Identifying Age-Related Conditions
13239,135094298,4040.0,,0,2,/harshjadhav6301/icr-baseline,ICR - Identifying Age-Related Conditions
13240,136242601,3484.0,0.3731228256747191,0,9,/ashishjagdishsharma/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13241,130512244,4377.0,0.3733497373628477,1,3,/yuvannabawa/icr-deeplearning,ICR - Identifying Age-Related Conditions
13242,130250258,3568.0,,0,0,/taiyokaggle/ver001-first-catboost,ICR - Identifying Age-Related Conditions
13243,135516920,3689.0,0.3757622979850777,0,0,/nikhilrasineni/baseline-xgboost,ICR - Identifying Age-Related Conditions
13244,135366351,4374.0,,4,20,/alejopaullier/icr-train-1-million-models-in-1-hour,ICR - Identifying Age-Related Conditions
13245,136604559,1575.0,0.3822214329776346,0,0,/uyzz9755/icr-competition-2023,ICR - Identifying Age-Related Conditions
13246,138262234,2399.0,0.3849700783811852,0,0,/dshaoyuwang/icr-rf-01,ICR - Identifying Age-Related Conditions
13247,138013617,3211.0,0.4787965086837666,2,15,/helang05/prediction-using-bagged-random-forest-in-progres,ICR - Identifying Age-Related Conditions
13248,139478151,3813.0,,0,1,/ganeshborkar31/icr-identifying-age-related-condition,ICR - Identifying Age-Related Conditions
13249,137266208,4253.0,0.4001447619676017,0,3,/jcornels/identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13250,133712065,3739.0,0.4019342598244108,0,0,/gauthamdinanath/notebook-icr,ICR - Identifying Age-Related Conditions
13251,129848963,4127.0,0.4051550116340796,0,8,/mathyseizaecrepin/icr-binary-classification-xgb-model,ICR - Identifying Age-Related Conditions
13252,134578765,4130.0,0.4051550116340796,0,0,/amanmishra0210/notebookb4d2667e94,ICR - Identifying Age-Related Conditions
13253,131855186,4500.0,,0,3,/eugenebarykin/icr-logregr,ICR - Identifying Age-Related Conditions
13254,133148469,3092.0,0.4070620571016269,0,0,/xxswkl/neuralnetwork,ICR - Identifying Age-Related Conditions
13255,130062567,3927.0,0.4089386890702193,0,0,/sunil199/icr-iarc-eda-comparison-of-models,ICR - Identifying Age-Related Conditions
13256,132629011,4023.0,0.4158310919683983,0,0,/d0641915/notebooka56aeb7044,ICR - Identifying Age-Related Conditions
13257,132895815,2549.0,0.4190602738720038,6,38,/masatakaitakura/for-beginner-icr-eda-xgb-submission-baseline,ICR - Identifying Age-Related Conditions
13258,136205323,4453.0,,0,0,/markus427/agerelatedconditions,ICR - Identifying Age-Related Conditions
13259,139404906,3871.0,,0,0,/juzykaggle/catboost-accuracy-0-9558,ICR - Identifying Age-Related Conditions
13260,130003860,4867.0,0.4234757564522336,0,7,/iniyatj/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13261,130266493,4605.0,0.4249744299365968,0,2,/ninadaithal/age-related-conditions,ICR - Identifying Age-Related Conditions
13262,135196600,4613.0,0.4254455610823159,0,0,/mizoisho/icr-2023-06-07,ICR - Identifying Age-Related Conditions
13263,162574300,2932.0,0.2956210836487556,0,1,/vinodkumargurjar/ai-ml-icr-identifying-age-related-conditions-vinod,ICR - Identifying Age-Related Conditions
13264,139711794,4009.0,0.3230470767383315,0,5,/ashx010/icr-age-condition-identification,ICR - Identifying Age-Related Conditions
13265,130384677,4794.0,0.4478536077219058,0,19,/averma111/pytorch-icr,ICR - Identifying Age-Related Conditions
13266,129668327,3450.0,,5,28,/pehahn/eda-with-r,ICR - Identifying Age-Related Conditions
13267,129551823,2882.0,0.6962965916202376,0,0,/mehulgoyal94/notebook34acee4379,ICR - Identifying Age-Related Conditions
13268,138863403,4044.0,0.4753739808135671,0,0,/bibhumohapatra18/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13269,129549523,4475.0,,0,5,/johnericbonilla/data-exploration-pca-and-rf,ICR - Identifying Age-Related Conditions
13270,132234817,3411.0,,1,5,/hari31416/icr-eda-and-preprocessing,ICR - Identifying Age-Related Conditions
13271,139540144,3652.0,0.7403230858691949,0,0,/kusoyounderlined/icr-rf-xgb-lgbm-soft-voting-lb-0-60,ICR - Identifying Age-Related Conditions
13272,138988855,3988.0,0.579119323897744,0,5,/mohamedmaboshady/lgbm-classifer,ICR - Identifying Age-Related Conditions
13273,139460820,4697.0,0.571430780426851,0,0,/sodiqsulaimon/icr-comp-identifying-age-related-condition,ICR - Identifying Age-Related Conditions
13274,138282132,4413.0,0.5726314021387707,0,0,/danilosantosvieira/startmodelchallenge,ICR - Identifying Age-Related Conditions
13275,139235013,3900.0,0.5845002416488463,3,6,/saharkhazali/age-cmp,ICR - Identifying Age-Related Conditions
13276,134401478,4132.0,0.5851963861261551,0,1,/gaganbajwaa/icr-gagan,ICR - Identifying Age-Related Conditions
13277,139541625,4622.0,,0,0,/quantyrainc/icr-notebook,ICR - Identifying Age-Related Conditions
13278,135646381,3957.0,0.6028551367356735,4,19,/mridul2003/icr-identify-age,ICR - Identifying Age-Related Conditions
13279,139491914,4430.0,0.7662018560469238,7,16,/nikhilmunakhiya/icr-logistic-regression-0-62,ICR - Identifying Age-Related Conditions
13280,139461007,3925.0,0.6345497458570909,0,0,/miguelsaraiva82/icr-logistic-regression,ICR - Identifying Age-Related Conditions
13281,138899859,4467.0,0.6986906032931736,0,0,/narareddy/icr-feature-scaling-reduction-lr,ICR - Identifying Age-Related Conditions
13282,130673259,4006.0,2.874277209498001,0,0,/mahadihasantarunno/icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13283,166997237,4035.0,,0,6,/saipoojalakkoju/icr-problem,ICR - Identifying Age-Related Conditions
13284,138251615,4210.0,0.7289565400163507,0,1,/prasadmujumdar19/notebooke0a4eec56d,ICR - Identifying Age-Related Conditions
13285,131150679,4286.0,0.6658548679305952,0,0,/emxheena/icr-model-selection-histgradientboosting,ICR - Identifying Age-Related Conditions
13286,167010211,4491.0,,5,25,/reymaster/starter-greeks-w-iterative-imputation-ensemble,ICR - Identifying Age-Related Conditions
13287,130726551,4661.0,,0,4,/soyabulislamlincoln/icr-data-eda-baseline,ICR - Identifying Age-Related Conditions
13288,133911896,4512.0,,2,8,/diodupont/eda-randonforest-balanced-log-loss,ICR - Identifying Age-Related Conditions
13289,139551423,4443.0,13.948352005637004,0,0,/andrewj90/fork-of-lb-probe-example,ICR - Identifying Age-Related Conditions
13290,129725435,4145.0,,1,5,/pradeepsapparapu/icr-identifying-age-related-eda-model-sub,ICR - Identifying Age-Related Conditions
13291,135475499,4170.0,0.6931471805599468,0,0,/mayankrakesh121/age-related-condition-tsne-feature-engineering,ICR - Identifying Age-Related Conditions
13292,136812960,4173.0,,0,0,/muhammadhadi28/rf-icr-identifying-age,ICR - Identifying Age-Related Conditions
13293,136596896,4770.0,,0,3,,ICR - Identifying Age-Related Conditions
13294,139640707,4180.0,,0,0,/ahsh37/identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13295,134536393,4205.0,2.567102021379366,0,0,/taegeunpark/icr-rf-lr-xgb-ipynb,ICR - Identifying Age-Related Conditions
13296,134826542,4774.0,0.7149243556893304,0,0,/dhritidas/icr-xgclassifier,ICR - Identifying Age-Related Conditions
13297,138397310,4614.0,,2,22,/farshidhossain68/icr-with-ml-models-and-xgboost,ICR - Identifying Age-Related Conditions
13298,132805418,4561.0,0.7599069953346708,0,12,/i191796majid/icr-eda-ensemble,ICR - Identifying Age-Related Conditions
13299,139474451,4403.0,,0,4,/muhriddinmalik/icr-identify-age-related-condition,ICR - Identifying Age-Related Conditions
13300,135050031,4408.0,0.826836246377272,0,0,/heshamsaber/voting-gridsearch,ICR - Identifying Age-Related Conditions
13301,130573310,4466.0,,0,1,/soumyapati/icr-prediction-python,ICR - Identifying Age-Related Conditions
13302,146761924,5439.0,,0,0,/manish123kaggle/icr-age-detection,ICR - Identifying Age-Related Conditions
13303,137336907,4178.0,,0,2,/dminchev1/notebookd3c62ff6af,ICR - Identifying Age-Related Conditions
13304,133585381,4807.0,,0,2,,ICR - Identifying Age-Related Conditions
13305,139554476,4710.0,0.8388648721330679,0,0,/sanjaygandotra/age-related-conditions,ICR - Identifying Age-Related Conditions
13306,131317690,4835.0,0.8972420965907044,0,6,/mzaoualim/kaggle-icr,ICR - Identifying Age-Related Conditions
13307,130228801,4869.0,,0,10,/divyanshikapoor05/icr-eda-for-beginners,ICR - Identifying Age-Related Conditions
13308,137473641,4641.0,0.9260372688126494,0,1,/pranaliyangandul/icr-xgb-randomizedsearchcv-with-pipeline,ICR - Identifying Age-Related Conditions
13309,138672955,4686.0,2.0006099419146546,0,8,/egorphysics/pytorch-optuna-baseline,ICR - Identifying Age-Related Conditions
13310,138672955,4686.0,2.1014630957604834,0,8,/egorphysics/pytorch-optuna-baseline,ICR - Identifying Age-Related Conditions
13311,135531117,4654.0,,0,6,/awaldeep/first-look-eda-baseline-sub-0-26-val-logloss,ICR - Identifying Age-Related Conditions
13312,134220375,4970.0,1.311851682425193,0,0,/xirongcui/notebook14483d972c,ICR - Identifying Age-Related Conditions
13313,133427957,4815.0,,0,2,/justinmustaine/rfc-gridsearch,ICR - Identifying Age-Related Conditions
13314,130352188,4989.0,,0,2,/duncankmckinnon/icr-analysis-in-r,ICR - Identifying Age-Related Conditions
13315,136382208,4936.0,10.8229034565023,12,19,/arvindh22/icr-age-related-conditions,ICR - Identifying Age-Related Conditions
13316,138888444,4949.0,5.36448339210995,4,5,/aarushi211/xgbclassifier-with-cv,ICR - Identifying Age-Related Conditions
13317,136889682,4951.0,4.401150600271685,0,4,/seydougoro/agerelatedconditionidentification,ICR - Identifying Age-Related Conditions
13318,136889682,4951.0,2.102252242024269,0,4,/seydougoro/agerelatedconditionidentification,ICR - Identifying Age-Related Conditions
13319,135836181,5074.0,2.307610260920799,0,13,/kaggleprollc/icr-usingrf,ICR - Identifying Age-Related Conditions
13320,136584993,5196.0,2.599657257406312,0,0,/guilhermealt/icr-submission,ICR - Identifying Age-Related Conditions
13321,142171635,5240.0,22.82115487228192,0,0,/brahimmohamed/icr-convolution,ICR - Identifying Age-Related Conditions
13322,134769989,5442.0,,2,10,/sergeyyakovlev1312/icr-classification,ICR - Identifying Age-Related Conditions
13323,130308056,6336.0,5.870734945536927,0,0,/pavandev/notebook23dd0879e2,ICR - Identifying Age-Related Conditions
13324,138154658,6370.0,,0,0,/spike8086/identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13325,139501892,6343.0,7.760948063773041,0,0,/vladshatrovsky/identifying-age-related-conditions-with-pytorch,ICR - Identifying Age-Related Conditions
13326,131098611,6394.0,,0,6,/kondetisandeep/icr-identifying-related-conditions,ICR - Identifying Age-Related Conditions
13327,134627439,6428.0,30.79993242412164,0,0,/ludwigsaux/test-icr-identifying-age-related-conditions,ICR - Identifying Age-Related Conditions
13328,136920150,1.0,1.0,37,95,/iamleonie/towards-green-ai,2023 Kaggle AI Report
13329,136970653,6.0,6.0,15,21,/pluvias/kaggle-ai-report-optimization,2023 Kaggle AI Report
13330,135585724,9.0,,3,30,/thedrcat/using-llms-to-extract-structured-data,2023 Kaggle AI Report
13331,136936013,11.0,,11,29,/pranavbelhekar/a-glimpse-into-the-realm-of-generative-ai,2023 Kaggle AI Report
13332,165459900,19.0,,13,19,/nghihuynh/kaggle-ai-report-medical-imaging-competitions,2023 Kaggle AI Report
13333,136963644,25.0,,12,54,/nlztrk/generative-ai-a-renaissance-in-creativity,2023 Kaggle AI Report
13334,136977467,31.0,,5,12,/niyamatalmass/generative-ai-tools-landscape,2023 Kaggle AI Report
13335,136959886,32.0,32.0,31,85,/sanjushasuresh/generative-ai-creating-machines-more-human-like,2023 Kaggle AI Report
13336,136971178,35.0,,10,7,/anaghasavit/kagglecompetitionsessay,2023 Kaggle AI Report
13337,141645554,36.0,,4,25,/kobbiemanrique/tabular-data-in-the-age-of-ai,2023 Kaggle AI Report
13338,136746017,37.0,37.0,24,19,/raimondextervinluan/2023-kaggle-ai-report-ai-ethics,2023 Kaggle AI Report
13339,137145004,39.0,,6,8,/eklavya12/generative-ai-a-report,2023 Kaggle AI Report
13340,136965543,42.0,,2,10,/kaungmyatkyaw/antique-enthusiasts-image-and-or-video-data,2023 Kaggle AI Report
13341,139414213,43.0,,6,6,/monicasusan/through-the-eyes-of-ai,2023 Kaggle AI Report
13342,136970603,44.0,44.0,6,2,/prathmeshadsod/dive-in-computer-vision,2023 Kaggle AI Report
13343,137101393,56.0,,42,48,/mistylight/mini-giants-small-language-models,2023 Kaggle AI Report
13344,136976663,58.0,,8,6,/akinremibunmi/principles-vs-implementation-ai-ethics,2023 Kaggle AI Report
13345,136895277,61.0,61.0,55,42,/luckypen/actionable-ai-ethics,2023 Kaggle AI Report
13346,167012579,62.0,,3,9,/dhorvay/kaggle-is-the-global-data-science-classroom,2023 Kaggle AI Report
13347,136647975,63.0,63.0,7,6,/kingabzpro/from-analysis-to-ai-the-journey-of-tabular-data,2023 Kaggle AI Report
13348,136975720,64.0,,3,8,/megan3/ai-ethics-and-covid-19,2023 Kaggle AI Report
13349,136934935,66.0,66.0,7,9,/veronikasarikaya/what-is-new-on-ai-ethics,2023 Kaggle AI Report
13350,135820852,67.0,,4,13,/muhammadirfanakbar/kaggle-ai-report-viz,2023 Kaggle AI Report
13351,137278116,69.0,,5,7,/dm2022/generative-ai-future-is-in-our-hands,2023 Kaggle AI Report
13352,136961779,74.0,74.0,4,4,/soumyaoruganti/image-segmentation-ai-report-2023,2023 Kaggle AI Report
13353,136757532,77.0,77.0,10,18,/crodoc/relevance-of-kaggle-competitions-for-real-life,2023 Kaggle AI Report
13354,136932332,79.0,79.0,8,12,/juanricardop/2023-ai-report-kaggle-competitions,2023 Kaggle AI Report
13355,159618088,80.0,,4,4,/afamos/ai-reports,2023 Kaggle AI Report
13356,136815780,81.0,,2,6,/dmitriygakh/see-slmhm-spem-maturity-tests-lstm-glove,2023 Kaggle AI Report
13357,136552740,83.0,83.0,9,11,/denismunene/the-advancement-of-kaggle-competitions-over-years,2023 Kaggle AI Report
13358,137241333,84.0,,9,15,/deepthiaj/meta-kaggle-analytics-exploring-ai-trends-21-23,2023 Kaggle AI Report
13359,136528527,94.0,,31,43,/soniadsilva/ai-at-the-cutting-edge-of-medical-imaging,2023 Kaggle AI Report
13360,136661359,95.0,95.0,9,4,/sabrinahan/kaggle-image-and-video-related-ai-report,2023 Kaggle AI Report
13361,136945396,107.0,107.0,3,0,/datamafia7/a-text-odyssey-the-past-present-and-future-of-nlp,2023 Kaggle AI Report
13362,135844465,113.0,,10,26,/harshadakushe/text-to-image-the-journey-so-far,2023 Kaggle AI Report
13363,136854317,125.0,125.0,8,13,/yeemeitsang/unreasonably-effective-ensemble-learning,2023 Kaggle AI Report
13364,136556049,138.0,,6,10,/vinitkp/text-data,2023 Kaggle AI Report
13365,149034906,149.0,,34,48,/emirhanbilgic/ai-ethics-we-are-about-to-be-late,2023 Kaggle AI Report
13366,136970147,152.0,,2,9,/aliwisterr/transfomers-for-time-series-forecasting,2023 Kaggle AI Report
13367,135743603,153.0,153.0,2,6,/abdulkhadarn/the-tab-and-the-time,2023 Kaggle AI Report
13368,136973586,154.0,154.0,12,17,/insiyajafferji/kaggle-competitions-for-biological-sciences,2023 Kaggle AI Report
13369,134898539,160.0,160.0,5,6,/lrsowmya/kaggle-empowering-data-enthusiasts-to-learn-by-do,2023 Kaggle AI Report
13370,136978549,162.0,,0,1,/dylanwaste/topic-salience-in-the-academic-literature,2023 Kaggle AI Report
13371,136964209,172.0,172.0,4,13,/ritwikdalmia/unlocking-the-promise-ai-ethics-in-action,2023 Kaggle AI Report
13372,136845855,176.0,,5,2,/umesalma/deep-dive-into-rsna-breast-cancer-detection,2023 Kaggle AI Report
13373,133557988,180.0,,3,2,/jonasaacampos/artigos-ethics,2023 Kaggle AI Report
13374,135836523,183.0,183.0,2,2,/umuttoygargoz/time-series-forecasting,2023 Kaggle AI Report
13375,141020931,184.0,,4,7,/vcolliym/climate-research,2023 Kaggle AI Report
13376,135745978,187.0,,1,0,/ingmanueljerez/we-are-taking-important-decision-about-ai-ethics,2023 Kaggle AI Report
13377,135730954,189.0,,10,4,/varunkabra123/data-and-time-series,2023 Kaggle AI Report
13378,137172304,191.0,,9,1,/laalinibhgoadi/kaggle-ai-report-for-tabular-and-time-series-data,2023 Kaggle AI Report
13379,132445171,199.0,199.0,1,0,/mainaksil/ai-report-a-first-look-at-the-data-for-text-data,2023 Kaggle AI Report
13380,136111495,201.0,201.0,4,4,/bacharacherif/recap-2023-kaggle-ai-report-eda,2023 Kaggle AI Report
13381,135831759,202.0,,10,7,/naturalray/the-change-in-kaggle-competitions,2023 Kaggle AI Report
13382,129312965,203.0,,24,29,/mpwolke/ai-ethics-my-write-oops,2023 Kaggle AI Report
13383,136300525,208.0,,4,3,/barbosajaf/jafb-2023-kaggle-ai-report,2023 Kaggle AI Report
13384,130276504,209.0,,3,10,/plarmuseau/grab-the-competitiondata,2023 Kaggle AI Report
13385,136975599,214.0,214.0,2,3,/jennifersantiago/ai-ethical,2023 Kaggle AI Report
13386,135392316,215.0,,3,8,/saharkhazali/final-ai-report-tabular-time-series,2023 Kaggle AI Report
13387,135657142,218.0,,0,3,/binarybeast880/kaggle-ai-report,2023 Kaggle AI Report
13388,135751234,219.0,219.0,0,0,/mayanessmith/notebook887398217d,2023 Kaggle AI Report
13389,131405239,289.0,0.0754651891766178,0,3,/alexeygankov/fill-nans-with-catboost,Feature Imputation with a Heat Flux Dataset
13390,130314186,123.0,,0,12,/satyaprakashshukl/simple-boost-xgb,Feature Imputation with a Heat Flux Dataset
13391,135483182,215.0,,0,4,/yeoyunsianggeremie/s3e15-ensemble-knn-imputation-score-0-72854,Feature Imputation with a Heat Flux Dataset
13392,130456537,225.0,,1,20,/ramjasmaurya/ps-3-15-simple-imputation-modelling,Feature Imputation with a Heat Flux Dataset
13393,129994963,31.0,0.0758032738479183,4,20,/oscarm524/ps-s3-ep15-eda-modeling-submission,Feature Imputation with a Heat Flux Dataset
13394,130605732,96.0,,1,9,/elskowaski/ps-s3e15,Feature Imputation with a Heat Flux Dataset
13395,129753195,110.0,0.0752392433289777,1,10,/e271828ai/ps-s3-e15-01-simplebaseline-en-jp-20230516,Feature Imputation with a Heat Flux Dataset
13396,131686591,13.0,0.075660665584582,0,2,/braveplayer/top-1-lgbm-catboost,Feature Imputation with a Heat Flux Dataset
13397,130723579,83.0,,0,9,/sitbayevalibek/feature-imputation-competition1,Feature Imputation with a Heat Flux Dataset
13398,131545414,68.0,,0,0,/drrajkulkarni/play-ground-s3e15-test,Feature Imputation with a Heat Flux Dataset
13399,129732285,23.0,0.0760156001228009,0,12,/dongjun819/pgs315-eda-lgbm,Feature Imputation with a Heat Flux Dataset
13400,130034832,230.0,,0,10,/xclimx/kps-s03e15-minimalistic-autogluon-lb-0-075180,Feature Imputation with a Heat Flux Dataset
13401,129739392,172.0,,0,8,/jakubrogulski/pgs315-eda,Feature Imputation with a Heat Flux Dataset
13402,131468993,186.0,0.0749810263515773,0,0,/kkityama/feature-imputation-with-a-heat-flux-dataset,Feature Imputation with a Heat Flux Dataset
13403,130504532,350.0,0.0799705297879921,0,7,/dhanrajmalla/knn-imputer-for-imputation,Feature Imputation with a Heat Flux Dataset
13404,148366795,141.0,,1,33,/ashishkumarak/feature-imputation-with-heat-flux-dataset,Feature Imputation with a Heat Flux Dataset
13405,130402427,404.0,,1,7,/krbharat/p3-e15-catboost-model-iterative-imputation,Feature Imputation with a Heat Flux Dataset
13406,130137036,405.0,0.0793360996890919,1,6,/minhazengg/heatflux-2,Feature Imputation with a Heat Flux Dataset
13407,133264497,365.0,,19,38,/suraj520/step-by-step-analysis-towards-feature-imputation,Feature Imputation with a Heat Flux Dataset
13408,131133359,406.0,,0,6,/meghanachebolu/01-feature-imputation-final,Feature Imputation with a Heat Flux Dataset
13409,130894428,257.0,0.0884490285706691,1,3,/ajayrahulprasad/feature-imputation-02,Feature Imputation with a Heat Flux Dataset
13410,130513726,408.0,,1,15,/srilaasyakandukuri/s3e15cat-boost,Feature Imputation with a Heat Flux Dataset
13411,130571938,384.0,0.0767847834494157,1,15,/gautamimamidala/feature-imputation-with-a-heat-flux-1,Feature Imputation with a Heat Flux Dataset
13412,130630824,409.0,,1,12,/suvarnayandapalli/feature-imputation,Feature Imputation with a Heat Flux Dataset
13413,130922363,415.0,0.0750094558971336,0,10,/bhuvanagayathri/feature-imputation-with-a-heat-flux-dataset,Feature Imputation with a Heat Flux Dataset
13414,130664770,368.0,0.0777909902502883,0,8,/baireddypranayreddy/nairain,Feature Imputation with a Heat Flux Dataset
13415,130953699,418.0,,0,4,/vissapragadasandeep/heat-flux,Feature Imputation with a Heat Flux Dataset
13416,135353206,420.0,,7,25,/mohammadrazeghi/p03e15-preprocess-pipeline-baseline-xgboost,Feature Imputation with a Heat Flux Dataset
13417,130182318,369.0,0.0978447421029735,0,8,/atuljo/a-simple-model-to-implement-with-modification,Feature Imputation with a Heat Flux Dataset
13418,131485880,419.0,0.0752227838989867,0,7,/tolgaik/ps-s3-e15-catboost-modeling-score-0-075076,Feature Imputation with a Heat Flux Dataset
13419,131115876,398.0,0.0759546111411932,5,26,/ivanvaccari/ps3e15-catboostregressor-hyper-optimized,Feature Imputation with a Heat Flux Dataset
13420,129754575,175.0,,2,28,/onurkoc83/lgbm-sample-sub-lb-score-0-076194,Feature Imputation with a Heat Flux Dataset
13421,130091895,176.0,,0,8,/nedadarbeheshti/feature-imputation,Feature Imputation with a Heat Flux Dataset
13422,131434677,325.0,,1,2,/newdatasc/lgbm-catboost-public-score-0-075105,Feature Imputation with a Heat Flux Dataset
13423,130590664,223.0,0.0762888799319526,0,1,/sec98b4e/ps3e15-lgbm,Feature Imputation with a Heat Flux Dataset
13424,131132596,63.0,0.0758360733311619,2,12,/rzatemizel/stacking-with-pipeline,Feature Imputation with a Heat Flux Dataset
13425,131016152,200.0,0.077499785265056,12,34,/sujaykapadnis/ps-s3e15-comparing-imputation-techniques,Feature Imputation with a Heat Flux Dataset
13426,131016152,200.0,0.0950064270077972,12,34,/sujaykapadnis/ps-s3e15-comparing-imputation-techniques,Feature Imputation with a Heat Flux Dataset
13427,131644267,11.0,,7,11,/dev7halo/11th-automl-is-all-you-need,Feature Imputation with a Heat Flux Dataset
13428,130860463,293.0,,2,4,/minkhantmk19/eda-xgboost-pipeline-beginner-s3e15,Feature Imputation with a Heat Flux Dataset
13429,130991368,455.0,0.0753616962010192,0,5,/akhilnambir789/notebook960ab50a66,Feature Imputation with a Heat Flux Dataset
13430,130087495,153.0,0.075567056382982,0,12,/majidabdoos/ps3e15-lgbmimputer-simple-model-lb-0-075567,Feature Imputation with a Heat Flux Dataset
13431,130590275,124.0,,0,6,/erfansobhaei/heat-flux-imputation,Feature Imputation with a Heat Flux Dataset
13432,130506763,198.0,0.0757005782551294,0,7,/jayeshsonawane/ps3e15-lgbm-0-075387-knn-imputation,Feature Imputation with a Heat Flux Dataset
13433,131383673,301.0,,4,34,/akioonodera/ps-3-15-lgbm-reg,Feature Imputation with a Heat Flux Dataset
13434,131478976,217.0,0.0758121875061604,0,0,/bogdandoicin/s3e15-algorithm-comparing,Feature Imputation with a Heat Flux Dataset
13435,131525272,115.0,,0,2,/samvelkoch/automl-pycaret-solution-tabular-series-s3e15,Feature Imputation with a Heat Flux Dataset
13436,130411514,206.0,0.0792874993009813,2,8,/natsu18/pgs-s3e15,Feature Imputation with a Heat Flux Dataset
13437,131239664,336.0,,0,12,/ernestglukhov/simple-solution-with-random-forest,Feature Imputation with a Heat Flux Dataset
13438,129854198,54.0,0.0856500249540399,0,6,/jimgruman/heat-flux,Feature Imputation with a Heat Flux Dataset
13439,131091015,39.0,0.0764771523959962,0,28,/docxian/ps-s3-e15-imputation-with-r,Feature Imputation with a Heat Flux Dataset
13440,131091015,39.0,0.0778253883642663,0,28,/docxian/ps-s3-e15-imputation-with-r,Feature Imputation with a Heat Flux Dataset
13441,130530889,266.0,0.0770436534491149,1,8,/elmo27/playground-3-15-imputing-catboost,Feature Imputation with a Heat Flux Dataset
13442,130355941,178.0,,2,7,/mustafabayhan/missing-value-imputation-and-catboost,Feature Imputation with a Heat Flux Dataset
13443,131371532,216.0,0.0756523111238265,0,4,/imessam/catboost-lightgbm-xgboost,Feature Imputation with a Heat Flux Dataset
13444,131032558,5.0,0.0756820125127136,23,108,/iqbalsyahakbar/ps3e15-eda-imputing-ensemble-for-beginners,Feature Imputation with a Heat Flux Dataset
13445,129935246,401.0,,1,4,/barbagrande007/bbg-007-s3e15-chf-autoencoder,Feature Imputation with a Heat Flux Dataset
13446,130564864,334.0,,0,4,/keitashimizu21/ja-en-modeling-predicting-critical-heat-flux,Feature Imputation with a Heat Flux Dataset
13447,131497783,119.0,0.0758940902929545,0,0,/kenjif/ps-3-15-auto-ml-blend-models-top2,Feature Imputation with a Heat Flux Dataset
13448,130183949,355.0,0.0759493735791446,0,2,/deepakjeff/feature-imputation,Feature Imputation with a Heat Flux Dataset
13449,129770349,327.0,0.0760157465058863,0,4,/iniyatj/ps-s3e15-beginner-guide,Feature Imputation with a Heat Flux Dataset
13450,130725789,431.0,,0,3,/nolanmeyer/ps-s3-e15-original-vs-synthetic-eda,Feature Imputation with a Heat Flux Dataset
13451,130710218,191.0,0.0758102701422347,2,13,/aakashs57/ps3e15-xgboost-lightgbm,Feature Imputation with a Heat Flux Dataset
13452,129961284,203.0,0.0770418434087059,0,2,/devildev89/ps-3-15-submission,Feature Imputation with a Heat Flux Dataset
13453,130348811,253.0,,0,6,/lukastaylor2/heat-flux-miceforest-and-pycaret,Feature Imputation with a Heat Flux Dataset
13454,131147356,381.0,,0,0,/alexbostick/cat-regression-heat-flux,Feature Imputation with a Heat Flux Dataset
13455,131381684,317.0,0.0761964151796073,2,11,/cv13j0/experimenting-with-feature-imputation-ideas,Feature Imputation with a Heat Flux Dataset
13456,131381684,317.0,0.0765717850581357,2,11,/cv13j0/experimenting-with-feature-imputation-ideas,Feature Imputation with a Heat Flux Dataset
13457,129802918,168.0,,1,6,/gauravduttakiit/pss3e15-lazypredict,Feature Imputation with a Heat Flux Dataset
13458,130021115,149.0,0.0766675765128405,1,8,/klyushnik/h2o-automl,Feature Imputation with a Heat Flux Dataset
13459,129978097,244.0,0.0760539843775267,0,5,/wasshoiwasshoi/ps-s3e15-eda-and-lightgbmbaseline,Feature Imputation with a Heat Flux Dataset
13460,130941650,212.0,0.0952577655230761,0,4,/jankuper192/eda-orginal-set-playground-mice-missforest,Feature Imputation with a Heat Flux Dataset
13461,131123678,439.0,,0,6,/hakhali99/fluxxx,Feature Imputation with a Heat Flux Dataset
13462,131556145,348.0,,0,11,/yamanju/playground-series-season-3-15-eda,Feature Imputation with a Heat Flux Dataset
13463,129806406,397.0,0.0761889075294696,0,11,/ranjeetshrivastav/heat-flux-catboost-baseline,Feature Imputation with a Heat Flux Dataset
13464,131058325,460.0,,9,14,/jagadishrcz/heat-flux-s3ep15,Feature Imputation with a Heat Flux Dataset
13465,131582905,373.0,,0,0,/strategos2/playground-series-season-3-episode-15,Feature Imputation with a Heat Flux Dataset
13466,131500418,218.0,0.0763324386813377,2,8,/ceyhunsahin/xgboost-optuna,Feature Imputation with a Heat Flux Dataset
13467,131500418,218.0,0.0763324386813377,2,8,/ceyhunsahin/xgboost-optuna,Feature Imputation with a Heat Flux Dataset
13468,129738258,374.0,,0,8,/kaizen97/eda-xbg-lgbm,Feature Imputation with a Heat Flux Dataset
13469,130100186,297.0,0.0776121411742105,0,4,/scodepy/feature-imputation-with-a-heat-flux-dataset-ipynb,Feature Imputation with a Heat Flux Dataset
13470,130662509,433.0,,0,7,/kondetisandeep/heat-flux-imputation,Feature Imputation with a Heat Flux Dataset
13471,131436076,493.0,,2,15,/mandapallijahnavi/feature,Feature Imputation with a Heat Flux Dataset
13472,129902071,393.0,0.0766954366033892,0,2,/paw27182/ps3e15-iterativeimputer-lgbmregressor,Feature Imputation with a Heat Flux Dataset
13473,131448772,449.0,0.0774254436881462,0,3,/manishkumar7432698/knn-imputer,Feature Imputation with a Heat Flux Dataset
13474,130710728,484.0,0.7912901345135422,1,6,/jimmyyeung/ps3-15-heat-flux-gradient-boost,Feature Imputation with a Heat Flux Dataset
13475,131728160,328.0,,3,12,/shashankjat10/heat-flux-imputation-nn-xgboost,Feature Imputation with a Heat Flux Dataset
13476,130755750,392.0,0.0769286095397756,0,2,/edwinhung/heatflux-fastai-tabularpandas,Feature Imputation with a Heat Flux Dataset
13477,131530322,372.0,,2,14,/bindunethala/heat-flux-model,Feature Imputation with a Heat Flux Dataset
13478,129769363,430.0,0.0776181368922992,0,4,/amarloni/pgs3-e15,Feature Imputation with a Heat Flux Dataset
13479,131496792,441.0,,6,40,/panini92/heat-flux-ps3e15-eda-catboost-missing-values,Feature Imputation with a Heat Flux Dataset
13480,130421593,500.0,0.0771269636270824,0,4,/frankostyn/mice-lgbm,Feature Imputation with a Heat Flux Dataset
13481,129895365,403.0,0.077211723161692,1,9,/aman7kumar/ensemble-of-randomforest-gradientboost-catboost,Feature Imputation with a Heat Flux Dataset
13482,130863247,515.0,,0,5,/shubhamsingh57/catboost-beginner-s,Feature Imputation with a Heat Flux Dataset
13483,130297325,507.0,0.0775302375818737,0,2,/samir95/the-imputation-toolbox,Feature Imputation with a Heat Flux Dataset
13484,130297325,507.0,0.0775302375818737,0,2,/samir95/the-imputation-toolbox,Feature Imputation with a Heat Flux Dataset
13485,131009955,509.0,,0,10,/brpuneet898/heat-influx-complete-code,Feature Imputation with a Heat Flux Dataset
13486,129720656,479.0,0.0780152891686643,12,28,/kdmitrie/pgs315-easy-use-of-h2o-automl,Feature Imputation with a Heat Flux Dataset
13487,130670046,510.0,,0,4,/manojkumarpentapalli/heat-flux-imputation,Feature Imputation with a Heat Flux Dataset
13488,131243239,524.0,0.077871183013702,0,5,/killershoaib/ps-e15-pipeline-gboost-heat-flux-imputation,Feature Imputation with a Heat Flux Dataset
13489,130170300,522.0,0.0838349488551169,1,7,/scirpus/fluxy-mcfluxface,Feature Imputation with a Heat Flux Dataset
13490,141497857,581.0,,0,5,/kvasart/heat-flux-catboost-testing,Feature Imputation with a Heat Flux Dataset
13491,131399316,573.0,,8,26,/aakashjoshi123/heatflux,Feature Imputation with a Heat Flux Dataset
13492,131463231,565.0,0.0804114038322225,1,7,/arshmodak/eda-data-prep-and-basic-ml-pipe-for-heatflux-data,Feature Imputation with a Heat Flux Dataset
13493,130245987,571.0,,0,2,/yukashihara/impute-missing-values-with-knn-imputer,Feature Imputation with a Heat Flux Dataset
13494,131263067,589.0,0.0824142844409147,0,5,/rfeng12/easily-customizable-neural-network,Feature Imputation with a Heat Flux Dataset
13495,131263067,589.0,0.0824142844409147,0,5,/rfeng12/easily-customizable-neural-network,Feature Imputation with a Heat Flux Dataset
13496,164819133,603.0,0.0842905011110545,0,5,/muhriddinmalik/feature-imputation-with-a-heat-flux-notebook-of-mk,Feature Imputation with a Heat Flux Dataset
13497,130488234,609.0,0.0849620575255154,0,8,/awesomeharris/ps3e15-feature-imputation-with-heat-flux-dataset,Feature Imputation with a Heat Flux Dataset
13498,129962762,610.0,0.0846084025281521,0,2,/nandomartinez/episode-15-baseline-with-knn-imputation,Feature Imputation with a Heat Flux Dataset
13499,131212378,598.0,0.0897588047411939,0,1,/vishweshhampali/ps-s3e14-imputation-using-linearregression-knn,Feature Imputation with a Heat Flux Dataset
13500,131212378,598.0,0.0848301454586332,0,1,/vishweshhampali/ps-s3e14-imputation-using-linearregression-knn,Feature Imputation with a Heat Flux Dataset
13501,131212378,598.0,0.0896755652021194,0,1,/vishweshhampali/ps-s3e14-imputation-using-linearregression-knn,Feature Imputation with a Heat Flux Dataset
13502,130842193,632.0,0.089951791048781,0,2,/gitashojaee/feature-imputation-iterativeimputer,Feature Imputation with a Heat Flux Dataset
13503,130212724,648.0,0.101383908053941,0,15,/averma111/pytorch-ps3e15-optuna,Feature Imputation with a Heat Flux Dataset
13504,130479604,669.0,0.1019043746584911,4,13,/jocelyndumlao/chf-prediction-analysis,Feature Imputation with a Heat Flux Dataset
13505,131316645,673.0,0.1128653309396672,0,1,/datascientistsohail/heat-flux-imputation-se03-ep15,Feature Imputation with a Heat Flux Dataset
13506,129949053,685.0,0.1353147902475563,0,2,/tracyporter/play-3-15-impute,Feature Imputation with a Heat Flux Dataset
13507,131377792,689.0,,0,2,/moh3we5/feature-imputation-with-a-heat-flux-dataset-0-086,Feature Imputation with a Heat Flux Dataset
13508,131451860,692.0,0.7921062933109299,0,1,/zahraalidadi75/feature-imputation-eda-with-xgboost-model,Feature Imputation with a Heat Flux Dataset
13509,135292741,241.0,,34,57,/atom1231/hubmap-mmdet-2-26-public-inference,HuBMAP - Hacking the Human Vasculature
13510,133516969,33.0,,0,2,/kaerunantoka/hubmap-tf-instance-segm-create-tfrecord-training,HuBMAP - Hacking the Human Vasculature
13511,133223842,286.0,,0,2,/yosukeyama/hubmap23-mmdet-train-mask2former-1024,HuBMAP - Hacking the Human Vasculature
13512,139258238,4.0,,0,0,/damtrongtuyen/training-hubmap-yolov6m,HuBMAP - Hacking the Human Vasculature
13513,132758429,741.0,,4,46,/itsuki9180/hubmap-making-dataset,HuBMAP - Hacking the Human Vasculature
13514,139788683,13.0,0.4793793223131425,0,4,/kiinngdom7/hubmap-hhv-13th-place-inference,HuBMAP - Hacking the Human Vasculature
13515,137519645,238.0,0.4652302602848592,0,4,/holmes0610/hubmap2023-inference,HuBMAP - Hacking the Human Vasculature
13516,139357383,1.0,0.3171109472437366,1,6,/tascj0/hubmap-2023-release,HuBMAP - Hacking the Human Vasculature
13517,135469850,80.0,0.4658010393406515,0,0,/shigengtian/yolov8-inferernce,HuBMAP - Hacking the Human Vasculature
13518,134896584,272.0,,2,1,/befunny/train-yolov8-baseline,HuBMAP - Hacking the Human Vasculature
13519,134889722,780.0,0.0297580649523333,7,7,/kongzhangtang/hubmap-unetplusplus-inference,HuBMAP - Hacking the Human Vasculature
13520,138469382,242.0,,0,4,/bhavesjain/hubmap-2023-cascade-rcnn,HuBMAP - Hacking the Human Vasculature
13521,137361941,513.0,0.4006703957268816,0,2,/zhuyu2/hubmap-mmdet3-1-single-fold-inference,HuBMAP - Hacking the Human Vasculature
13522,135939601,451.0,,2,15,/leoand00/hubmap-prediction-visualization,HuBMAP - Hacking the Human Vasculature
13523,135472543,799.0,,0,3,/vishakkbhat/mask-rcnn-cascading,HuBMAP - Hacking the Human Vasculature
13524,132763668,237.0,,0,2,/alabibojesomo/inference-yolo,HuBMAP - Hacking the Human Vasculature
13525,134543672,37.0,0.443859594927307,0,0,/abebe9849/yolo-v8-inference,HuBMAP - Hacking the Human Vasculature
13526,130980383,699.0,0.0,0,10,/michalaffek/sample-submission-dummy-seg-score-0-000,HuBMAP - Hacking the Human Vasculature
13527,134762462,728.0,,2,18,/hengck23/lb4-09-baseline-yolov7,HuBMAP - Hacking the Human Vasculature
13528,137956455,590.0,,0,75,/ammarnassanalhajali/hubmap-2023-k-fold-cv-coco-dataset-generator,HuBMAP - Hacking the Human Vasculature
13529,135977451,737.0,,0,0,/ttkaixin/hubmap-unet,HuBMAP - Hacking the Human Vasculature
13530,134782419,248.0,0.2136655774504638,0,16,/namgalielei/hubmap-cv-score-map-calculator,HuBMAP - Hacking the Human Vasculature
13531,136327162,245.0,,3,20,/maxchen303/hubmap-openimages-eval-metrics-for-validation,HuBMAP - Hacking the Human Vasculature
13532,133098172,679.0,,0,10,/saworz/hubmap-how-to-draw-polygons-on-images,HuBMAP - Hacking the Human Vasculature
13533,137121505,595.0,,1,5,/whybeaking/hubmap-mmdet3-1-training,HuBMAP - Hacking the Human Vasculature
13534,138476297,598.0,0.0704144216273927,0,4,/haokaigao/testttt,HuBMAP - Hacking the Human Vasculature
13535,138476297,598.0,0.0704144216273927,0,4,/haokaigao/testttt,HuBMAP - Hacking the Human Vasculature
13536,131246889,209.0,,0,15,/mohammaddehghan/hubmap-pytorch-baseline,HuBMAP - Hacking the Human Vasculature
13537,135377916,620.0,,0,0,/robotng/yolov8-infer-check,HuBMAP - Hacking the Human Vasculature
13538,136252273,624.0,1.3253810470510272e-05,0,1,/amitkumar122294/notebook6caabf113a,HuBMAP - Hacking the Human Vasculature
13539,138934539,626.0,,1,6,/yassinealouini/kidney-vascular-eda,HuBMAP - Hacking the Human Vasculature
13540,138029668,402.0,0.3648646108385249,0,0,/skeller/hubmap-mmdet3-1-single-fold-inference,HuBMAP - Hacking the Human Vasculature
13541,135739077,105.0,,0,4,/daaadaaa/convert-training-data-to-coco-folds,HuBMAP - Hacking the Human Vasculature
13542,135326312,642.0,,6,9,/josipvrdoljak/u-net-train,HuBMAP - Hacking the Human Vasculature
13543,134947085,464.0,,4,6,/camillagretschel/hubmap-training,HuBMAP - Hacking the Human Vasculature
13544,137363712,349.0,0.1408224964879762,0,0,/haozhou1009/hubmap-smp-inference,HuBMAP - Hacking the Human Vasculature
13545,131703407,568.0,,2,31,/benihime91/hubmap-2023-create-coco-annotations,HuBMAP - Hacking the Human Vasculature
13546,135144105,693.0,,11,24,/andtaichi/hubmap-mmdet-ver3-0-0-infer,HuBMAP - Hacking the Human Vasculature
13547,137460214,173.0,,0,0,/rarara108/making-dataset,HuBMAP - Hacking the Human Vasculature
13548,133693587,257.0,0.4392376868091586,0,0,/thanhhau097a/inference-detectron2,HuBMAP - Hacking the Human Vasculature
13549,138624126,247.0,,0,0,/huangzeyuzheng/hubmap-2023-yolov7-baseline,HuBMAP - Hacking the Human Vasculature
13550,137213129,713.0,,0,0,/redbeanjellyk/hubmap-2023-k-fold-cv-coco-dataset-generat-85cc2c,HuBMAP - Hacking the Human Vasculature
13551,131684286,504.0,6.3720242646684005e-06,0,1,/bibhabasumohapatra/infer-hubmap-hacking-vasculature,HuBMAP - Hacking the Human Vasculature
13552,135530721,850.0,,0,1,/truthisneverlinear/kidney-histology-slices-eda,HuBMAP - Hacking the Human Vasculature
13553,137146287,851.0,,0,0,/shyeark/yolov8-sam-training,HuBMAP - Hacking the Human Vasculature
13554,135898055,744.0,,0,3,/neilz0211/yolov7,HuBMAP - Hacking the Human Vasculature
13555,133135758,542.0,,1,62,/fnands/a-quick-yolov7-baseline,HuBMAP - Hacking the Human Vasculature
13556,134808875,318.0,,0,13,/finlay/hubmap-eda-coco-yolov7-train-and-validate,HuBMAP - Hacking the Human Vasculature
13557,134890725,540.0,,0,0,/wikiplusannangela/hubmap-data-files-eda,HuBMAP - Hacking the Human Vasculature
13558,135961028,482.0,,4,13,/dinowun/eda-simplified-hubmap-hacking-vascul-en-zh,HuBMAP - Hacking the Human Vasculature
13559,136424901,535.0,0.3316253731186557,0,0,/leehann/infer-mask-rcnn,HuBMAP - Hacking the Human Vasculature
13560,133278191,244.0,,6,9,/theo88/hubmap-vasculature-extended-eda-and-masks,HuBMAP - Hacking the Human Vasculature
13561,134320266,764.0,0.3328450641470998,0,0,/rawmatter/a-quick-yolov7-baseline-inference,HuBMAP - Hacking the Human Vasculature
13562,133888275,806.0,,0,1,/solerikaboman/utility-class-tile,HuBMAP - Hacking the Human Vasculature
13563,134860264,387.0,,24,79,/mersico/hubmap-eda-pycocotools-submission,HuBMAP - Hacking the Human Vasculature
13564,133393837,716.0,0.0,5,9,/dhruvkhatri/submission-smp-working-pycoco-smp,HuBMAP - Hacking the Human Vasculature
13565,132922144,449.0,,0,0,/robertsun2/unet-hubmap,HuBMAP - Hacking the Human Vasculature
13566,133317546,696.0,,0,2,/takafumitakizawa/hubmap-making-dataset-add-glomerulus-unsure-mask,HuBMAP - Hacking the Human Vasculature
13567,135464759,265.0,0.3144637129046659,0,1,/luoluozhang/mask2former,HuBMAP - Hacking the Human Vasculature
13568,134331539,841.0,,0,0,/purpleofdial/hubmap-data-processing,HuBMAP - Hacking the Human Vasculature
13569,133978704,884.0,0.1943900655084804,0,0,/lijingcheng/hubmap-inference,HuBMAP - Hacking the Human Vasculature
13570,139270292,283.0,,0,0,/helefeng/notebook35c3f5f2a8,HuBMAP - Hacking the Human Vasculature
13571,130837920,922.0,,1,9,/governor/quick-eda-trying-to-assemble-whole-slide-images,HuBMAP - Hacking the Human Vasculature
13572,131072356,897.0,0.0,0,9,/ermak9/sample-submission,HuBMAP - Hacking the Human Vasculature
13573,136432754,839.0,1.3980812732605771e-06,1,0,/rishengyang/hubmap-mmdet-2-26-public-inference,HuBMAP - Hacking the Human Vasculature
13574,135906417,935.0,,0,0,/manuelnkegoum/hubmap-train,HuBMAP - Hacking the Human Vasculature
13575,131791405,939.0,,0,15,/yusaku5739/stainnet-make-stain-normalized-image,HuBMAP - Hacking the Human Vasculature
13576,131033401,960.0,,1,22,/ezmgszi/data-import-and-binary-mask-generation,HuBMAP - Hacking the Human Vasculature
13577,131210743,963.0,,6,13,/zman950/sample-submission-with-segment-anything,HuBMAP - Hacking the Human Vasculature
13578,131286804,977.0,0.0,1,10,/jazivxt/whole-slide-images,HuBMAP - Hacking the Human Vasculature
13579,131041210,980.0,,0,4,/shinyatakaramoto/hubmap-eda,HuBMAP - Hacking the Human Vasculature
13580,136359156,991.0,,0,0,/kimalexanderh/ataset-0-1-shapehubmap-0612,HuBMAP - Hacking the Human Vasculature
13581,137618992,1000.0,,0,4,/vinitkp/hubmap-data-files-eda,HuBMAP - Hacking the Human Vasculature
13582,132415576,7.0,1.3672788259596886,3,13,/docxian/ps-s3-e16-crab-age-regression,Regression with a Crab Age Dataset
13583,132220570,87.0,,20,32,/xclimx/eda-xgboost-optuna,Regression with a Crab Age Dataset
13584,131735578,66.0,,3,19,/mattop/playground-series-s3-e16-eda-tsne,Regression with a Crab Age Dataset
13585,161910152,69.0,,0,3,/cozyhn/crab2,Regression with a Crab Age Dataset
13586,131585633,32.0,1.4588414309411537,2,8,/alekseyfomin/ensemble-baseline-for-finetuning,Regression with a Crab Age Dataset
13587,134382074,122.0,,1,3,/olegbalakin/crab-age-catboost,Regression with a Crab Age Dataset
13588,133039707,42.0,1.3487288564772613,1,12,/bhargav6031/lightgbm-gridsearchcv-and-feature-engineering,Regression with a Crab Age Dataset
13589,133490541,8.0,1.3366757824369493,0,0,/xiaohu2200/score-1-3360-on-private,Regression with a Crab Age Dataset
13590,131832005,51.0,,7,27,/priyanshu594/interactive-eda-submission,Regression with a Crab Age Dataset
13591,133249878,45.0,,4,20,/suraj520/detailed-analysis-towards-predicting-s-age,Regression with a Crab Age Dataset
13592,132609306,73.0,1.4217828062440006,2,12,/satyaprakashshukl/crab-age-dataset-eda-prediction,Regression with a Crab Age Dataset
13593,131691403,117.0,,11,32,/manavgupta92/crab-age-prediction-s-eda-baseline-cat-lgb,Regression with a Crab Age Dataset
13594,131536494,59.0,1.37479135694487,1,6,/e271828ai/ps-s3-e16-simplebaseline-en-jp-20230530,Regression with a Crab Age Dataset
13595,133339786,242.0,,0,3,/rafayqayyum/regression-crab-stacking-eda,Regression with a Crab Age Dataset
13596,132166260,95.0,,1,37,/pandeyg0811/mae-1-33-eda-ensemble,Regression with a Crab Age Dataset
13597,132207293,18.0,,0,5,/dhruvtiwari/easy-xgboost-model-to-learn-basics,Regression with a Crab Age Dataset
13598,132297714,244.0,1.337486073128735,7,26,/rzatemizel/flaml-ensemble-ladregression,Regression with a Crab Age Dataset
13599,135483259,103.0,,0,6,/yeoyunsianggeremie/s3e16-ensemble-private-score-1-33948,Regression with a Crab Age Dataset
13600,132017531,223.0,,0,7,/javigallego/outliers-statistical-analysis-fe-xgb-sweep,Regression with a Crab Age Dataset
13601,132987412,285.0,,0,5,/lovinggirls/lgbm-and-kfold-regression-with-crabs-dataset,Regression with a Crab Age Dataset
13602,131755297,12.0,,2,9,/tolgaik/ps-s3-e16-catboost-modeling-score-1-36173,Regression with a Crab Age Dataset
13603,131557402,90.0,1.3820980269431304,0,5,/harshavardhanbabu/crab-eda-baseline-catboost-winsoriser,Regression with a Crab Age Dataset
13604,133219990,183.0,,17,102,/tumpanjawat/ps3e16-eda-cluster-ensemble-xg-cat,Regression with a Crab Age Dataset
13605,133048817,314.0,1.3393092271852527,0,3,/bogdandoicin/feature-engineering-catboostregressor,Regression with a Crab Age Dataset
13606,132942341,172.0,,3,8,/candlemania/crap-age-regression-baseline,Regression with a Crab Age Dataset
13607,131545653,114.0,,2,7,/yus002/2023-05-30-eda-tps-crab-age-prediction,Regression with a Crab Age Dataset
13608,133163964,56.0,1.3507545832067254,0,2,/tdoh86/ps316-dnn-tf,Regression with a Crab Age Dataset
13609,133290634,240.0,1.3437560684606955,0,19,/klyushnik/ensemble-learning-regression,Regression with a Crab Age Dataset
13610,133235518,76.0,,6,13,/manishkumar7432698/crab-age-prediction,Regression with a Crab Age Dataset
13611,133291476,145.0,1.3396130861946722,2,8,/utisop/1-33961-mae-score-crab-age-prediction,Regression with a Crab Age Dataset
13612,133291476,145.0,1.3396130861946722,2,8,/utisop/1-33961-mae-score-crab-age-prediction,Regression with a Crab Age Dataset
13613,132889705,102.0,,0,49,/prthmgoyl/deeplearningmodel,Regression with a Crab Age Dataset
13614,132406734,287.0,,0,0,/ksakaida/clab-age,Regression with a Crab Age Dataset
13615,132026029,200.0,1.3626814384138262,1,9,/dongjun819/pgs316-eda-lgbm-ensemble,Regression with a Crab Age Dataset
13616,131676650,323.0,,0,3,/jakubrogulski/ps3e16-eda-model,Regression with a Crab Age Dataset
13617,133114742,94.0,,0,1,/grantgonnerman/ps-s3-e16-eda-and-modeling,Regression with a Crab Age Dataset
13618,132332374,229.0,1.3407272358958775,2,10,/jimmy1995taiwan/playground-crab-age-prediction-with-lgbmregressor,Regression with a Crab Age Dataset
13619,131561626,467.0,1.393683201746188,2,16,/samvelkoch/mr-eugene-harold-krabs-low-code-automl-ver-1,Regression with a Crab Age Dataset
13620,131779419,260.0,,0,5,/daraghthomas/pgs3e16c-eda-xgboost,Regression with a Crab Age Dataset
13621,131649347,132.0,,1,6,/helpming/simpleeda-lgbm-randomsearch,Regression with a Crab Age Dataset
13622,133471106,124.0,1.3427529626253418,0,3,/kkanar/lgbm-features-parameters-from-genetic-algorithm,Regression with a Crab Age Dataset
13623,132096917,298.0,,0,2,/paulbacher/crab-age-regression-model-selection,Regression with a Crab Age Dataset
13624,132694858,142.0,1.341942671933556,0,6,/donkaggle1/simple-optuna-catboost,Regression with a Crab Age Dataset
13625,132039086,70.0,1.3502481515243594,10,38,/sec98b4e/ps3e16-hgbm-kfold,Regression with a Crab Age Dataset
13626,133356586,294.0,1.351564873898511,0,0,/d3stron/crab-age-xgboost-lgbm,Regression with a Crab Age Dataset
13627,133051228,361.0,,0,10,/zhiweiyoung/ps3e16-crab-score-1-3535-xgboost,Regression with a Crab Age Dataset
13628,132868464,256.0,1.3435632533171276,24,57,/akioonodera/ps-3-16-lgbm-reg,Regression with a Crab Age Dataset
13629,147535785,57.0,,7,23,/joebeachcapital/crab-age-eda,Regression with a Crab Age Dataset
13630,132964628,280.0,1.3436645396536009,0,7,/tangelus/benchmarking-lgbm-modeling,Regression with a Crab Age Dataset
13631,132226755,118.0,,4,17,/psyflow/psyflow-crab-age-prediction-pg-s3-e16,Regression with a Crab Age Dataset
13632,132922189,16.0,,0,8,/abhijeetsinghmeena/ps3-e16-eda,Regression with a Crab Age Dataset
13633,132413035,138.0,1.369897700800162,0,7,/xgboostftw/crab-1-36-ensemble,Regression with a Crab Age Dataset
13634,132341069,289.0,,6,12,/chiejuwonsfx/crab-age-prediction-cjfx,Regression with a Crab Age Dataset
13635,132037498,316.0,,0,10,/iqbalsyahakbar/ps3e16-eda-and-ensemble-for-starters,Regression with a Crab Age Dataset
13636,131527231,211.0,1.420523809834903,0,9,/dhanrajmalla/basic-submission-xgboost,Regression with a Crab Age Dataset
13637,132090755,220.0,,2,5,/serifoz/simple-catboostregressor,Regression with a Crab Age Dataset
13638,133642043,321.0,,0,0,/athrunzala/optuna-with-xgbbaseline,Regression with a Crab Age Dataset
13639,132413332,214.0,,1,6,/riverallzero/basic-tabnetregressor,Regression with a Crab Age Dataset
13640,131657741,110.0,,0,7,/utsav1234/voting-regressor-the-best-performer,Regression with a Crab Age Dataset
13641,132207756,343.0,,0,4,/mousemice/flaml-basic-feature-engineering-0-345-lb,Regression with a Crab Age Dataset
13642,131992055,328.0,1.3494378608325737,2,4,/hermengardo/crab-age-prediction-eda-optuna-lgb,Regression with a Crab Age Dataset
13643,133406656,374.0,,11,36,/ahmetyldrr/predict-crab-age-catboost-score-1-3468,Regression with a Crab Age Dataset
13644,133087187,302.0,,0,7,/kishore3914/crab-age-prediction,Regression with a Crab Age Dataset
13645,132556954,406.0,,0,4,/bartkmie/simple-approach-to-crab,Regression with a Crab Age Dataset
13646,132242041,274.0,,9,18,/aesedeu/low-memory-lightgbm-p3-s3-e16-crab-challenge,Regression with a Crab Age Dataset
13647,131851494,337.0,1.3531854552820823,9,14,/whyoverfitting/lightgbm-with-gridsearchcv,Regression with a Crab Age Dataset
13648,131621320,226.0,,0,9,/mexwell/quick-eda-feature-engineering-lightgbm,Regression with a Crab Age Dataset
13649,131774454,334.0,1.3593639218069482,4,11,/jeremyhaakenson/crab-xgboost,Regression with a Crab Age Dataset
13650,133007966,322.0,,0,6,/pranay27sy/feature-engineering-regression-crabage-dataset,Regression with a Crab Age Dataset
13651,134679776,387.0,,1,6,/prathameshprege/ps-s3-e16-regression-with-a-crab-age-dataset,Regression with a Crab Age Dataset
13652,133568883,222.0,,0,3,/atefbouzid/regression-with-a-crab-age-dataset,Regression with a Crab Age Dataset
13653,131526977,338.0,,9,42,/mpwolke/average-lifespan-of-a-crab,Regression with a Crab Age Dataset
13654,132420626,372.0,1.3532867416185557,3,13,/tejasurya/lgbm-xgb-catboost-cv-age-predict-regression,Regression with a Crab Age Dataset
13655,132746652,620.0,1.3844829332523043,2,10,/nazimcherpanov/crabby-old-regression-pinching-insights,Regression with a Crab Age Dataset
13656,132017723,345.0,,0,6,/rayrishiraj/crab-regression-analysis,Regression with a Crab Age Dataset
13657,133486363,330.0,1.3470069887572167,0,3,/gabrielfacheti/crab-age-prediction-votingregressor,Regression with a Crab Age Dataset
13658,131732869,509.0,,0,8,/scirpus/crabby-mccrabface-i,Regression with a Crab Age Dataset
13659,133026548,357.0,1.3649346703129748,0,1,/themeeemul/age-crab-prediction,Regression with a Crab Age Dataset
13660,133368198,473.0,1.3887886623802423,0,3,/ngntnlong/pgs-ss3e16,Regression with a Crab Age Dataset
13661,132653170,393.0,1.3750633039602955,5,18,/matthewjansen/crab-age-prediction-kfold-ensemble,Regression with a Crab Age Dataset
13662,133115318,383.0,1.37708903068976,1,10,/songsyans/easy-mlr3-xgboost,Regression with a Crab Age Dataset
13663,138043845,355.0,,24,37,/anjusukumaran4/crab-age-dataset-eda-prediction-4-models,Regression with a Crab Age Dataset
13664,132748948,429.0,1.35784462675985,5,21,/i191796majid/feature-selection-crab,Regression with a Crab Age Dataset
13665,134017115,352.0,,2,6,/bedynoag/eda-modelling-hyperparameter-tuning-bayesian,Regression with a Crab Age Dataset
13666,137792853,465.0,,0,1,/rafaelsaraivacampos/regression-with-a-crab-age-dataset-solution,Regression with a Crab Age Dataset
13667,131619102,466.0,1.3589230964339816,2,20,/eliassolomatin/simple-catboost-baseline-with-synth-dataset,Regression with a Crab Age Dataset
13668,132725400,517.0,,0,3,/quantummo0se/ensemble-crab-age-prediction-s3e16,Regression with a Crab Age Dataset
13669,133708634,433.0,,2,17,/iqmansingh/crab-age-voting-regression-synthetic-data,Regression with a Crab Age Dataset
13670,133326186,394.0,,0,0,/jmviji/crab-age-competition-part-1,Regression with a Crab Age Dataset
13671,132846238,470.0,,1,11,/mesutssmn/crab-age-predicion-with-some-ml-models,Regression with a Crab Age Dataset
13672,131784089,422.0,1.375671021979135,2,6,/awesomeharris/ps3e16-regression-with-a-crab-age-dataset,Regression with a Crab Age Dataset
13673,133205616,516.0,1.3747760172879384,0,7,/imessam/catboost-lightgbm-xgboost-dnn-cnn,Regression with a Crab Age Dataset
13674,133282878,521.0,1.3693589443545835,0,0,/danilopaula/tps-s3e16,Regression with a Crab Age Dataset
13675,131625571,458.0,1.3654868310099126,1,15,/sujaykapadnis/ps-s3e16-eda-stacked-submission,Regression with a Crab Age Dataset
13676,131625571,458.0,1.3652129751924256,1,15,/sujaykapadnis/ps-s3e16-eda-stacked-submission,Regression with a Crab Age Dataset
13677,131597052,498.0,,0,3,/keitashimizu21/ja-en-regression-with-a-crab-age-dataset,Regression with a Crab Age Dataset
13678,132837133,514.0,1.4112225260812317,0,2,/syerramilli/ps3e16-basiceda-xgboost-optuna,Regression with a Crab Age Dataset
13679,132138383,500.0,,0,7,/charunumesh/ps-s3-e16,Regression with a Crab Age Dataset
13680,133446212,537.0,,0,3,/einonm/regression-with-a-crab-age-dataset-nn-mae-1-364,Regression with a Crab Age Dataset
13681,132904064,556.0,,12,24,/harshapondhugula/crab-age-s3ep16,Regression with a Crab Age Dataset
13682,132853641,545.0,,9,23,/panini92/crab-age-s3e16-eda-model-comparison,Regression with a Crab Age Dataset
13683,133337416,541.0,,1,11,/nikoolaylovyagin/eda-catboost-lgbm-from-pycaret-blended,Regression with a Crab Age Dataset
13684,132821669,523.0,1.3702625987831574,0,5,/kurosakishusuke/ps3e16-eda-optuna-lgbm,Regression with a Crab Age Dataset
13685,132821669,523.0,1.3702625987831574,0,5,/kurosakishusuke/ps3e16-eda-optuna-lgbm,Regression with a Crab Age Dataset
13686,133469960,624.0,,0,13,/francescoliveras/ps-s3-e16-eda-model-en-es,Regression with a Crab Age Dataset
13687,132243313,544.0,1.3725625013753735,0,5,/krbharat/ps3-e16-benchmark,Regression with a Crab Age Dataset
13688,131860668,590.0,1.3731355984490534,1,10,/vaidyaprasad84/impacts-of-removing-multi-collinearity,Regression with a Crab Age Dataset
13689,133357264,582.0,1.4082524355820358,7,22,/atuljo/eda-regression-lgbm-optimised-mae-1-367,Regression with a Crab Age Dataset
13690,133210479,609.0,,0,14,/lusfernandotorres/playground-series-season-03-episode-16,Regression with a Crab Age Dataset
13691,133241493,569.0,1.55607729677958,0,14,/cybersimar08/simple-lgbm-regressor-used,Regression with a Crab Age Dataset
13692,134383307,567.0,,0,9,/sanjanasatish68l/simple-xgboost-model-better-than-complex-models,Regression with a Crab Age Dataset
13693,133370870,604.0,,1,8,/shashankjat10/crab-age-prediction-nn,Regression with a Crab Age Dataset
13694,131579905,534.0,,2,8,/amarloni/pgs3e16,Regression with a Crab Age Dataset
13695,131628730,577.0,1.4276542796211844,1,7,,Regression with a Crab Age Dataset
13696,131958735,617.0,1.382918050400084,1,6,/yazhinisp/score-1-37-simple-xgboost-baseline,Regression with a Crab Age Dataset
13697,133331493,552.0,,4,11,/natalialimanska/crab-age-investigation,Regression with a Crab Age Dataset
13698,133333652,587.0,1.405164322717498,2,16,/yogesh239/ps3e16-regression-lgbm-rf-crab-age-predictions,Regression with a Crab Age Dataset
13699,133333652,587.0,1.4334032442364746,2,16,/yogesh239/ps3e16-regression-lgbm-rf-crab-age-predictions,Regression with a Crab Age Dataset
13700,132701362,614.0,1.3771644715993108,0,4,/aronpollner/crab-age-prediction-with-lr-rf-xgboost,Regression with a Crab Age Dataset
13701,133014757,563.0,1.3754684493061886,0,0,/joanmarcos/notebook34c83fadd6,Regression with a Crab Age Dataset
13702,132724627,633.0,1.4575103818494886,6,16,/kkhandekar/what-a-crab-age-regression,Regression with a Crab Age Dataset
13703,133431538,629.0,,0,5,/alessandrolobello/crab-competition-1-368-mae-score,Regression with a Crab Age Dataset
13704,132975805,595.0,1.376582599007394,2,10,/zonwie/s13e16-beginner-lightgbm-gridsearchcv,Regression with a Crab Age Dataset
13705,132978466,688.0,,0,4,/sparsh3649/notebook3c68e29f77,Regression with a Crab Age Dataset
13706,132310041,756.0,1.3776967487085992,0,4,/fredparrela/teste1,Regression with a Crab Age Dataset
13707,132852941,646.0,1.4433482039268122,0,13,/ifeanyichukwunwobodo/playground-s03e18-grid-search-baseline,Regression with a Crab Age Dataset
13708,132852941,646.0,1.3913469259109008,0,13,/ifeanyichukwunwobodo/playground-s03e18-grid-search-baseline,Regression with a Crab Age Dataset
13709,132852941,646.0,1.3827754186974603,0,13,/ifeanyichukwunwobodo/playground-s03e18-grid-search-baseline,Regression with a Crab Age Dataset
13710,132852941,646.0,1.3907673763921125,0,13,/ifeanyichukwunwobodo/playground-s03e18-grid-search-baseline,Regression with a Crab Age Dataset
13711,133272606,676.0,1.3810391978122152,2,9,/jaga360/regression-with-a-crab-age,Regression with a Crab Age Dataset
13712,131529490,678.0,1.381444343158108,8,17,/abocadobaby/simple-eda-lgbmregressor,Regression with a Crab Age Dataset
13713,131625545,718.0,1.385403569715384,0,8,/rfeng12/s3e16-easily-customizable-basic-nn,Regression with a Crab Age Dataset
13714,131843058,713.0,,3,8,/alexbostick/boost-xgboost-regression-age-preds,Regression with a Crab Age Dataset
13715,132514477,681.0,1.3836928130503792,2,14,/eslamfouad/regression-with-a-crab-age-dataset-ml,Regression with a Crab Age Dataset
13716,132459389,661.0,1.4108590737972206,1,8,/gauravduttakiit/pss3e16-flaml-rmse,Regression with a Crab Age Dataset
13717,132897514,854.0,,0,0,/subhendu/s03-e16-regression-with-a-crab-age-dataset-tf-mlp,Regression with a Crab Age Dataset
13718,133200153,704.0,,0,6,/ajaybabua/crab-age-lr-ridge-lasso,Regression with a Crab Age Dataset
13719,131969551,773.0,,1,6,/jimmyyeung/ps3-16-crab-age-eda-optuna-lgbm,Regression with a Crab Age Dataset
13720,133328428,751.0,,0,0,/ronfswanson/accuracyofvariousmodels-crabage,Regression with a Crab Age Dataset
13721,167005582,786.0,,2,15,/varunguttikonda/regression-with-crab-age-dataset,Regression with a Crab Age Dataset
13722,131743561,755.0,,0,5,/atharvbharaskar/crab-age-eda,Regression with a Crab Age Dataset
13723,133228738,1258.0,1.4974171984199331,0,2,/xirongcui/notebookd538a047fd,Regression with a Crab Age Dataset
13724,133275934,670.0,1.3872956103818526,2,12,/neupane9sujal/xgb-model,Regression with a Crab Age Dataset
13725,132212489,791.0,,0,2,/suranjandas1990/ps3e16-eda-i-sgd,Regression with a Crab Age Dataset
13726,132905540,744.0,1.3951179985819913,0,12,/ashx010/ps3e16-eda-feature-engineering-ml-model,Regression with a Crab Age Dataset
13727,132960193,766.0,1.3907626861136433,0,8,/dedywjakson/crab-age-prediction-with-regression-model,Regression with a Crab Age Dataset
13728,132757717,796.0,1.4071511641041223,0,8,/spike8086/crabageprediction-baseline-of-tensorflow-ae,Regression with a Crab Age Dataset
13729,131986993,685.0,1.388780971558796,1,6,/chaitanyakolliboyina/crab-age-regression,Regression with a Crab Age Dataset
13730,132178096,698.0,1.429771299625241,0,5,/haoranliang01/haoran-s-naive-predictions,Regression with a Crab Age Dataset
13731,132030360,699.0,1.3890203941760346,0,12,/shashanknecrothapa/crabage,Regression with a Crab Age Dataset
13732,132196219,783.0,,0,7,/starsiwach/crab-age-svm,Regression with a Crab Age Dataset
13733,133161473,722.0,,1,6,/coinshot/crab-age-reggression-model,Regression with a Crab Age Dataset
13734,133134566,827.0,,6,19,/akshayhedau/crab-age-xgbreg-hyperparam-randomizedsearchcv,Regression with a Crab Age Dataset
13735,132323898,762.0,,0,6,/soyabulislamlincoln/crab-age-cnn-lstm,Regression with a Crab Age Dataset
13736,132573060,769.0,,0,1,/ashutoshojha/playground-s3-e16-baseline-submission,Regression with a Crab Age Dataset
13737,133067530,757.0,1.4214459367265957,4,10,/barbagrande007/bbg007-crabs-s3e16,Regression with a Crab Age Dataset
13738,133750791,823.0,1.3608832168540463,0,0,/shenhsunliao/2023-6-8-practice,Regression with a Crab Age Dataset
13739,132349046,874.0,1.396046305783447,0,5,/gargivipat/crab-age-prediction-notebook,Regression with a Crab Age Dataset
13740,132858662,747.0,1.3967385799655627,0,5,/cyborg123/version-1-crab,Regression with a Crab Age Dataset
13741,133328291,857.0,1.3955628527700483,0,1,/ninadaithal/crab-age,Regression with a Crab Age Dataset
13742,133355173,883.0,,0,1,/nyagami/predicting-the-age-of-crabs-regression,Regression with a Crab Age Dataset
13743,133191174,978.0,1.401451045497817,4,21,/eesuck/crabage,Regression with a Crab Age Dataset
13744,133309120,859.0,1.4016522715182806,0,0,/arambarseghyan/summerproject-crabage,Regression with a Crab Age Dataset
13745,134247846,901.0,,0,5,/sawsanshakir/notebook-crab-age-dataset,Regression with a Crab Age Dataset
13746,131752202,879.0,1.4026093061476292,19,33,/phongnguyen1/a-framework-for-tabular-regression-e16-14-11,Regression with a Crab Age Dataset
13747,133312334,877.0,1.4115700602349897,0,2,/scodepy/crab-age-prediction-xgboost,Regression with a Crab Age Dataset
13748,131800707,904.0,,0,6,/newdatasc/crabby-patty-age-baseline-lgbm,Regression with a Crab Age Dataset
13749,132705105,896.0,,0,13,/averma111/stacking-crabage-s3e16,Regression with a Crab Age Dataset
13750,132712682,913.0,1.4046990251264635,3,10,/datascientistsohail/se03-ep16-regression,Regression with a Crab Age Dataset
13751,131829811,927.0,,0,5,/shamikrana/crab-age-prediction-kaggle-competition,Regression with a Crab Age Dataset
13752,133329526,899.0,,2,6,/aigetswild/playground-series-s3-e16-eda-modeling-and-sub,Regression with a Crab Age Dataset
13753,131753666,962.0,1.4065514154866852,5,18,/drmwnnrafi/ps3e16-crab-age-tabnet,Regression with a Crab Age Dataset
13754,133166991,974.0,,8,17,/chemaplana/the-accountant-crab-crab-crab-time,Regression with a Crab Age Dataset
13755,133300509,836.0,,0,4,/kiankii/regression-with-crab-age-dataset,Regression with a Crab Age Dataset
13756,131727193,937.0,1.4074698132433727,0,6,/stpeteishii/pss3-ep16-lgbm-with-optuna,Regression with a Crab Age Dataset
13757,132157471,961.0,,0,2,/satyasavith/crab-rave,Regression with a Crab Age Dataset
13758,133830358,1009.0,,0,5,/mohamedouchir/crab-age-pycaret,Regression with a Crab Age Dataset
13759,133306623,882.0,,0,0,/alanshmyga/regression-with-a-crab-age,Regression with a Crab Age Dataset
13760,132351911,972.0,1.412893750633056,2,8,/bendjedouattia/crab-age-with-tensorflow,Regression with a Crab Age Dataset
13761,132915285,976.0,,0,6,/muhammettarkylmaz/eda-data-visualization-and-model-hyper-param,Regression with a Crab Age Dataset
13762,132214764,908.0,1.4097378765442985,2,8,/bibekchalise/regression-with-crab-age-dataset,Regression with a Crab Age Dataset
13763,133275889,940.0,1.5141294439380129,1,5,/varunsampathkumar/crabageprediction-challengekaggle,Regression with a Crab Age Dataset
13764,135487687,977.0,,0,4,/glebmikh/ds65-catboost-ms,Regression with a Crab Age Dataset
13765,131523039,988.0,1.4113741171179934,2,9,/kaizen97/eda-base-submission,Regression with a Crab Age Dataset
13766,131571993,1003.0,1.4141562616282808,7,12,/aman7kumar/crab-age-ensembling-label-encoding,Regression with a Crab Age Dataset
13767,132532974,1044.0,1.4119630575919195,0,2,/marioshadjiantonis/playground-s3e16,Regression with a Crab Age Dataset
13768,133244595,1027.0,1.413546981778587,2,13,/amyrmahdy/crab-age,Regression with a Crab Age Dataset
13769,132804112,1015.0,,3,18,/sadikaljarif/regression-with-a-crab-age,Regression with a Crab Age Dataset
13770,132797255,1058.0,1.42366282411628,0,7,/stanislavchalyi/compet,Regression with a Crab Age Dataset
13771,132696909,1051.0,1.4254323447077932,1,9,/klaidenx/p-s3e16-eda-model,Regression with a Crab Age Dataset
13772,132777604,1100.0,,0,1,/yatinaggarwal033/crab-age,Regression with a Crab Age Dataset
13773,132074330,1073.0,,1,12,/phanendrasairam/crab-age-prediction-s3e16,Regression with a Crab Age Dataset
13774,133353758,1065.0,1.4286146701734024,0,18,/reymaster/ps-s3e16-votingregressor-synthetic-data,Regression with a Crab Age Dataset
13775,133045519,1087.0,3.738310037475983,0,8,/kolambekalpesh/crab-age-dataset,Regression with a Crab Age Dataset
13776,133328456,1116.0,,0,3,/debarghasen/competition-crab-age-dataset,Regression with a Crab Age Dataset
13777,132263121,1075.0,,0,4,/vineet30/regressionwithcrabagedataset,Regression with a Crab Age Dataset
13778,131642071,1083.0,1.443735440089132,0,3,/mohamedaminesahraoui/regression-with-a-crab-age-dataset,Regression with a Crab Age Dataset
13779,132633010,1133.0,,2,11,/kirtanmatalia26/crab-age-prediction-using-linear-regression,Regression with a Crab Age Dataset
13780,133083944,1169.0,1.4556872277929709,0,6,/chiranjeevisrinivas/crab-age-regression,Regression with a Crab Age Dataset
13781,131808739,1151.0,,2,13,/vstacknocopyright/crab-age-prediction-with-random-forest-extratree,Regression with a Crab Age Dataset
13782,132016924,1171.0,,0,6,/ranjithkacharya/crab-eda-predictions,Regression with a Crab Age Dataset
13783,132017558,1183.0,,0,2,/testanother/crab-regression-submission-simple,Regression with a Crab Age Dataset
13784,136245140,1194.0,,4,12,/krishnaraj30/crab-age-prediction-regression-random-forest,Regression with a Crab Age Dataset
13785,132277955,1219.0,1.481469133951181,0,0,/hemakarapu/regression-crab-age-dataset,Regression with a Crab Age Dataset
13786,132599284,1222.0,,0,9,/ashishjagdishsharma/crabagedataset,Regression with a Crab Age Dataset
13787,133230732,1238.0,1.485397882024455,0,6,/ajitjadhav1/crab-age-prediction-using-linear-regression,Regression with a Crab Age Dataset
13788,131727408,1246.0,,1,6,/vengadeshwaran58/crab-age-prediction,Regression with a Crab Age Dataset
13789,132559064,1243.0,1.485727051226497,0,2,/venkatsam30/notebook500bc8ff07,Regression with a Crab Age Dataset
13790,133348757,1247.0,1.486123631885096,0,3,/davidbranson/crab-age-predictions-playground-s03e16,Regression with a Crab Age Dataset
13791,131588002,1260.0,1.494257609480399,0,2,/usamayousaf50/ps3-e16-multiple-models-comparison,Regression with a Crab Age Dataset
13792,132481030,1261.0,1.5019797899777367,0,4,/szn619/kaggle-playground-challenge,Regression with a Crab Age Dataset
13793,132481030,1261.0,1.5019797899777367,0,4,/szn619/kaggle-playground-challenge,Regression with a Crab Age Dataset
13794,131775028,1276.0,,0,4,/dsadler/regression-prediction-for-crab-age-data,Regression with a Crab Age Dataset
13795,132761128,1275.0,1.5832353910369357,0,3,/shawnie/notebook4d01542dd6,Regression with a Crab Age Dataset
13796,132041677,1274.0,1.5097826585045422,0,4,/daaadaaa/s3e16-crab-age-competition,Regression with a Crab Age Dataset
13797,146980936,1290.0,,14,39,/meeratif/crabs-the-simplest-code,Regression with a Crab Age Dataset
13798,131961222,1304.0,1.5221310645193964,1,5,/pohzixiang/crab-age-regression-zx,Regression with a Crab Age Dataset
13799,132263223,1310.0,,1,13,/ivancanepa/neural-network-keras-predicti-n-crab-age,Regression with a Crab Age Dataset
13800,134997328,1305.0,1.6221006786184544,0,7,/milanbhor/crab-age-detection,Regression with a Crab Age Dataset
13801,135938588,1326.0,,0,4,/richarddev/crabs-age-predictions,Regression with a Crab Age Dataset
13802,133303396,1327.0,,0,1,/vadimsaburov/crab-age-eda-preprocessing-model-selection,Regression with a Crab Age Dataset
13803,132000921,1333.0,1.6566370742631438,0,4,/tracyporter/play-3-16-tf,Regression with a Crab Age Dataset
13804,133029121,1330.0,1.60235693304973,0,3,/tarifraihan/notebook0b4d07e2f0,Regression with a Crab Age Dataset
13805,132635467,1325.0,1.6031601336979642,2,8,/alokkr2001/regression-with-a-crab-age-dataset,Regression with a Crab Age Dataset
13806,133111553,1336.0,1.6127989455112146,0,3,/arshmodak/eda-data-prep-and-basic-ml-for-predicting-crabage,Regression with a Crab Age Dataset
13807,136797913,1356.0,,0,4,/chetanp7970/regression-crab-age-dataset,Regression with a Crab Age Dataset
13808,132829771,1383.0,,1,10,/snmahsa/regression-cost-data,Regression with a Crab Age Dataset
13809,133176978,1384.0,,0,2,/giofis/kc1-regressioncrabage,Regression with a Crab Age Dataset
13810,132905478,1398.0,3.010571290033601,26,30,/shatabdi5/crab-age-regression,Regression with a Crab Age Dataset
13811,132905478,1398.0,3.010571290033601,26,30,/shatabdi5/crab-age-regression,Regression with a Crab Age Dataset
13812,131796488,1401.0,3.140889294034235,2,9,/jocelyndumlao/crabs-exploring-original-synthetic-data,Regression with a Crab Age Dataset
13813,133250523,1412.0,3.795300313987643,0,0,/dibya069/crab-age-ensemble-pipeline-xgboost-win,Regression with a Crab Age Dataset
13814,133031321,1418.0,,3,15,/nileshthonte/crab-age-regression-eda-modelling,Regression with a Crab Age Dataset
13815,132379875,1419.0,,2,5,/minalijain/regression-crab-age-prediction,Regression with a Crab Age Dataset
13816,132567868,1427.0,,0,5,/ashioyajotham/crab-age-regression,Regression with a Crab Age Dataset
13817,134820723,4.0,,0,1,/wimgovers/s3e17-target-encoding,Binary Classification of Machine Failures
13818,134565581,209.0,,20,39,/mehrankazeminia/ps3e17-gaussiannb,Binary Classification of Machine Failures
13819,134877954,151.0,,2,9,/wordcards/pgs3-17-target-encoding-and-aggregation-features,Binary Classification of Machine Failures
13820,134306338,236.0,0.9665755259193124,12,20,/thiagolimasantos/ps3-e17-eda-autogluon-models-lb-0-97882-top-6,Binary Classification of Machine Failures
13821,153116155,141.0,,3,13,/siddhvr/ps3e17-catboost-lightgbm-top-subs-ensemble,Binary Classification of Machine Failures
13822,133756606,143.0,0.9771813467160394,7,24,/utisop/0-97718-catboost-machine-failure-prediction,Binary Classification of Machine Failures
13823,133756606,143.0,0.9771813467160394,7,24,/utisop/0-97718-catboost-machine-failure-prediction,Binary Classification of Machine Failures
13824,134523086,148.0,,5,11,/thiagomantuani/ps3e17-feature-selection-sfs-xgboost,Binary Classification of Machine Failures
13825,134733856,56.0,,0,8,/vijayjoshi17/failure-analysis-eda-gaussiannb,Binary Classification of Machine Failures
13826,133636896,64.0,0.9664942107543868,2,16,/dongjun819/pgs3-17-eda-ensemble,Binary Classification of Machine Failures
13827,134512541,43.0,0.9759085154609792,2,28,/oscarm524/ps-s3-ep17-eda-modeling-submission,Binary Classification of Machine Failures
13828,134921006,176.0,0.9781977862776096,0,13,/maverickss26/lb-0-97820-binary-classification-machine-failure,Binary Classification of Machine Failures
13829,134617319,180.0,,5,9,/brpuneet898/top-10-binary-classification-machine-failures,Binary Classification of Machine Failures
13830,133609225,177.0,,1,7,/asheshsaha/eda-fe-ensemble-optuna-tuning,Binary Classification of Machine Failures
13831,145415173,94.0,,9,42,/yaaangzhou/pg-s3-e17-eda-modeling,Binary Classification of Machine Failures
13832,141560909,86.0,,1,37,/eishkaran/lb-0-971-eda-lgbm,Binary Classification of Machine Failures
13833,134156897,191.0,,0,1,/ryokiti/bc-of-machine-failures,Binary Classification of Machine Failures
13834,133990931,147.0,,18,83,/tumpanjawat/s3e17-mf-eda-clustering-adaboost,Binary Classification of Machine Failures
13835,133369993,172.0,0.9630074081849108,0,11,/satyaprakashshukl/binary-classification-of-machine-failures-e-17,Binary Classification of Machine Failures
13836,134461009,193.0,,2,13,/devsubhash/machine-failure-eda-catboost,Binary Classification of Machine Failures
13837,133378441,110.0,,0,8,/awesomeharris/ps3e17-basic-eda,Binary Classification of Machine Failures
13838,133427950,59.0,,21,62,/manavgupta92/s3e17-eda-baseline-cat-xgb-lgb,Binary Classification of Machine Failures
13839,134141956,73.0,,9,19,/jimmyyeung/ps3-17-machine-failure-catboost-top-21,Binary Classification of Machine Failures
13840,134773079,276.0,,20,33,/aakashjoshi123/machine-failure,Binary Classification of Machine Failures
13841,134869913,279.0,,0,1,/leotom/playground-s3e17,Binary Classification of Machine Failures
13842,133968169,41.0,0.9719246946895596,6,17,/i191796majid/0-97192-machine-faliure-simple,Binary Classification of Machine Failures
13843,133508137,30.0,0.9615119974095312,0,4,/shivamqr786/simple-catboost-for-machine-failure-predictions,Binary Classification of Machine Failures
13844,133763550,78.0,,3,31,/pandeyg0811/data-oversampling-vs-model-advancement,Binary Classification of Machine Failures
13845,133511269,112.0,0.9628036016809836,4,12,/suraj520/pss3-e17-case-study-recommendations-prediction,Binary Classification of Machine Failures
13846,134282429,84.0,0.9775433236619456,5,18,/shashanknecrothapa/simple-submission-logistic-regression,Binary Classification of Machine Failures
13847,134647125,13.0,0.9592363136931626,0,6,/haruomiyoshikawa/s3e17-tabtransformer,Binary Classification of Machine Failures
13848,133502085,240.0,,3,9,/harshavardhanbabu/one-shot-eda-sweetviz-dataprofiling-autoviz,Binary Classification of Machine Failures
13849,135138342,295.0,,2,11,/eryaww/ps3-e17-machine-failures-eda-1,Binary Classification of Machine Failures
13850,134239330,109.0,,0,8,/danbraswell/identical-rows-except-for-machine-failure,Binary Classification of Machine Failures
13851,134245039,210.0,,2,12,/tolgaik/ps-s3-e17-catboost-pool-optuna-0-97675,Binary Classification of Machine Failures
13852,135000400,47.0,,1,6,/annafabris/repeatedkfold-catboost,Binary Classification of Machine Failures
13853,133664545,38.0,0.9741191669593252,2,7,/erokhinvitaly/0-97411-eda-new-fts-ensemble-baseline,Binary Classification of Machine Failures
13854,157401881,215.0,,3,16,/pythonafroz/eda-electrical-motor-fault-prediction,Binary Classification of Machine Failures
13855,134519397,79.0,,0,1,/manteemike/pgs-s3-e17-machine-failure-eda,Binary Classification of Machine Failures
13856,133708279,291.0,0.9748439505977184,0,8,/yongsukprasertsuk/machine-failures-catboost,Binary Classification of Machine Failures
13857,133463593,119.0,0.9688589885098768,1,11,/nivedithavudayagiri/s3e17-eda-simple-ensemble-baseline,Binary Classification of Machine Failures
13858,134502622,44.0,0.9756828243909816,2,10,/yashasvimisra/tps-june-23,Binary Classification of Machine Failures
13859,134032809,218.0,0.9755627185734002,0,8,/alenic/lb-0-9755-simple-lightgbm,Binary Classification of Machine Failures
13860,135233919,332.0,0.9743674686236516,4,10,/laparicio/machine-failure-votingclf,Binary Classification of Machine Failures
13861,134697370,260.0,0.9729153083888,3,11,/shenhsunliao/2023-6-16-machine,Binary Classification of Machine Failures
13862,134520576,15.0,0.9747279935130412,0,6,/jmviji/ps3e17-lgbm-xgb-catboost,Binary Classification of Machine Failures
13863,134173525,324.0,0.9654422995264844,0,13,/jimgruman/machine-failure-in-r-with-embeddings,Binary Classification of Machine Failures
13864,133772631,305.0,,1,15,/docxian/ps-s3-e17-machine-failure-eda-corr-glm,Binary Classification of Machine Failures
13865,134437483,309.0,0.9636207983448216,0,4,/sec98b4e/ps3e17-lgbm-cv,Binary Classification of Machine Failures
13866,133431016,352.0,,0,7,/takekawatomoki/eda-submit,Binary Classification of Machine Failures
13867,134671016,205.0,,0,3,/abhijeetsinghmeena/ps3-e17-machine-failure-notebook-1-0,Binary Classification of Machine Failures
13868,134704120,385.0,0.9742988070940845,2,6,/andredrodrigues/simple-eda-xgb,Binary Classification of Machine Failures
13869,133859806,368.0,0.9694936409259224,11,40,/reymaster/0-9738-eda-feature-engineering-ensemble-baseline,Binary Classification of Machine Failures
13870,134889065,287.0,0.9646200206648388,2,13,/cozyhn/autogluon-baseline-ps-s3-e17,Binary Classification of Machine Failures
13871,134860329,302.0,0.9727592123132732,39,72,/akioonodera/ps-3-17-lgbm-bin,Binary Classification of Machine Failures
13872,134066503,412.0,0.9719551878764068,0,4,/xirongcui/notebook4f177bcf35,Binary Classification of Machine Failures
13873,134032080,414.0,,0,6,/natalialimanska/machine-failure-eda-and-classification,Binary Classification of Machine Failures
13874,133603744,421.0,,0,6,/psyflow/psyflow-ps3e17-machine-failures-0-966,Binary Classification of Machine Failures
13875,136156807,354.0,,1,2,/sanprofnext/binary-machine-learning-ensemble-classifier,Binary Classification of Machine Failures
13876,134906589,359.0,0.970800388072476,0,6,/popovanastya/ps-s3e7-2023-brief-eda-and-gaussiannb-gb-xgb,Binary Classification of Machine Failures
13877,135011461,360.0,,2,8,/oostg0t/lgbm-dart-tabnet-catboost-fe-based-on-physics,Binary Classification of Machine Failures
13878,134076439,387.0,0.9702166613528312,0,4,/natsu18/ps-3-17-xgboost,Binary Classification of Machine Failures
13879,134960316,763.0,0.9667371190659376,0,1,/nicholashorsford/binary-classification-of-machine-failure-xgboost,Binary Classification of Machine Failures
13880,134759249,628.0,,0,5,/aigetswild/playground-series-s3-e17-machine-failure,Binary Classification of Machine Failures
13881,134591230,411.0,0.966548559155434,2,3,/rzatemizel/flaml-with-sklearn-pipeline,Binary Classification of Machine Failures
13882,134689170,408.0,0.9641322333936077,0,10,/creaperlost/catboost-optuna-simple-guide,Binary Classification of Machine Failures
13883,133676994,662.0,,0,2,/serifoz/s3e17-xgboost-and-catboost,Binary Classification of Machine Failures
13884,134609500,478.0,0.9692365232041744,0,7,/arnogils/playground-s03e17-daily-buildout-lgbm-first,Binary Classification of Machine Failures
13885,135054183,762.0,,2,4,/strategos2/playground-series-season-3-episode-17,Binary Classification of Machine Failures
13886,134863413,582.0,0.9674612803943952,2,29,/iqmansingh/machine-failures-xgb-lgbm-ensemble,Binary Classification of Machine Failures
13887,134888892,460.0,0.9442519201891656,5,16,/klyushnik/big-size,Binary Classification of Machine Failures
13888,133409157,458.0,,2,8,/mexwell/ps3e17-eda-for-getting-started,Binary Classification of Machine Failures
13889,133606798,439.0,0.9655265188044432,0,4,/vaidyaprasad84/eda-sampling-ft-binary-classification,Binary Classification of Machine Failures
13890,134164207,469.0,0.9664332243806928,0,7,/ashx010/binary-machine-failure-prediction-model,Binary Classification of Machine Failures
13891,134640389,470.0,0.9636211094997892,4,9,/kamranjameel11/kamran-jameel-project,Binary Classification of Machine Failures
13892,134935286,494.0,,0,3,/l0r1knl/sklearn-base-models-pss3e17,Binary Classification of Machine Failures
13893,133550518,477.0,,0,2,/xgboostftw/feature-eng-unsupervised-high-corr-features,Binary Classification of Machine Failures
13894,134773565,563.0,,6,17,/saugatkafley/binary-machine-failures-randomforest-kfold,Binary Classification of Machine Failures
13895,134394891,601.0,,0,11,/yoshifumimiya/s3e17-one-point-feature-engineering,Binary Classification of Machine Failures
13896,133380440,513.0,,2,5,/dhanrajmalla/basic-catboost,Binary Classification of Machine Failures
13897,135419206,540.0,,1,16,/utkarshx27/machine-failure-prediction,Binary Classification of Machine Failures
13898,135260019,522.0,,0,15,/ahana09/ps-s3e17-xgb-cat-lgbm,Binary Classification of Machine Failures
13899,134125261,547.0,,0,6,/chiranjeevisrinivas/playground-series-s3e17,Binary Classification of Machine Failures
13900,133961873,642.0,0.9551506415289408,2,12,/yourstrulyrshi/random-forest-xgboost,Binary Classification of Machine Failures
13901,134781600,542.0,0.9622576284307688,0,7,/neupane9sujal/xgboost-0-96,Binary Classification of Machine Failures
13902,134750624,612.0,0.9667367041926472,5,5,/jassersoualhia/machine-failure-simple-random-forest,Binary Classification of Machine Failures
13903,133514360,466.0,0.9666825632282452,0,5,/xiaohu2200/baseline-framework-with-xgb-lgb-cat,Binary Classification of Machine Failures
13904,147301547,510.0,,9,35,/joebeachcapital/machine-failures-eda-simple-models,Binary Classification of Machine Failures
13905,133476546,589.0,,0,2,/andrewnuk/ps-s3e17-20230613-kfolds,Binary Classification of Machine Failures
13906,134964840,436.0,0.9620635714491668,0,1,/ceyhunsahin/ludwig-ai-base-model,Binary Classification of Machine Failures
13907,134257680,644.0,0.9199627485272516,0,6,/ajaybabua/machine-failures-prediction-with-xgbclassifier,Binary Classification of Machine Failures
13908,134425657,550.0,0.9606522762334236,6,16,/cid007/ydata-profiling-eda-base-model,Binary Classification of Machine Failures
13909,134867662,687.0,0.9636429940658598,0,2,/thomasmeiner/machine-failures-automl-using-bluecast,Binary Classification of Machine Failures
13910,133896578,534.0,,0,2,/ehekatlact/ps3e17-eda-lgbm-japanese,Binary Classification of Machine Failures
13911,134874711,780.0,,0,3,/smruthiiii/machine-failure-classification,Binary Classification of Machine Failures
13912,134870212,832.0,0.9659413920948798,17,54,/yogesh239/lgbm-optuna-predict-machine-failure-probability,Binary Classification of Machine Failures
13913,134870212,832.0,0.9655984993203338,17,54,/yogesh239/lgbm-optuna-predict-machine-failure-probability,Binary Classification of Machine Failures
13914,133369029,372.0,,1,10,/gauravduttakiit/pss3e17-autoviz,Binary Classification of Machine Failures
13915,133878740,518.0,,0,2,/abhay06102003/notebook5548611aba,Binary Classification of Machine Failures
13916,134924805,463.0,0.963081877940544,2,17,/sujaykapadnis/ps-s3e17-eda-and-ensemble-stack,Binary Classification of Machine Failures
13917,134904068,426.0,0.9657293918434666,0,1,/ssarkar445/machinefailure-autoxgb,Binary Classification of Machine Failures
13918,134396886,698.0,0.963936205763876,12,35,/sanjanasatish68l/simple-xgboost-model-to-predict-probability,Binary Classification of Machine Failures
13919,134393822,590.0,0.965182588846671,0,16,/cybersimar08/binary-classification-of-tool-failure,Binary Classification of Machine Failures
13920,134265786,777.0,,3,14,/bhavkaur/machine-failure-baseline-eda,Binary Classification of Machine Failures
13921,134799360,711.0,0.9652591329687564,1,9,/denismunene/machine-failure-prediction-xgboost,Binary Classification of Machine Failures
13922,134911232,659.0,0.9554463424666996,0,4,/phvarma/eda-ensemble-learning,Binary Classification of Machine Failures
13923,134953028,511.0,0.9643642512812844,0,5,/johnycooly/machine-failure-proba,Binary Classification of Machine Failures
13924,134512740,647.0,,1,3,/ardong/machine-failures-eda-baseline-xgb-optuna,Binary Classification of Machine Failures
13925,134523471,615.0,0.9626039439099608,0,13,/keenanzhuo/failure-prob-eda-voting-classifier-walkthrough,Binary Classification of Machine Failures
13926,134837790,852.0,0.9642740163406144,0,3,/aiotsir/competition-binary-classification-of-machine-failu,Binary Classification of Machine Failures
13927,134837790,852.0,0.9642740163406144,0,3,/aiotsir/competition-binary-classification-of-machine-failu,Binary Classification of Machine Failures
13928,134837790,852.0,0.9642740163406144,0,3,/aiotsir/competition-binary-classification-of-machine-failu,Binary Classification of Machine Failures
13929,134797037,671.0,,0,1,/alihaiders/machine-failure-random-forest-baseline,Binary Classification of Machine Failures
13930,139262138,649.0,,0,13,/nikhil1e9/machine-anomaly-detection,Binary Classification of Machine Failures
13931,134093433,485.0,0.9626292511806775,0,1,/datascientistsohail/machine-failures-se03-ep17,Binary Classification of Machine Failures
13932,134138954,798.0,,0,4,/shivijaiswal/machine-failure,Binary Classification of Machine Failures
13933,134137813,663.0,,0,5,/kenjif/ps-3-17-auto-ml-model-comparison,Binary Classification of Machine Failures
13934,159416685,657.0,,0,4,/arpitppatel/advance-hyperparameter-tuning,Binary Classification of Machine Failures
13935,134388698,651.0,,0,1,/benfoglia/playground-3-17-machine-failure-classification,Binary Classification of Machine Failures
13936,134379479,801.0,0.9632486570032996,0,2,/adityabhadauria/binary-classification-using-catboost-0-96,Binary Classification of Machine Failures
13937,134045142,664.0,,0,9,/ahmetyldrr/machine-failures-lgbmclassifier,Binary Classification of Machine Failures
13938,134299806,689.0,,0,7,/jeremyhaakenson/fe-and-xgboost-for-predicting-machine-failure,Binary Classification of Machine Failures
13939,134990049,697.0,0.9562170733220088,1,5,/barbagrande007/bbg007-s3e17-machinefailure,Binary Classification of Machine Failures
13940,134941355,714.0,0.9629132319479816,0,4,/efecanxrd/predicting-machine-failure-xgboost,Binary Classification of Machine Failures
13941,134941355,714.0,0.9629132319479816,0,4,/efecanxrd/predicting-machine-failure-xgboost,Binary Classification of Machine Failures
13942,134678578,669.0,0.9628725743655188,5,12,/jaga360/machine-failure-random-forest-baseline,Binary Classification of Machine Failures
13943,134888540,755.0,0.9625536405234956,0,4,/kwkdhueda/rf-xgb-lgb,Binary Classification of Machine Failures
13944,135045332,858.0,,4,16,/miladziekanowska/machine-failure-eda-and-modeling,Binary Classification of Machine Failures
13945,134211485,746.0,0.962434053297527,0,5,/scodepy/binary-classification,Binary Classification of Machine Failures
13946,133443098,658.0,0.9609739067518346,0,8,/stpeteishii/pss3-ep17-lgbm-with-optuna,Binary Classification of Machine Failures
13947,134443697,715.0,,2,11,/siddharthkumarsah/s3e17-playground-solution-auc-0-96213,Binary Classification of Machine Failures
13948,134936359,921.0,0.9620088081748293,2,9,/arjunbasandrai/machine-failure-prediction-lgbm-optuna,Binary Classification of Machine Failures
13949,134929372,886.0,0.9480338013864652,0,2,/ahmadarrafimoreno/notebook-buongiorno-playground-series-s3e17,Binary Classification of Machine Failures
13950,133602837,635.0,,0,6,/nataliekalina/beginner-friendly-machine-failure-eda,Binary Classification of Machine Failures
13951,134094760,811.0,,0,1,/lewiskiwonlee/notebook0d533a2c61,Binary Classification of Machine Failures
13952,133608962,817.0,,0,2,/daraghthomas/broken-machines-eda-catboost-baseline-model,Binary Classification of Machine Failures
13953,134978973,847.0,,2,7,/pasindusandakan/binary-classification-of-machine-failures,Binary Classification of Machine Failures
13954,133769176,724.0,0.9138026061925232,0,3,/amarloni/pgs3e17,Binary Classification of Machine Failures
13955,135697970,939.0,0.9569814773596386,1,4,/ved1104/classification-of-machine-failures-with-smote,Binary Classification of Machine Failures
13956,134922922,857.0,0.9491639162296148,2,3,/muhammadbilalhaneef/machine-failure-prediction-feature-eng-ann,Binary Classification of Machine Failures
13957,134461111,770.0,0.9536796045593744,0,2,/babusarath05/machine-failure,Binary Classification of Machine Failures
13958,134461111,770.0,0.9536796045593744,0,2,/babusarath05/machine-failure,Binary Classification of Machine Failures
13959,139687118,788.0,,0,1,/arghya123r/binary-classification-machine-failure,Binary Classification of Machine Failures
13960,134491294,856.0,0.9568171875366256,0,12,/satishpb/machine-failure-classification,Binary Classification of Machine Failures
13961,134412968,797.0,,0,5,/brianhumecky2/binary-classification-of-machine-failure,Binary Classification of Machine Failures
13962,134763415,781.0,0.9597953554520262,3,6,/stautxie/machine-failure-prediction-baseline,Binary Classification of Machine Failures
13963,135416185,947.0,,2,12,/amyrmahdy/neural-network-classification-machine-failures,Binary Classification of Machine Failures
13964,134090172,966.0,0.958500743349218,0,7,/igabiegasiewicz/eda-randomforestclassifier-95,Binary Classification of Machine Failures
13965,142920438,887.0,,0,5,/daaadaaa/s3e17-machine-failures,Binary Classification of Machine Failures
13966,134551801,829.0,0.9525741746770056,0,6,/mirkosnguyn/binary-classification-vanilla-neural-network,Binary Classification of Machine Failures
13967,133932104,873.0,,3,12,/dekomorisanae09/autoencoding-machine-failures,Binary Classification of Machine Failures
13968,133646093,885.0,0.9554359706344387,0,4,/scirpus/failure-mcfailure,Binary Classification of Machine Failures
13969,133578153,892.0,,0,3,/priyash07/pca-random-forest,Binary Classification of Machine Failures
13970,133804630,983.0,0.9480259187939468,0,12,/kishore3914/machine-failure-predictor,Binary Classification of Machine Failures
13971,134224605,893.0,0.9364058365204244,1,9,/kolambekalpesh/binary-classification,Binary Classification of Machine Failures
13972,134473630,1436.0,,0,3,/muhammadfahad43828/muhammad-fahad-project,Binary Classification of Machine Failures
13973,134289500,1015.0,0.951132904866028,0,2,/taylordaugherty/machine-failure-competition-2023-6-19,Binary Classification of Machine Failures
13974,133438350,914.0,,0,7,/phanendrasairam/machine-failures-s3e17-0-94,Binary Classification of Machine Failures
13975,133617801,994.0,0.9471389196989928,2,9,/atuljo/a-simple-notebook-to-start-with,Binary Classification of Machine Failures
13976,133877828,925.0,0.9330524157138236,3,15,/lonewalker29/oversampling-neural-network-vs-random-forest,Binary Classification of Machine Failures
13977,134098927,1062.0,,0,1,/nataliaxdd/1-binary-classification-of-machine-failures,Binary Classification of Machine Failures
13978,134203960,1046.0,0.9396446485805422,0,1,/cyborg123/random-experiments,Binary Classification of Machine Failures
13979,134437326,1023.0,0.939508777577924,1,5,/angellapark/certification-study-mission31-participation,Binary Classification of Machine Failures
13980,134655983,1001.0,0.938943512719704,3,15,/ifeanyichukwunwobodo/predicting-machine-failure-flaml-tps03ep17,Binary Classification of Machine Failures
13981,134843170,1040.0,0.9385741717728926,1,6,/coinshot/machine-failure-model-ipynb,Binary Classification of Machine Failures
13982,134514514,1018.0,0.93801834528203,3,11,/charunumesh/ps-s3-e17-eda,Binary Classification of Machine Failures
13983,133366966,1066.0,0.9344325954327845,1,7,/christilee/ps3-ep17-machinefailures-v1,Binary Classification of Machine Failures
13984,134942885,1034.0,0.9319717745105583,1,4,/prakharprasad/machine-failures-94-accuracy-logreg,Binary Classification of Machine Failures
13985,133483067,1054.0,,1,8,/nolanmeyer/ps-s3e17-eda,Binary Classification of Machine Failures
13986,134766444,1126.0,,0,6,/kiankii/binary-classification-of-machine-failures,Binary Classification of Machine Failures
13987,134592807,1060.0,0.9309124992817506,0,5,/ngntnlong/ps-s3e17-eda-binary-classification-with-keras,Binary Classification of Machine Failures
13988,135295561,1083.0,,0,6,/kimdove/machine-failure-with-pycaret,Binary Classification of Machine Failures
13989,133678898,1086.0,0.9288753677073832,0,3,/gaaaaaaab/machine-failures-optuna-rf,Binary Classification of Machine Failures
13990,134007544,1117.0,,0,2,/danilsantiev/pipeline-with-custom-function,Binary Classification of Machine Failures
13991,134318261,1116.0,0.9179924115526448,0,2,/amitmalhotra03/decision-tree-logistic-xgb,Binary Classification of Machine Failures
13992,133458517,1087.0,0.9142749394336857,0,7,/tracyporter/play-3-17-rfc,Binary Classification of Machine Failures
13993,134773710,1157.0,0.9229269144691,0,8,/onepabs/playground-series-s3-e17,Binary Classification of Machine Failures
13994,135252131,1177.0,,0,6,/aleemaparakatta/machine-failure-detection-beginner,Binary Classification of Machine Failures
13995,135599200,1077.0,,0,2,/adschmidt/machine-failure,Binary Classification of Machine Failures
13996,134851210,1102.0,,2,5,/sawsanshakir/notebook-machine-fail,Binary Classification of Machine Failures
13997,141329025,1113.0,,8,10,/sagayaabinesh/binary-classification-of-machine-failure-dtc,Binary Classification of Machine Failures
13998,133455879,1085.0,,2,32,/mpwolke/when-will-my-machine-breakdown,Binary Classification of Machine Failures
13999,134444595,1202.0,,0,4,/debarghasen/binary-machine-failure-with-log-reg,Binary Classification of Machine Failures
14000,134599818,1231.0,0.9180761122389902,4,14,/stepantikhonov/catboost-machine-failures,Binary Classification of Machine Failures
14001,133434295,1254.0,0.9180761122389902,0,3,/akiyukikouyama/baseline-gradient-boosting-classfier,Binary Classification of Machine Failures
14002,134709440,1239.0,,0,2,/halilbrahimhatun/machine-failure,Binary Classification of Machine Failures
14003,133374807,1272.0,0.9180482120102084,0,10,/aman7kumar/machine-failure-prediction,Binary Classification of Machine Failures
14004,134917193,1228.0,0.9160778750356012,0,6,/maxagrafa/classification-of-machine-failures,Binary Classification of Machine Failures
14005,136673083,1076.0,,1,20,/dumanmesut/machine-failures-classification-lgbm-xgb,Binary Classification of Machine Failures
14006,134906932,1235.0,,0,6,/shuvojitdas/s3e17-eda-binary-classification,Binary Classification of Machine Failures
14007,133376410,1237.0,0.9161894759507287,0,7,/pohzixiang/machine-failure-classification-zx,Binary Classification of Machine Failures
14008,133598035,1217.0,0.9161615757219468,0,0,/oswaldomezaleon/xgb-b-of-robbed,Binary Classification of Machine Failures
14009,139541241,1223.0,0.9161615757219468,0,8,/eesuck/lgbmc-binary-classification,Binary Classification of Machine Failures
14010,156243309,1212.0,,0,9,/sjagkoo7/binary-classification-of-machine-failures-s3e17,Binary Classification of Machine Failures
14011,133471902,1181.0,,0,9,/kirtanmatalia26/machine-failure-prediction-using-randomforest,Binary Classification of Machine Failures
14012,133433773,1135.0,0.915644021292127,0,4,/akshayhedau/machine-failures-xgbc-hyperparamtunning,Binary Classification of Machine Failures
14013,133596947,1377.0,0.9143865403488132,0,1,/nkaria1/playground-s3e17-machine-failure,Binary Classification of Machine Failures
14014,133390145,1230.0,,0,4,/nnsssadithya/machine-failure-challange,Binary Classification of Machine Failures
14015,134462155,1366.0,,4,7,/anjusukumaran4/binary-classification-of-machine-failures,Binary Classification of Machine Failures
14016,142471143,1335.0,0.91419123874734,0,1,/hritwijkamble/machinefail-comp,Binary Classification of Machine Failures
14017,134048486,1338.0,0.9126115049756792,0,8,/kkhandekar/binary-classification-tensorflow-v-s-pytorch,Binary Classification of Machine Failures
14018,134267421,1372.0,0.9126115049756792,0,5,/ragaa5/binary-classifiction-machine-failures,Binary Classification of Machine Failures
14019,134267421,1372.0,0.9126115049756792,0,5,/ragaa5/binary-classifiction-machine-failures,Binary Classification of Machine Failures
14020,134408685,1343.0,0.9125836047468971,0,9,/marialusa/binary-classification-of-machine-failures-in-r,Binary Classification of Machine Failures
14021,134408685,1343.0,0.9126115049756792,0,9,/marialusa/binary-classification-of-machine-failures-in-r,Binary Classification of Machine Failures
14022,134812427,1375.0,,0,13,/patriciabrezeanu/svm-classification,Binary Classification of Machine Failures
14023,134615407,1369.0,0.9125836047468971,0,5,/shrishtivaish/machine-breakdowns,Binary Classification of Machine Failures
14024,134250875,1385.0,0.9125557045181152,0,1,/hemakarapu/binary-classification-machine-failures,Binary Classification of Machine Failures
14025,133877129,1166.0,,0,5,/shivam2111/machine-failure,Binary Classification of Machine Failures
14026,133602019,1276.0,0.9124999040605516,3,11,/panini92/machine-failures-eda-model-comparison,Binary Classification of Machine Failures
14027,133752043,1383.0,0.9107527689161996,2,11,/ashishjagdishsharma/predicting-machine-failure,Binary Classification of Machine Failures
14028,134621093,1395.0,0.9107527689161996,1,9,/piyushjoshi01/binary-classification-multiple-algorithm-and-eda,Binary Classification of Machine Failures
14029,134102827,1262.0,0.9103515864443472,0,9,/kagankoral/machine-failure-classification-model,Binary Classification of Machine Failures
14030,134746785,1422.0,,0,7,/ahmedali74/machine-failure,Binary Classification of Machine Failures
14031,134873057,1440.0,,6,14,/vstacknocopyright/predicting-machine-failures-with-random-forest-clf,Binary Classification of Machine Failures
14032,134500591,1445.0,0.7221300051091646,0,1,/hsuweiho/notebookd7e7d9cafe,Binary Classification of Machine Failures
14033,134732174,1467.0,,5,9,/debamritapaul/binary-classification-of-machine-failures,Binary Classification of Machine Failures
14034,134802700,1469.0,,0,2,/owais12345/binary-machine-failures-randomforest-kfold,Binary Classification of Machine Failures
14035,142342997,1472.0,,0,3,/mindoflogicalfire/machinefailure,Binary Classification of Machine Failures
14036,134811032,1474.0,,1,18,/akhiljethwa/machine-failures-ensemble-ann-model,Binary Classification of Machine Failures
14037,133526806,1481.0,0.5,7,15,/jocelyndumlao/machine-failure-prediction,Binary Classification of Machine Failures
14038,134601403,1485.0,,0,4,/sviatoslavmatviiuk/notebooke52862bbdb,Binary Classification of Machine Failures
14039,150614904,1488.0,,0,2,/abdelrahmanalimo/machines-failure,Binary Classification of Machine Failures
14040,134523172,1473.0,,0,3,/brahimmohamed/simple-ann,Binary Classification of Machine Failures
14041,135421231,11.0,,2,31,/onurkoc83/s3e18-cv-0-6864-public-score-0-6467,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14042,140015068,1.0,,1,12,/nihilisticneuralnet/1st-place-winning-solution,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14043,136280524,156.0,0.661177795064295,4,30,/mehrankazeminia/ps3e18-gaussiannb,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14044,136091318,128.0,,0,2,/markusdarkus/0-66-russia-forward,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14045,135047439,153.0,0.6328456947368329,0,6,/cozyhn/autogluon-eda-pandas-profiling-feature-importance,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14046,137184976,109.0,,1,0,/ashutossahoo/predicting-enzyme-classes-on-substrates,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14047,135686116,180.0,,0,3,/acchiko/comparison-of-distribution-for-playground-s3e18,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14048,135098145,85.0,,21,85,/waalbannyantudre/ps3-e18-eda-multioutputclassifier-xgb-baseline,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14049,135580326,167.0,,0,10,/awesomeharris/ps3e18-original-dataset-cleaning,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14050,135182744,190.0,,0,10,/sanjanasatish68l/easy-multioutputclassifier-for-enzymes,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14051,135343199,46.0,0.634613031504371,0,7,/leeheewon01/ps3e18-automl-multi-label-autogluon,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14052,135673138,125.0,,1,23,/anshtanwar/cat-gbc-lgbm-xgb,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14053,135103342,158.0,0.6331506308582717,0,8,/dongjun819/pgs3-18-eda-basic-ensemble,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14054,136182171,33.0,,1,10,/jbomitchell/random-forest-ec-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14055,135975389,209.0,,0,9,/meisa0/s3e18-target-encoding-lb-0-65947,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14056,136957624,212.0,,0,6,/aman1320/enzymes,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14057,135541618,30.0,0.639191724564208,4,21,/ramjasmaurya/binaryrelevance-multilabelclassifiy-lb-0-63919,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14058,135175618,37.0,0.614125652168181,0,11,/rm1000/simple-logistic-regression,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14059,136047363,48.0,0.6357701416223251,2,7,/maverickss26/lb-0-6581-enzyme-substrate-dataset,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14060,135345050,71.0,,6,14,/mridul2003/multi-label-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14061,135320284,90.0,0.6321423460881195,0,1,/yapwh1208/playground-s3e18-xgb,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14062,135162825,7.0,0.6544632236628609,4,24,/l0glikelihood/pyboost-baseline,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14063,135318972,12.0,0.6544771454591356,0,9,/utisop/0-66088-ensemble-automl-enzyme-classify,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14064,135437258,19.0,0.5,0,6,/ajay308/multi-label-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14065,135127124,25.0,0.642042161157206,6,11,/swapnilchowdhury/ps3e18-eda-gridsearchcv-lightgbmc-0-64204,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14066,136369108,100.0,0.6504581154866553,4,14,/jeremiaaron/ps-s3e18-catboost-xgb-lgbm-soft-voting,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14067,135069555,35.0,0.6324934242772463,8,37,/nivedithavudayagiri/enzyme-eda-ensemble-multilabel-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14068,135171143,219.0,0.6463528314340887,0,4,/jmviji/ps3e18-lgbm-classifier-chain,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14069,135477914,228.0,,1,13,/utkarshx27/multi-label-classification-score-0-642,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14070,135126075,217.0,,0,4,/harshavardhanbabu/eda-baseline-rf-catboost-feature-elimination,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14071,135247350,171.0,0.6318915068475334,1,9,/syerramilli/ps3e18-multi-label-feed-forward-nn,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14072,135042471,278.0,0.635161602313293,0,6,/evancallaghan/neural-networks-mlc-using-tensorflow,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14073,136231529,286.0,0.6470469913420538,23,61,/akioonodera/ps-3-18-lgbm-bin,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14074,135478480,320.0,,0,9,/gauravduttakiit/pss3e18-lazypredict,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14075,135527325,295.0,,2,14,/docxian/ps-s3-e18-correlation-of-targets,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14076,135581652,196.0,,0,7,/pasqualemar/s3ep18-eda-baseline-ensembling,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14077,136027057,281.0,0.6460177957697857,0,6,/denismunene/multilabel-classification-using-ensemble-learning,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14078,136318115,498.0,0.6348696122988623,0,8,/khushiipatni/enzyme-multi-label-classification-dt-tfdf,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14079,136030794,238.0,0.6436618911213675,0,2,/shenhsunliao/enzyme,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14080,150554287,339.0,,0,13,/nikhil1e9/enzyme-substrate-multi-label,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14081,135353145,243.0,0.6454056877954858,0,15,/suraj520/pss3e18-stacking-classifier-optuna-submission,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14082,135662826,391.0,0.6100274661326353,15,37,/yogesh239/multi-label-classification-adab-catb-gb-rfc,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14083,135662826,391.0,0.6270097900585778,15,37,/yogesh239/multi-label-classification-adab-catb-gb-rfc,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14084,135662826,391.0,0.6294866902718066,15,37,/yogesh239/multi-label-classification-adab-catb-gb-rfc,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14085,135662826,391.0,0.6100682896369249,15,37,/yogesh239/multi-label-classification-adab-catb-gb-rfc,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14086,135662826,391.0,0.6294458667675169,15,37,/yogesh239/multi-label-classification-adab-catb-gb-rfc,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14087,135905257,261.0,0.6371062674499461,0,2,/nicobarea/xgb-lgbm-mars-with-tidymodels,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14088,136435215,356.0,,1,8,/yashoza12/auto-sklearn-multilabel-classification-enzyme,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14089,135998442,400.0,,3,11,/loki4514/enzyme-substrate-generic-algorithms,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14090,135318731,462.0,0.6433774779084479,0,4,/georgedoukas/play-18-23-one-vs-rest-manualy-tuned-classifiers,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14091,135616731,224.0,,2,16,/aakashjoshi123/enzyme-substrate,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14092,136182791,480.0,0.6432894477205904,18,60,/cybersimar08/enzyme-gradient-xgb-ada-cat-lgbm-ensemble,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14093,136294951,481.0,,0,5,/ashx010/ps3e18-catboost-model-0-64-score,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14094,136342587,428.0,0.6229645070905683,0,4,/benidictusgalihmp/ps3e18-xgboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14095,136342587,428.0,0.6229645070905683,0,4,/benidictusgalihmp/ps3e18-xgboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14096,135395388,293.0,,1,8,/thiagolimasantos/ps-s3-e18-eda-essemble-flaml-aws-autogluon,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14097,135905920,556.0,,0,8,/omkarkhade7/multi-label-classification-using-ann,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14098,135100246,337.0,0.6416250188914161,0,14,/jeremyhaakenson/enzyme-pca-and-xgboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14099,135058466,276.0,,1,5,/thomasmeiner/enzyme-classification-bluecast-automl-baseline,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14100,135954619,504.0,0.6380835746367799,2,8,/ceyhunsahin/ludwig-base-model,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14101,135489171,287.0,,0,0,/leotom/playground-s3e18-4,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14102,135144146,237.0,0.6417932183690855,1,11,/jimmyyeung/ps3-18-enzyme-eda-easy-ensemble,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14103,134978037,297.0,0.641489444190714,4,11,/killershoaib/pse18-multilabel-baseline-xgboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14104,135596419,507.0,,0,4,/sharifulprince/overfit-champion-741a40,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14105,135172759,422.0,0.6387023256741677,0,3,/markus427/proteinprediction,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14106,135687485,406.0,0.6398147586552765,0,0,/lukabarbakadze/multilabel-classification-challange,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14107,135660127,395.0,,6,29,/iqbalsyahakbar/ps3e18-eda-and-modelling-for-starters,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14108,135097454,355.0,0.6317683531089249,0,3,/saugatkafley/pss3e18-sweetviz-skewness-removal,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14109,135862896,508.0,,4,8,/sinanozdemir/enzyme-substrate-prediction-xgboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14110,135551980,442.0,0.4905121546749311,3,13,/atuljo/eda-ensemble-cb-xgb-lgbm-0-64,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14111,135154109,432.0,0.6384416799519373,0,6,/stpeteishii/pss3-ep18-viualize-importance-and-predict,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14112,138184800,354.0,,0,1,/ikonuhov/score-0-63-rus-xgb-lgbm-multi-class-predict,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14113,135163446,386.0,0.6068976504757402,0,9,/averma111/pss3e18-widedeep-eda,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14114,135505713,457.0,0.6209313494024411,0,10,/adityarawat0701/xgboost-multilabel-classification-bayesian-opt,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14115,136325534,567.0,,0,5,/sarahserafini/s3e18-with-tensorflow-neural-network,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14116,135771013,563.0,0.6375920041157526,3,13,/arnavsmayan/playground-series-s3-e18-gradient-boost-xgb,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14117,135800586,560.0,,1,3,/shivaninlp/ps3e18-multilabel-classification-nn,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14118,135531849,601.0,0.6298060347303878,0,2,/vaibhavprajapati22/gradient-boosting,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14119,136472867,490.0,,0,0,/strategos2/playground-series-season-3-episode-18,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14120,135179756,434.0,0.6371770679298787,0,7,/nataliekalina/eda-simple-model-selection,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14121,135030821,385.0,,0,13,/yoshifumimiya/s3e18-default-check,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14122,135520396,514.0,,1,6,/transhumanistx/ensemble-nns-gbc-ec,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14123,134987136,413.0,,1,4,/aaryansingh729/enzyme-substrate-eda,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14124,135503375,680.0,0.6337061454685708,0,8,/lonewalker29/neural-network-pytorch-s3e18-enzyme-subs,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14125,135004549,598.0,0.6205436976646034,0,3,/michael0621/explore-multi,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14126,135498886,540.0,0.6351442768863085,0,8,/christph/ps3e18-r-tidymodels-starter,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14127,135011089,487.0,0.6347850687083234,3,14,/iqmansingh/enzyme-classification-baseline,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14128,135136448,569.0,0.6121458613561568,0,6,/arjunbasandrai/lgbm-catboost-xgboost-weighted-ensemble-optuna,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14129,135408232,489.0,0.6337908465581713,0,11,/ashishjagdishsharma/explore-multi-label-classification-with-an-enzyme,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14130,135779628,518.0,0.6036352282064379,0,2,/achoum666/with-tf-decision-forests,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14131,135932310,519.0,,11,40,/gusthema/multi-label-with-tf-decision-forests,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14132,136328607,524.0,0.5149896485296116,1,7,/ridamahmood005/multi-label-classification-baseline-ova,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14133,136135627,526.0,0.6337433034306812,0,3,/warriorwizard/with-tf-decision-forests,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14134,135090336,648.0,,0,9,/san2deep/beginner-code-random-forest,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14135,134972545,424.0,0.5312403944396387,0,8,/reymaster/ps3-18-xgboost-w-aux-vars,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14136,135421864,497.0,0.6190897432640816,1,5,/maximeperez/enzymeboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14137,136038381,472.0,0.631702458317952,0,1,/smruthiiii/model-comparison-predictions-enzyme,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14138,135164817,600.0,,8,15,/darkmatter2222/s3e18-tensorflow-peer-review-please,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14139,135513217,647.0,0.6317810307366815,0,8,/damerajee/multi-classification-xgboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14140,147642092,547.0,,0,13,/joebeachcapital/pss3e18-eda-models-ensemble-submission,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14141,135428713,585.0,,0,1,/mohamedtahaouf/enzyme-substrate-dataset,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14142,135064602,509.0,0.630756631676178,0,4,/tracyporter/play-3-18-tf,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14143,135566463,637.0,0.628044189192317,0,5,/barbagrande007/bbg007-s3e18-enzymes,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14144,135471791,584.0,0.6262765045830163,1,13,/akiyukikouyama/ps-s3e18-eda-with-original-data-and-build-model,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14145,135510634,671.0,,0,7,/deshram/multi-label-classification-pss3e18,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14146,135873223,676.0,,0,1,/raufie/enzyme-substrate-playground-torch-63,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14147,135750224,688.0,0.6277244664349844,3,9,/yasinnaal/enzyme-substrate-playground-simple,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14148,135573673,587.0,0.6266575959008573,0,3,/chiranjeevisrinivas/playground-series-s3e18,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14149,138818096,565.0,,0,1,/keerthi4701/enzyme-multi-class-simple-model,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14150,136540947,545.0,,0,0,/madhava20217/xgboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14151,135097849,614.0,,0,3,/manteemike/pgs-s3e18-enzyme-substrate-eda,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14152,135355863,685.0,,0,3,/priyanshu594/enzyme-substrate-eda-submission,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14153,135267498,713.0,0.6027029374335142,0,8,/satishpb/multilabel-enzyme-substrate-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14154,135248170,708.0,,0,4,/yashkalkani/explore-multi-label-classification-with-an-enzyme,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14155,135129967,684.0,0.5977092147201222,0,5,/kishore3914/enzyme-substrate-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14156,135564296,769.0,,0,1,/ritzig/multi-label-using-imblearn-stacking,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14157,136542378,781.0,0.5858333884248632,0,0,/anzarwani2/linear-regression-bagging-only-ml-modelling,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14158,135450371,783.0,,0,6,/onepabs/ps3e18-eda-ensemble-adasyn,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14159,136110218,786.0,,0,1,/sherafzal/notebook6379e3af67,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14160,135284574,810.0,,6,13,/onurtuncaybal/xgboost-svm-and-random-forests-with-pca-in-r,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14161,136322816,822.0,0.5736810345959751,1,0,/suranjandas1990/ps3e18-eda,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14162,135950414,832.0,,0,5,/karansingla05/enzyme-substrate-pca-ensemble-1,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14163,136312484,835.0,0.5641980651097085,0,4,/suvammistry/ps-s3e18-adaboostclassifier-nearestcentroid,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14164,136270583,850.0,,0,15,/shlezinger/enzyme-substrate,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14165,136213223,859.0,0.5609069601619265,0,5,/piyushjoshi01/s3e18-multi-label-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14166,136241514,934.0,,0,4,/lwissitoon/explore-multi-label-classification-neuron,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14167,136668277,880.0,,3,10,/ahana09/ps-s3e18-tried-pycaret-first-time,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14168,135315675,873.0,0.5583367367321417,0,10,/amarloni/pgs3-e18-multiabel-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14169,135341699,868.0,0.5542967159172558,0,6,/aman7kumar/multi-class,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14170,136332851,903.0,0.5569607786041444,0,13,/dumanmesut/enzyme-multi-label-classification,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14171,135155846,882.0,0.5556238802084226,4,9,/stepantikhonov/catboost-enzyme-substrate,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14172,135482404,932.0,0.5200230375363779,0,7,/shubhamgupta012/season-3-episode-18,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14173,135363723,886.0,0.5552667459156513,0,4,/shreyanshsinghks/eda-rf-easy-explaination-all-models,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14174,135621089,973.0,,0,2,/ragaa5/notebook1e3ddf7892,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14175,135931543,983.0,,0,4,/phanendrasairam/enzyme-substrate-s3e18,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14176,135189647,972.0,0.528240685334865,0,5,/daaadaaa/s3e18-enzyme,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14177,136165180,1002.0,0.51901750082957,0,5,/arvindh22/enzyme-substrate-multioutput-classifier-models,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14178,135570285,993.0,,0,12,/vstacknocopyright/predicting-ec-classes-of-substrates-with-ensemble,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14179,135536789,996.0,0.4784550802442309,0,9,/ibrahimallabbad/eda-multi-classification-gradientboost-catboost,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14180,135816280,1006.0,,2,9,/shivijaiswal/explore-multi-class-label,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14181,135238843,1014.0,,0,4,/themayurbhat/nn-multi-label-classification-for-enzyme-substrate,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14182,135528186,1019.0,,0,1,/alekyaarra/multi-label-ensemble-deep-learning,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14183,136342737,1044.0,0.4326005575439458,0,4,/muhannadmansour/eda-classification-with-an-enzyme-substrate,Explore Multi-Label Classification with an Enzyme Substrate Dataset
14184,136933357,27.0,,1,12,/johnsmith44/eda-holidays-and-weekends,Forecasting Mini-Course Sales
14185,136374289,1151.0,,1,9,/oskarseweryn/s3e19-time-series-forecasting-eda,Forecasting Mini-Course Sales
14186,147642010,1153.0,,2,14,/joebeachcapital/psse19-eda-feature-engineering,Forecasting Mini-Course Sales
14187,136747097,100.0,37.82089436927557,4,9,/stepantikhonov/catboost-mini-course-sales,Forecasting Mini-Course Sales
14188,137081405,268.0,66.26950437581871,2,7,/awesomeharris/ps3e19-eda-baseline-models,Forecasting Mini-Course Sales
14189,136600000,205.0,35.58485373987057,0,9,/kriangkraitan/automl-time-series-forcasting-num-sold,Forecasting Mini-Course Sales
14190,136768792,447.0,,0,4,/cozyhn/s3e19-autogluon-timeseries-baseline,Forecasting Mini-Course Sales
14191,137049034,452.0,,37,131,/tumpanjawat/s3e19-course-eda-fe-lightgbm,Forecasting Mini-Course Sales
14192,137032562,34.0,,0,6,/christph/r-tidymodels-xgb,Forecasting Mini-Course Sales
14193,137874440,85.0,20.32005164250992,14,32,/chingiznurzhanov/timeseriessplit-catboost-trick,Forecasting Mini-Course Sales
14194,136383362,16.0,,9,32,/vipin20/arima-sarimax-exponential-smoothing-using-optuna,Forecasting Mini-Course Sales
14195,136475876,9.0,,1,11,/onurkoc83/catboost-with-trick,Forecasting Mini-Course Sales
14196,140117649,4.0,,4,33,/michaelbryantds/4th-place-solution-pygam-lb-5-47,Forecasting Mini-Course Sales
14197,162410627,32.0,,0,9,/kkamal2003/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14198,137618733,33.0,10.683586914187057,0,7,/fadhilumar/baseline-forecasting-method,Forecasting Mini-Course Sales
14199,143715830,25.0,,0,0,/dannyquirouette/using-prophet-on-multiple-time-series,Forecasting Mini-Course Sales
14200,137426687,79.0,,20,112,/iqbalsyahakbar/ps3e19-time-series-for-beginners,Forecasting Mini-Course Sales
14201,138560426,28.0,,8,27,/alpayabbaszade/time-series-catboost-forecast-stratified-cv,Forecasting Mini-Course Sales
14202,138134193,78.0,56.192589170781694,0,3,/szulky/a-dnn-model-in-forecasting-mini-course-sales,Forecasting Mini-Course Sales
14203,148729021,46.0,,0,0,/skuldropr/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14204,140401879,95.0,,0,19,/nikhil1e9/ps-s3e19-eda-ensemble-postprocessing,Forecasting Mini-Course Sales
14205,137452347,116.0,,0,6,/omkarkhade7/forecasting-minicourse-sales-with-different-algos,Forecasting Mini-Course Sales
14206,138270144,73.0,,0,5,/indropal/ps-s3-e19-observe-time-series-plots-for-dataset,Forecasting Mini-Course Sales
14207,136796323,89.0,,0,4,/johnycooly/sales-eda,Forecasting Mini-Course Sales
14208,137811147,69.0,,4,12,/markusdarkus/eda-analysis,Forecasting Mini-Course Sales
14209,138892642,119.0,,2,5,/lastdance9/using-75-prophets-rank-119,Forecasting Mini-Course Sales
14210,138161081,146.0,6.6674406396295085,0,7,/ikonuhov/score-6-6-rus-xgb-catboost-forecastings-sale,Forecasting Mini-Course Sales
14211,137770469,163.0,38.21684089421031,0,1,/vivinkurama/quick-prediction-random-forest,Forecasting Mini-Course Sales
14212,138422046,137.0,,0,0,/danieleduardocantu/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14213,138567448,155.0,,0,0,/strategos2/s3ep19-playground-eda-and-simple-modelling,Forecasting Mini-Course Sales
14214,138598288,150.0,,6,11,/ahana09/ps-s3e19-pycaret,Forecasting Mini-Course Sales
14215,161988847,145.0,,6,7,/sasakitetsuya/study-on-smape,Forecasting Mini-Course Sales
14216,137624228,157.0,7.319160134962489,0,6,/hudasaleh1/forecasting-sales-of-courses,Forecasting Mini-Course Sales
14217,137928255,159.0,,0,1,/valentinbelyaev/forecasting-mini-course-sales-machine-learning-3,Forecasting Mini-Course Sales
14218,138500631,141.0,7.395247887839824,3,11,/arnogils/playground-s03e19-basic-buildout,Forecasting Mini-Course Sales
14219,138815070,171.0,,13,28,/aaachen/ps3e19-simple-eda-randomforest,Forecasting Mini-Course Sales
14220,136487321,192.0,,0,9,/akiyukikouyama/ps3e19-eda-for-train-dataset,Forecasting Mini-Course Sales
14221,137228577,194.0,41.76144684364204,0,12,/utkarshx27/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14222,138416022,176.0,49.67956151167243,0,2,/archietram/fastai-chapter-9-tabular,Forecasting Mini-Course Sales
14223,138416022,176.0,53.667575997161975,0,2,/archietram/fastai-chapter-9-tabular,Forecasting Mini-Course Sales
14224,138416022,176.0,50.772061756210064,0,2,/archietram/fastai-chapter-9-tabular,Forecasting Mini-Course Sales
14225,137896948,161.0,,0,2,/abhilash21/forecasting-mini-course-sales-using-deepar,Forecasting Mini-Course Sales
14226,138484913,165.0,8.473871104528737,39,81,/kacperrabczewski/last-minute-forecasting,Forecasting Mini-Course Sales
14227,138484898,213.0,,4,11,/usamimeri/forecasting-from-bottom-to-up-eda-randomforest,Forecasting Mini-Course Sales
14228,137134455,221.0,,0,5,/radhakrishnanb/quick-and-easy-forecast,Forecasting Mini-Course Sales
14229,138360622,224.0,,4,17,/tesnimglen/ps3e19-eda-fbprophet-for-sales-forecasting,Forecasting Mini-Course Sales
14230,138375624,229.0,11.968151333270672,5,18,/jankratschmann/sales-forecasting,Forecasting Mini-Course Sales
14231,136388576,230.0,,0,7,/edwardhuangtw/p3se19-auto-ml-pycaret,Forecasting Mini-Course Sales
14232,137776662,235.0,15.332747972216538,4,15,/deepanadak/who-s-sold-more,Forecasting Mini-Course Sales
14233,137584904,251.0,15.406217525319526,2,10,/abhishek123maurya/fourier-features-and-time-series,Forecasting Mini-Course Sales
14234,137862318,250.0,48.1534001227726,1,8,/syerramilli/ps3e19-lightgbm-forecasting-with-time-features,Forecasting Mini-Course Sales
14235,138512684,252.0,17.632008396662663,0,9,/thierryneusius/2023s3e19-timeseries-prophet,Forecasting Mini-Course Sales
14236,138073898,254.0,19.77379966900497,4,24,/sachinpatil1280/sales-forcasting,Forecasting Mini-Course Sales
14237,137782920,255.0,,0,1,/kukazucker/fmcs-notebook,Forecasting Mini-Course Sales
14238,136815746,264.0,39.111564872017176,1,8,/jeremyhaakenson/time-series-fe-and-neural-network,Forecasting Mini-Course Sales
14239,138897748,269.0,,2,11,/mohamedtahaouf/forecasting-course-sales-fold-cbr-timeseriessplit,Forecasting Mini-Course Sales
14240,136645068,275.0,,5,28,/shivanimalhotra91/dart-covid-data-smoothing,Forecasting Mini-Course Sales
14241,138241794,278.0,,5,34,/magantiit/ps3e19-eda-forecasting-mini-course-sales-rf,Forecasting Mini-Course Sales
14242,137055393,286.0,32.751667798646814,0,3,/act18l/stacked-model-extratrees-adaboost,Forecasting Mini-Course Sales
14243,136806393,283.0,,0,5,/kiradit/eda-and-simple-modeling,Forecasting Mini-Course Sales
14244,137327257,305.0,,0,4,/vladislavonufrienko/pss3e19-eda-xgbregressor,Forecasting Mini-Course Sales
14245,138535296,313.0,34.34660289929202,1,17,/anzarwani2/eda-pycaret-with-xgboost,Forecasting Mini-Course Sales
14246,137487505,320.0,37.43506585905044,0,1,/keelanoliverbutler/ml-sales-competiton,Forecasting Mini-Course Sales
14247,137011586,317.0,41.78445048818647,0,5,/hacyxo/project,Forecasting Mini-Course Sales
14248,138498410,314.0,,2,7,/shashankjat10/pl-s3-e19-data-insights-xgboost,Forecasting Mini-Course Sales
14249,137898726,318.0,,0,1,/kavisekar/llm-emporium-the-data-discovery-haven,Forecasting Mini-Course Sales
14250,137128046,339.0,,0,8,/saugatkafley/pss3e19-forcasting-catboost-timeseriessplit,Forecasting Mini-Course Sales
14251,137778613,351.0,38.16358406374285,3,14,/dhruvch121/predicting-nums-sold,Forecasting Mini-Course Sales
14252,136811905,359.0,45.6915324451761,0,4,/yunsuxiaozi/ps3e19-linearregression,Forecasting Mini-Course Sales
14253,136937002,347.0,,0,1,/likithsh/ps-s3e19-using-time-series-cv,Forecasting Mini-Course Sales
14254,136424296,396.0,43.66806674610323,2,10,/chiranjeevisrinivas/playground-series-s3e19,Forecasting Mini-Course Sales
14255,136582836,354.0,,0,18,/anshtanwar/s3e19-new-features-eda,Forecasting Mini-Course Sales
14256,136388851,374.0,120.65779539551971,0,1,/thomasmeiner/s3e19-time-series-montecarlo-based-predictions,Forecasting Mini-Course Sales
14257,138496460,439.0,36.86151669031112,2,11,/docxian/ps-s3-e19-explo-r-ation,Forecasting Mini-Course Sales
14258,137495707,362.0,37.336849685293664,0,1,/maximeperez/lightgbm-baseline,Forecasting Mini-Course Sales
14259,136652393,392.0,37.37733019857596,0,10,/manavgupta92/must-have-automated-ensembling-model,Forecasting Mini-Course Sales
14260,136652393,392.0,37.37733019857596,0,10,/manavgupta92/must-have-automated-ensembling-model,Forecasting Mini-Course Sales
14261,136964470,401.0,,2,6,/gauravduttakiit/pss3e19-lazypredict,Forecasting Mini-Course Sales
14262,136395853,338.0,39.41152010969108,0,4,/stpeteishii/pss3-ep19-lgbm-with-optuna,Forecasting Mini-Course Sales
14263,136525070,456.0,47.26200149031267,0,4,/harshavardhanbabu/baseline-using-facebook-prophet-lb-47-262,Forecasting Mini-Course Sales
14264,136551668,366.0,49.5917592125138,0,4,/hariprasath1436/time-series-forecasting-with-catboost,Forecasting Mini-Course Sales
14265,137544425,389.0,,0,3,/tanmay9516/forecasting-mini-course-sales-38-081,Forecasting Mini-Course Sales
14266,137745209,405.0,37.97573546482386,0,2,/harshpriye/mini-course-sales-forecast,Forecasting Mini-Course Sales
14267,137909255,431.0,39.25271463303204,0,7,/atuljo/basic-start-model,Forecasting Mini-Course Sales
14268,136974672,409.0,38.64032963977498,0,7,/kkhandekar/course-sales-regression-stacking-regressor,Forecasting Mini-Course Sales
14269,136884693,443.0,,1,11,/katechubarova/forecasting-mini-course-sales-preparing-data-lr,Forecasting Mini-Course Sales
14270,136752645,463.0,,1,24,,Forecasting Mini-Course Sales
14271,137016863,462.0,39.85757971393832,3,20,/francescoliveras/ps-s3-e19-eda-model-en-es,Forecasting Mini-Course Sales
14272,137877808,391.0,105.32918382953784,0,8,/kim145/mini-course-sales-eda-first-cut-lstm,Forecasting Mini-Course Sales
14273,151539622,585.0,,29,66,/bennyfung/sales-forecast-by-facebook-prophet,Forecasting Mini-Course Sales
14274,137920332,321.0,,0,2,/aneekeshkumar/s03e19-xgb-without-2020data-covidyear,Forecasting Mini-Course Sales
14275,136472458,561.0,,2,4,/defdet/sales-prediction-with-nn,Forecasting Mini-Course Sales
14276,137162300,577.0,,0,12,/goolmonika/forecasting-using-etna-library-60-lines-catboost,Forecasting Mini-Course Sales
14277,138512098,560.0,44.20160569452515,0,8,/priyamsaha17/sales-forecast-using-autogluon-exp-1,Forecasting Mini-Course Sales
14278,136594255,553.0,45.64704038425098,2,13,/jimgruman/mini-course-sales,Forecasting Mini-Course Sales
14279,136710954,899.0,53.862146429441374,0,4,/lwissitoon/playground-series-s3e19-neural-regression,Forecasting Mini-Course Sales
14280,136420997,571.0,,1,1,/robertmumford/notebookf2a2b6da0f,Forecasting Mini-Course Sales
14281,138295207,536.0,44.23559315396295,0,1,/nguynbhonganh/notebook6bf1d25d5d,Forecasting Mini-Course Sales
14282,157368745,569.0,,0,14,/sjagkoo7/forecasting-mini-course-sales-s3e19-light-gbm,Forecasting Mini-Course Sales
14283,138453926,590.0,54.3278015159875,1,6,/mdmillenniumrahman/kaggle-first-compt,Forecasting Mini-Course Sales
14284,137211113,581.0,50.01568383336028,1,7,/amarloni/pgs3e19-eda-submission,Forecasting Mini-Course Sales
14285,138485628,620.0,47.96546157602755,0,2,/sviatoslavmatviiuk/notebook5fc2dc4655,Forecasting Mini-Course Sales
14286,138485628,620.0,47.96546157602755,0,2,/sviatoslavmatviiuk/notebook5fc2dc4655,Forecasting Mini-Course Sales
14287,138485628,620.0,50.25354761988838,0,2,/sviatoslavmatviiuk/notebook5fc2dc4655,Forecasting Mini-Course Sales
14288,137292141,639.0,46.25742134544775,0,15,/sujaykapadnis/75-models-approach-eda-sample-submission,Forecasting Mini-Course Sales
14289,137931481,642.0,47.418032365415286,1,12,/manishkumar7432698/ps3e19-feel-the-data-with-plotly-optuna,Forecasting Mini-Course Sales
14290,138498117,671.0,50.79166760467066,1,16,/abhashrai/sales-forecasting-playground-s3e19,Forecasting Mini-Course Sales
14291,148970975,624.0,,0,2,/lorresprz/forecasting-sales-with-prophet,Forecasting Mini-Course Sales
14292,139079895,665.0,,0,3,/ashx010/ps3e19-eda-model-optuna-lgbm,Forecasting Mini-Course Sales
14293,137285882,647.0,,0,4,/mexwell/ps3e19-eda-prophet-forecasting-at-scale,Forecasting Mini-Course Sales
14294,138288414,733.0,,0,9,/tuhinm2002/forecasting-mini-course-sales-simple-solution,Forecasting Mini-Course Sales
14295,136883037,753.0,,0,5,/abhikalpsrivastava15/simple-kaggle-forecasting-mini-course-sales,Forecasting Mini-Course Sales
14296,137519742,698.0,50.850863127976055,0,1,/tigerh/playground-sales-forecast,Forecasting Mini-Course Sales
14297,136821839,787.0,50.16978585177636,1,8,/ashishjagdishsharma/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14298,138147749,743.0,50.00797165878028,0,6,/agnijbiswas/playgrounds3e19-using-random-forest,Forecasting Mini-Course Sales
14299,137061022,800.0,,0,5,/kumarsakshat22/beginner-episode19,Forecasting Mini-Course Sales
14300,138088138,759.0,56.24584239923532,12,25,/kishore3914/sales-forecasting,Forecasting Mini-Course Sales
14301,136787755,804.0,,0,5,/kirtanmatalia26/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14302,138818033,784.0,,0,2,/keerthi4701/mini-course,Forecasting Mini-Course Sales
14303,140699960,756.0,,0,7,/natasha23/forecasting-sales-data-python,Forecasting Mini-Course Sales
14304,137910349,773.0,57.24841198305258,0,13,/reymaster/ps3-19-time-series-gdp-ensemble,Forecasting Mini-Course Sales
14305,137785254,791.0,,4,17,/dishaasinghi/ensembling-visualization-ps3e19,Forecasting Mini-Course Sales
14306,162531082,780.0,,10,23,/abdullah7aled/sales-forecasting,Forecasting Mini-Course Sales
14307,138075533,778.0,,0,3,/loki4514/times-series,Forecasting Mini-Course Sales
14308,138115413,769.0,,0,3,/realshaktigupta/forecasting-competition,Forecasting Mini-Course Sales
14309,138265496,877.0,,0,1,/jinkoike/notebookf52489f9bf,Forecasting Mini-Course Sales
14310,138150020,855.0,50.26647209438851,0,2,/geraldnyeo/ps3e19,Forecasting Mini-Course Sales
14311,136574988,843.0,50.38199658541388,0,15,/dumanmesut/course-sales-regression-xgb-lgbm-cat,Forecasting Mini-Course Sales
14312,136927743,868.0,,0,6,/davidhguerrero/one-tribute-to-eda-which-makes-sense,Forecasting Mini-Course Sales
14313,137879745,851.0,50.557910064355774,0,3,/violetmakena/sales-forcasting,Forecasting Mini-Course Sales
14314,137040650,763.0,50.74580840647738,0,5,/yazeedalsahouri03/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14315,137002881,1015.0,62.372892122822,0,3,/mirkosnguyn/store-sales-forecast-lgbm,Forecasting Mini-Course Sales
14316,138516515,1012.0,,1,13,/muhannadmansour/sales-forecasting-catboost,Forecasting Mini-Course Sales
14317,137109191,898.0,52.21703100272854,0,2,/pohzixiang/minicost-sales-forecasting-zx,Forecasting Mini-Course Sales
14318,137158820,883.0,,0,7,/gauthamupadhyaya/mini-course-sales,Forecasting Mini-Course Sales
14319,137872136,1034.0,57.97125650839531,1,6,/neupane9sujal/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14320,137078765,991.0,52.68093285629168,1,3,/tracyporter/play-3-19-ts-tf,Forecasting Mini-Course Sales
14321,137460352,869.0,52.683456765826506,4,13,/satishpb/mini-course-sales-forecasting,Forecasting Mini-Course Sales
14322,136936186,1006.0,,0,4,/ahmetyldrr/mini-course-sales-lightgbm-predict,Forecasting Mini-Course Sales
14323,137615502,889.0,53.03854263153103,2,6,/harsh2040/introductory-notebook-for-prediction,Forecasting Mini-Course Sales
14324,138045754,865.0,,2,13,/juhibhojani/forecasting-mini-sales-for-beginners,Forecasting Mini-Course Sales
14325,136806109,981.0,53.15333744124299,0,3,/natsu18/pgs-s3-e19-practicever,Forecasting Mini-Course Sales
14326,138507436,1007.0,53.78632252078987,2,10,/ashutoshdevpura/sales-prediction-analysis,Forecasting Mini-Course Sales
14327,136624818,913.0,54.109564102401,0,4,/farelarden/forecasting-mini-course-sales,Forecasting Mini-Course Sales
14328,138108207,922.0,54.60078839039449,0,3,/manuiaccarino/forecasting-sales,Forecasting Mini-Course Sales
14329,139191464,936.0,,4,7,/kagankoral/ps-s03e19-eda-modelling,Forecasting Mini-Course Sales
14330,138001895,958.0,55.55316424050041,2,2,/debamritapaul/artificial-neural-network-regressor,Forecasting Mini-Course Sales
14331,138453079,1045.0,,1,6,/yashkalkani/forcasting-mini-courses-sales,Forecasting Mini-Course Sales
14332,136873365,1058.0,62.97070980834264,0,5,/piyushjoshi01/s3e19-mini-course-sales,Forecasting Mini-Course Sales
14333,137165828,1061.0,,0,8,/muhriddinmalik/forecasting-mini-course-sales-notebook,Forecasting Mini-Course Sales
14334,137666802,1073.0,,12,22,/shivijaiswal/forecast-mini-sales,Forecasting Mini-Course Sales
14335,139840422,1090.0,,1,9,/arindambaruah/can-we-calculate-kaggle-sales-accurately,Forecasting Mini-Course Sales
14336,136867917,1083.0,,3,13,/gabrielbuchhorn/convert-date-to-day-month-and-year,Forecasting Mini-Course Sales
14337,137856616,1094.0,,0,6,/vinitkp/r-forecasting-eda-regression,Forecasting Mini-Course Sales
14338,137047910,1101.0,74.2026783049808,0,1,/cg24hr/forecast-mini-course-sales,Forecasting Mini-Course Sales
14339,136482570,1103.0,75.10690124036398,2,9,/uumutsezerr/s3e19-eda-and-feature-engineering,Forecasting Mini-Course Sales
14340,136651969,1106.0,,2,18,/swathiunnikrishnan/forecasting-mini-course-sales-using-regression,Forecasting Mini-Course Sales
14341,137027720,1109.0,75.10690124036398,2,6,/jocelyndumlao/exploring-insights-in-mini-course-sales,Forecasting Mini-Course Sales
14342,138201821,1119.0,78.61471512958327,0,2,/suvammistry/ps-s3e19,Forecasting Mini-Course Sales
14343,137889517,1133.0,84.71634833455309,7,14,/meeraajayakumar/forecasting-sales-r2-score-0-98,Forecasting Mini-Course Sales
14344,138472747,1145.0,102.63280020536229,0,2,/shivanaysan/forecasting-mini-course-sales-stacking-pipeline,Forecasting Mini-Course Sales
14345,136843671,1147.0,107.15545444117085,0,0,/leotom/playground-s3-e19,Forecasting Mini-Course Sales
14346,137332565,1171.0,,0,8,/udaykirankavaturu/playground-series-season-3-episode-19,Forecasting Mini-Course Sales
14347,143593184,6.0,,0,1,/conjuring92/retriever-data-prep-v4,Kaggle - LLM Science Exam
14348,140651730,17.0,0.7717436537661259,13,151,/nlztrk/openbook-debertav3-large-baseline-single-model,Kaggle - LLM Science Exam
14349,146229927,28.0,,0,4,/daisuketakahashi/wikipedia-bi-gram-inverted-index,Kaggle - LLM Science Exam
14350,147713054,5.0,0.9280066583437372,0,3,/zaburo/llm-sience-exam-5th-place-solution,Kaggle - LLM Science Exam
14351,143321420,25.0,,2,68,/mbanaei/finding-270k-wikipedia-stem-articles,Kaggle - LLM Science Exam
14352,138287757,11.0,0.6508531002913015,12,26,/zzy990106/llama-7b-infer,Kaggle - LLM Science Exam
14353,141748094,23.0,0.8243861839367458,5,39,/hustzx/lb0-824-deberta-with-context-ensemble,Kaggle - LLM Science Exam
14354,140539167,19.0,,10,58,/steubk/the-art-of-prompt-engineering,Kaggle - LLM Science Exam
14355,139359682,26.0,0.7561381606325425,18,55,/hycloud/2023kagglellm-deberta-v3-large-model1-inference,Kaggle - LLM Science Exam
14356,142189414,50.0,,12,42,/samson8/how-to-create-wikipedia-embeddings,Kaggle - LLM Science Exam
14357,144645400,52.0,0.8216812317935913,0,0,/cecilll/fork-of-fork-of-0-806-sharing-my-trained-with-co,Kaggle - LLM Science Exam
14358,138253501,32.0,,1,44,/quangbk/open-book-llm-science-exam-reduced-ram-usage,Kaggle - LLM Science Exam
14359,141695423,95.0,,70,291,/cdeotte/how-to-train-open-book-model-part-1,Kaggle - LLM Science Exam
14360,143254095,140.0,0.3066999583853522,0,0,/fanyang99/lb-0-762-train-4-fold-and-ensemble,Kaggle - LLM Science Exam
14361,139480125,94.0,0.580108198085725,2,8,/mozattt/lb0-726-peft-with-3k-new-data,Kaggle - LLM Science Exam
14362,147357580,67.0,,7,22,/fejust/llmse-open-book-tpu-training,Kaggle - LLM Science Exam
14363,143026709,147.0,,2,4,/datadote/llm-train-csv-eda,Kaggle - LLM Science Exam
14364,143485384,160.0,0.6446109030378683,0,0,/wentap/vicuna-7b-v15-hf-perplexity-ranking,Kaggle - LLM Science Exam
14365,153222520,43.0,,0,0,/jay00hwang/generate-wiki-context,Kaggle - LLM Science Exam
14366,141820263,49.0,,0,1,/bobfromjapan/llm-science-exam-re-translation-by-deepl-api,Kaggle - LLM Science Exam
14367,140068776,159.0,,1,6,/tanyong666/llama2-7b-infer-in-8bit,Kaggle - LLM Science Exam
14368,144003833,151.0,,15,19,/ksmcg90/faster-context-extraction-pyarrow-fixed,Kaggle - LLM Science Exam
14369,136535547,184.0,,0,1,/hidngnguyna/llm-science-exam-eda,Kaggle - LLM Science Exam
14370,146091836,255.0,,0,0,/xiaocao123/how-to-train-open-book-model,Kaggle - LLM Science Exam
14371,136625881,154.0,,0,0,/namgalielei/debertav3-base-multiplechoice,Kaggle - LLM Science Exam
14372,143949686,194.0,,0,11,/illidan7/llmse-study-for-the-right-exam,Kaggle - LLM Science Exam
14373,144502926,240.0,,2,5,/jonathanchan/csc494-deberta-v3-270k-articles,Kaggle - LLM Science Exam
14374,145784741,163.0,0.8152309612983777,1,1,/wamiottowang/trained-with-context-model,Kaggle - LLM Science Exam
14375,140489796,212.0,0.5170620058260498,0,6,/mgoksu/4-fold-cv-on-200-samples-earlystopping-map3-eval,Kaggle - LLM Science Exam
14376,143657463,249.0,,1,2,/mujrush/eda-cosine-similarity-of-dataset-each-text,Kaggle - LLM Science Exam
14377,136529054,112.0,,1,16,/seshurajup/llm-science-exam-eda,Kaggle - LLM Science Exam
14378,137119312,173.0,,3,31,/judehunt23/llm-science-exam-wikipedia-graph-analysis,Kaggle - LLM Science Exam
14379,144959758,259.0,0.7118185601331661,0,1,/potterhan/llm-exam-deberta,Kaggle - LLM Science Exam
14380,145164630,142.0,0.8535164377861008,3,29,/goelyash/llm-science-mistral-7b,Kaggle - LLM Science Exam
14381,145164630,142.0,0.8535164377861008,3,29,/goelyash/llm-science-mistral-7b,Kaggle - LLM Science Exam
14382,142208181,200.0,,0,3,/rin121/llm-se-pytorch-lightning-simple-training-code,Kaggle - LLM Science Exam
14383,145995491,148.0,,0,0,/ranchantan/llm-se-ensemble,Kaggle - LLM Science Exam
14384,139580385,225.0,,0,0,/chep66/lb-0-709-llm-se-deberta-v3-large-t-1k-wiki,Kaggle - LLM Science Exam
14385,144386128,266.0,,0,0,/myominhtet/finding-context-on-wiki-20220301-en-sci,Kaggle - LLM Science Exam
14386,137619273,115.0,0.7170203911776941,5,24,/takanashihumbert/llm-extra-data-with-cv-and-earlystopping,Kaggle - LLM Science Exam
14387,137194267,186.0,,0,6,/defdet/filtering-by-answering,Kaggle - LLM Science Exam
14388,142774083,227.0,0.8329171868497715,1,26,/miteshadake/llm-science-exam-fork-of-fork-of-fork-of-0-806,Kaggle - LLM Science Exam
14389,143521493,54.0,0.8129421556387852,18,43,/cpmpml/uni-tianyan-70b-with-wikipedia-rag,Kaggle - LLM Science Exam
14390,140694292,659.0,,0,5,/mowgli2/longformer-peft-llmscience,Kaggle - LLM Science Exam
14391,137071419,275.0,,12,123,/jjinho/open-book-llm-science-exam,Kaggle - LLM Science Exam
14392,140476951,231.0,,16,47,/judith007/ensemble-score-boost-lb-0-763,Kaggle - LLM Science Exam
14393,142866747,295.0,0.828339575530587,0,0,/wchan757/llm-science-exam-approach,Kaggle - LLM Science Exam
14394,136545735,260.0,0.679983354140657,4,41,/zifencai/deberta-v3-large-inference,Kaggle - LLM Science Exam
14395,144858236,299.0,,2,3,/romanweilguny/train-open-book-p1-v3-7,Kaggle - LLM Science Exam
14396,140551946,642.0,,3,24,/max2020/using-gpt4-the-art-of-prompt-engineering,Kaggle - LLM Science Exam
14397,141597588,280.0,0.7765293383270913,0,4,/yrnmmh/notebook7798b08d0d,Kaggle - LLM Science Exam
14398,140718126,363.0,0.3876404494382022,0,6,/serjhenrique/llmse-t5-text2text-pipeline,Kaggle - LLM Science Exam
14399,142160153,327.0,,0,2,/ohmeow/differential-learning-rates-and-lora,Kaggle - LLM Science Exam
14400,139940277,324.0,,43,244,/radek1/new-dataset-deberta-v3-large-training,Kaggle - LLM Science Exam
14401,148236943,298.0,,1,4,/junxhuang/running-llm-with-flexible-sharding-technique,Kaggle - LLM Science Exam
14402,139450563,637.0,,1,8,/johnowhitaker/benchmark-gpt3-5,Kaggle - LLM Science Exam
14403,142537336,318.0,0.5588847274240526,1,2,/nikoolaylovyagin/llm-exam-tensorflow-and-distilbert1,Kaggle - LLM Science Exam
14404,141983716,377.0,,2,30,/jasonheesanglee/0-81-workworkworkworkwork,Kaggle - LLM Science Exam
14405,144330453,379.0,,1,9,/sircausticmail/llm-exam-benchmarking,Kaggle - LLM Science Exam
14406,145167584,582.0,0.8734914689970874,7,25,/kononenko/max-context-2700-platypus2-70b-with-wikipedia-rag,Kaggle - LLM Science Exam
14407,144402356,429.0,,0,5,/dangnguyen97/transformers-0-86,Kaggle - LLM Science Exam
14408,144731110,586.0,,0,3,/hodinhtrieu/llmse-using-platypus2,Kaggle - LLM Science Exam
14409,158137042,459.0,,0,0,/alexjoe/how-to-finetune-llms-with-lora,Kaggle - LLM Science Exam
14410,137692338,596.0,,0,1,/satyabrat35/lb-710-t5-with-merged-deberta,Kaggle - LLM Science Exam
14411,137037550,1159.0,,0,3,/lonnieqin/llm-science-exam-with-alpaca,Kaggle - LLM Science Exam
14412,145760480,621.0,0.6385767790262163,1,2,/shamepooh/scibert-baseline-inferring-with-rag,Kaggle - LLM Science Exam
14413,141365298,411.0,0.8085726175613817,8,31,/siddhvr/llm-science-exam-sub-0-808,Kaggle - LLM Science Exam
14414,141729464,412.0,0.7950478568456097,2,1,/scenerysunfireink/using-multi-qa-minilm-l6-cos-v1,Kaggle - LLM Science Exam
14415,143925258,466.0,,4,0,/pimang62/fine-tuned-llama2-with-peft,Kaggle - LLM Science Exam
14416,142529762,529.0,,0,2,/bkowshik/exploratory-data-analysis-llm-science-exam,Kaggle - LLM Science Exam
14417,136994063,704.0,,0,2,/zh4men9/llm-science-exam-k-fold-submission,Kaggle - LLM Science Exam
14418,153593835,551.0,,26,63,/bennyfung/bert-model-for-multiple-choice,Kaggle - LLM Science Exam
14419,137047081,375.0,,0,0,/shangshandalaohu/simple-loss-perplexity-llm-baseline,Kaggle - LLM Science Exam
14420,144221829,348.0,0.4837702871410733,0,5,/josuehuaman/llm-science-exam-solution,Kaggle - LLM Science Exam
14421,139527149,693.0,0.7347066167290883,27,98,/datafan07/single-model-rewardtrainer-lora-llm,Kaggle - LLM Science Exam
14422,145627417,317.0,0.8399916770703291,0,5,/minhsienweng/longformer-tf-idf-wikipedia-retrieval,Kaggle - LLM Science Exam
14423,145893400,855.0,0.7954640033291718,0,0,/alekseytrepetsky/llama-inference,Kaggle - LLM Science Exam
14424,142918417,795.0,,2,5,/limamateus/kaggle-llm-other-parameters-and-text-size,Kaggle - LLM Science Exam
14425,141720498,723.0,0.5081148564294624,3,17,/gokifujiya/llm-science-exam-with-bert-baseline,Kaggle - LLM Science Exam
14426,143187837,744.0,,0,2,/damonhan/fine-turn-llama2-llm,Kaggle - LLM Science Exam
14427,138837835,1433.0,,2,34,/mayank00rastogi/deberta-v3-xlargemcq-s-ipynb,Kaggle - LLM Science Exam
14428,144301086,778.0,0.3811901789429879,1,13,/enricomanosperti/llm-science-exam-with-bert,Kaggle - LLM Science Exam
14429,143952953,786.0,0.7357469829379939,6,22,/alvinleenh/0-742-llm-science-exam-peft-with-deberta,Kaggle - LLM Science Exam
14430,140385171,787.0,0.4394506866416977,3,21,/cmsm12/locally-fine-tuning-llama-2-using-qlora,Kaggle - LLM Science Exam
14431,147719172,837.0,,0,1,/shufflecss/open-book-qa-debertav3-large,Kaggle - LLM Science Exam
14432,144166233,850.0,,0,5,/tony92151/usage-of-gguf-llama2-7b,Kaggle - LLM Science Exam
14433,141581963,869.0,0.56221389929255,0,23,/serhiikharchuk/starter-notebook-ranked-predictions-with-bert,Kaggle - LLM Science Exam
14434,142105389,703.0,,0,3,/evanarlian/llmse-meta-galactica,Kaggle - LLM Science Exam
14435,139662333,888.0,,1,1,/myogye/notebook14400fc14e,Kaggle - LLM Science Exam
14436,143017671,953.0,0.3753641281731168,4,4,/gavinmin/qwen-7b-int4-inference-score-0-7-on-train,Kaggle - LLM Science Exam
14437,137007193,972.0,,0,2,/delayedkarma/llm-qa-bert-basic-lb0-563,Kaggle - LLM Science Exam
14438,143304062,939.0,0.3736995422388681,0,3,/polyakovstepan/baseline-llm-science-exam,Kaggle - LLM Science Exam
14439,143371308,984.0,,0,0,/stanmt/llm-sci-exam-open-book-baselinev1,Kaggle - LLM Science Exam
14440,141983686,1010.0,,2,8,/dominic789654/how-to-train-open-book-model-part-2-fixed,Kaggle - LLM Science Exam
14441,141371586,982.0,0.4764877236787344,0,0,/planetassem/llm-science-exam-my-beginner-code,Kaggle - LLM Science Exam
14442,143391903,1016.0,0.8335414065751148,0,0,/viplav113/fork-of-llm-questionanswer,Kaggle - LLM Science Exam
14443,141176264,1133.0,0.4714939658759876,0,2,/rayzzzr/locally-fine-tuning-llama-2-using-qlora,Kaggle - LLM Science Exam
14444,140655001,1089.0,0.7089055347482311,0,0,/iver666/inference-using-3-trained-deberta-v3-models,Kaggle - LLM Science Exam
14445,141547784,1094.0,,0,0,/xiu0714/deberta-llm-exam,Kaggle - LLM Science Exam
14446,144515217,1104.0,,0,2,/aynoji/watchara-26-csc494-2023-midterm,Kaggle - LLM Science Exam
14447,136604072,1108.0,,18,104,/debarshichanda/qlora-falcon-7b-training,Kaggle - LLM Science Exam
14448,141343379,1129.0,0.5249687890137323,0,5,/vijayendrad/kaggle-distilberttf-model1,Kaggle - LLM Science Exam
14449,141870073,1131.0,0.8243861839367458,0,10,/sreekanthpolu/llm-science-exam,Kaggle - LLM Science Exam
14450,141870073,1131.0,0.8243861839367458,0,10,/sreekanthpolu/llm-science-exam,Kaggle - LLM Science Exam
14451,137571518,1157.0,,0,0,/kimijima/bert-0-363,Kaggle - LLM Science Exam
14452,142752784,1192.0,,0,6,/smokeyscraper/llm-nb,Kaggle - LLM Science Exam
14453,139633441,1467.0,0.4696213066999575,0,7,/gumballnguyen/flan-t5-model,Kaggle - LLM Science Exam
14454,139591272,1248.0,0.7211818560133165,0,1,/evgeniyvigurskiy/bert-qlora-inference-ipynb,Kaggle - LLM Science Exam
14455,142646835,1275.0,,0,1,/ajaysadhu/baseline-newdata,Kaggle - LLM Science Exam
14456,144959803,1265.0,,0,0,/hyunjin123/fork-of-0-806-sharing-my-trained-with-con-fe3f24,Kaggle - LLM Science Exam
14457,145105019,1260.0,0.8154390345401582,0,0,/gangyongjin/comp-llm-science-yongjin,Kaggle - LLM Science Exam
14458,140278142,1218.0,,0,2,/sontungkieu/llm-science-exam-training,Kaggle - LLM Science Exam
14459,141037747,1287.0,,0,8,/zilanyu/visual-analysis-of-datasets-eda,Kaggle - LLM Science Exam
14460,142532720,1261.0,,0,0,/dwit392/context-more-data-t-1,Kaggle - LLM Science Exam
14461,141542630,1311.0,0.8079483978360383,1,12,/coldslim/llm-science-exam-project,Kaggle - LLM Science Exam
14462,138508962,1207.0,0.4879317519766949,0,4,/maxperozek/fine-tuning-bert-multiple-choice-tf,Kaggle - LLM Science Exam
14463,141152661,1390.0,0.6227632126508522,0,1,/ndranathunga/debertav3-large,Kaggle - LLM Science Exam
14464,144834197,1342.0,,1,0,/donkeys/vec256t5,Kaggle - LLM Science Exam
14465,137079874,1352.0,0.5607573866000823,0,1,/alenic/simple-flan-t5-large,Kaggle - LLM Science Exam
14466,139345038,1426.0,0.5070744902205568,1,8,/shivaiyer129/llm-science-exam-t5-model,Kaggle - LLM Science Exam
14467,144308440,1573.0,,0,4,/zakirkhanaleemi/science-exam-v3,Kaggle - LLM Science Exam
14468,148517602,1606.0,,0,10,/yaaangzhou/transfomer-pytorch-code-and-learning-note,Kaggle - LLM Science Exam
14469,139474384,1452.0,,1,4,/dashmeta/add-3000-data-to-train,Kaggle - LLM Science Exam
14470,139897981,1619.0,0.7561381606325425,0,1,/simonemento/llm-science-exam,Kaggle - LLM Science Exam
14471,146200157,1635.0,,2,3,/dstomcray/2023-kaggle-llm-multiple-choice-questions,Kaggle - LLM Science Exam
14472,139301023,1520.0,0.7114024136496043,0,0,/mjulianimsj75/new-dataset-deberta-v3-large-training,Kaggle - LLM Science Exam
14473,140342645,1405.0,,0,1,/cenzop/eda-data-gathering-llm-se-wiki-stem-1k-ds,Kaggle - LLM Science Exam
14474,136909082,1558.0,,2,6,/coronatianmao/memo-some-needed-knowledge-for-the-competition,Kaggle - LLM Science Exam
14475,141989508,1440.0,0.7476071577195174,0,6,/neupane9sujal/deberta-for-llm-exam-0-74,Kaggle - LLM Science Exam
14476,139286007,1482.0,0.7376196421140239,0,1,/aacashsrinath/llm-science-exam-answer-predictions,Kaggle - LLM Science Exam
14477,139056703,1454.0,0.737203495630462,0,2,/astitwaagarwal/llm-notebook-2,Kaggle - LLM Science Exam
14478,145137636,1461.0,0.4712858926342065,0,3,/satyanshu404/science-llm,Kaggle - LLM Science Exam
14479,140468967,1468.0,,0,2,/erijoel/llmse-data-gathering-with-few-shot-prompting,Kaggle - LLM Science Exam
14480,140464483,1650.0,0.7355389096962128,0,2,/love2echo/rl-llms-lora,Kaggle - LLM Science Exam
14481,139364337,1487.0,,2,51,/maverickss26/lb-0-733-llm-science-exam,Kaggle - LLM Science Exam
14482,142353678,1657.0,,0,0,/yamitomo/new-dataset-deberta-v3-large-training,Kaggle - LLM Science Exam
14483,138922245,1683.0,0.5058260507698701,0,1,/noobhocai/new-dataset-deberta-v3-large-training,Kaggle - LLM Science Exam
14484,141501733,1603.0,0.7247191011235949,0,3,/anhndo/workflow-for-fine-tuning-llm-beginner-friendly,Kaggle - LLM Science Exam
14485,137010219,1768.0,,7,170,/leonidkulyk/eda-data-gathering-llm-se-wiki-stem-1k-ds,Kaggle - LLM Science Exam
14486,137090458,1703.0,,0,5,/amulil/vicuna-7b-v1-3-perplexity-ranking,Kaggle - LLM Science Exam
14487,136714587,1729.0,,0,11,/quekyaojing/graph-approaches-for-eda-solution,Kaggle - LLM Science Exam
14488,138770068,1913.0,0.6960049937578024,1,15,/haiber/llm-with-more-preprocessing-and-cv,Kaggle - LLM Science Exam
14489,136813779,1926.0,0.6924677486475237,0,27,/tanreinama/t5-loss-scoring-for-llm-science-exam,Kaggle - LLM Science Exam
14490,137684572,1933.0,0.6918435289221804,4,38,/eishkaran/kaggle-llm-science-exam,Kaggle - LLM Science Exam
14491,137239045,1952.0,0.679983354140657,0,7,/ashishjagdishsharma/llm-science-exam,Kaggle - LLM Science Exam
14492,137463996,1954.0,0.679983354140657,0,3,/himanshukumar7079/kaggle-llm-science-exam,Kaggle - LLM Science Exam
14493,137463996,1954.0,0.679983354140657,0,3,/himanshukumar7079/kaggle-llm-science-exam,Kaggle - LLM Science Exam
14494,139626131,1981.0,0.5312109862671652,1,4,/lwolwo/simple-correlation-between-the-number-of-question,Kaggle - LLM Science Exam
14495,141130540,1969.0,,0,9,/tenffe/zhangxin-test-reward-model,Kaggle - LLM Science Exam
14496,140669447,1974.0,0.5942571785268405,0,11,/giraffeingreen/guidance-psmathur-orca-mini-v3-7b,Kaggle - LLM Science Exam
14497,137646617,1990.0,,0,13,/utkarshx27/llm-science-exam-deberta-v3-base,Kaggle - LLM Science Exam
14498,136487869,2018.0,0.6111111111111103,4,66,/vad13irt/starter-notebook-deberta-base-lr-3e-5-7-epochs,Kaggle - LLM Science Exam
14499,140309216,2056.0,,1,32,/awsaf49/llm-science-exam-kerascore-kerasnlp-tpu,Kaggle - LLM Science Exam
14500,137304872,2020.0,0.5905118601747806,0,2,/oostg0t/baseline-deberta-v3-base-train-pred,Kaggle - LLM Science Exam
14501,141298021,2066.0,0.5740740740740732,0,15,/tigerh/learning-llm-and-using-flan-t5-logits,Kaggle - LLM Science Exam
14502,149600051,2091.0,0.3037869330004167,0,3,/fathinahizzati/bow-tfidf-2-new,Kaggle - LLM Science Exam
14503,141473164,2110.0,0.4970869746150638,0,0,/thefreakin/scique-bert,Kaggle - LLM Science Exam
14504,141132276,2151.0,,0,2,/kaggleaccount2112/eda-llm-science-exam-data,Kaggle - LLM Science Exam
14505,136957533,2153.0,0.540366208905534,1,5,/vinayak121/with-bert,Kaggle - LLM Science Exam
14506,136957533,2153.0,0.5468164794007485,1,5,/vinayak121/with-bert,Kaggle - LLM Science Exam
14507,144008828,2160.0,0.4989596337910936,0,6,/ahsh37/my-llm-compitions,Kaggle - LLM Science Exam
14508,140552419,2210.0,0.5403662089055338,0,0,/baghasadikusuma/llm-with-bert,Kaggle - LLM Science Exam
14509,139577861,2197.0,0.5387016229712851,0,2,/gariton/starter-notebook-ranked-predictions-with-bert,Kaggle - LLM Science Exam
14510,139907878,2204.0,0.5066583437369947,0,8,/letuanm/bert-uncased-sequence-classification,Kaggle - LLM Science Exam
14511,139907878,2204.0,0.4889721181856007,0,8,/letuanm/bert-uncased-sequence-classification,Kaggle - LLM Science Exam
14512,139431640,2229.0,0.5114440282979601,0,1,/j13mehul/learning-approaches-embedding-finetuning,Kaggle - LLM Science Exam
14513,139431640,2229.0,0.4866833125260086,0,1,/j13mehul/learning-approaches-embedding-finetuning,Kaggle - LLM Science Exam
14514,143712801,2303.0,0.5074906367041193,0,4,/pavan9065/explore-predictions-with-bert,Kaggle - LLM Science Exam
14515,146637940,2324.0,0.4669163545568033,0,0,/div1996p/flan-t5-zero-shot-inferencing,Kaggle - LLM Science Exam
14516,138661946,2360.0,,2,17,/patriciabrezeanu/llm-science-exam-with-openai-api,Kaggle - LLM Science Exam
14517,137062011,2313.0,,0,5,/stpeteishii/llm-science-exam-answers-are-text-dataset,Kaggle - LLM Science Exam
14518,140705348,2346.0,0.4804411152725752,0,6,/krooz0/performing-zero-shot-learning-with-flan-t5,Kaggle - LLM Science Exam
14519,143148906,2428.0,,0,0,/afiqhatta/how-to-train-open-book-model,Kaggle - LLM Science Exam
14520,137512957,2404.0,,2,8,/jocelyndumlao/llms-challenging-scientific-queries,Kaggle - LLM Science Exam
14521,144830591,2409.0,0.4719101123595499,0,8,/adityaghuse/llm-exam,Kaggle - LLM Science Exam
14522,137107197,2391.0,0.4683728672492709,0,1,/anubhav1302/llm-evaluation-t5-encoder-similarity-score,Kaggle - LLM Science Exam
14523,148636518,2472.0,,0,1,/ifyokoh/llm-science-exam,Kaggle - LLM Science Exam
14524,141158412,2418.0,0.4615064502704947,0,12,/amanmukati/llm-qa,Kaggle - LLM Science Exam
14525,137141240,2349.0,,0,0,/itaykoren2/llm-science-exam-bert-base-uncased,Kaggle - LLM Science Exam
14526,140868448,2516.0,,0,3,/shikha130vv/quantization,Kaggle - LLM Science Exam
14527,138569787,2433.0,0.4431960049937578,0,0,/trnmtin/llm-exam,Kaggle - LLM Science Exam
14528,136751182,2526.0,,0,6,/dmitriygakh/llm-sci-exam-eda-based-on-text-structure,Kaggle - LLM Science Exam
14529,161074875,2541.0,,0,0,/adlrmdn/kaggle-llm-science-self-exam,Kaggle - LLM Science Exam
14530,144837559,2545.0,,1,3,/navneetsajwan/magic-of-retrieval-augmented-generation-rag,Kaggle - LLM Science Exam
14531,137075907,2574.0,0.3670411985018726,1,1,/scottnewcomer/llm-science-street-tfidf,Kaggle - LLM Science Exam
14532,138250853,2581.0,0.3612151477320018,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14533,138250853,2581.0,0.3732833957553059,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14534,138250853,2581.0,0.3720349563046193,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14535,138250853,2581.0,0.3720349563046194,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14536,138250853,2581.0,0.3739076154806492,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14537,138250853,2581.0,0.3693300041614651,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14538,138250853,2581.0,0.365376612567624,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14539,138250853,2581.0,0.3580940491052853,0,6,/spike8086/the-easiest-llm-example-with-bi-lstm,Kaggle - LLM Science Exam
14540,144994630,2554.0,0.3778610070744901,0,5,/simonovaanna/science-exam-using-bert,Kaggle - LLM Science Exam
14541,140186509,2587.0,0.3826466916354557,4,9,/idrakesedbeyli/idrak-llm,Kaggle - LLM Science Exam
14542,138813861,2634.0,,0,15,/deepaktripathiuk/simple-solution-with-universal-sentence-encoder,Kaggle - LLM Science Exam
14543,142016286,2632.0,0.3395755305867672,0,3,/rajatraj0502/kaggle-llm-science-exam,Kaggle - LLM Science Exam
14544,140499011,2633.0,0.3322929671244281,0,2,/abhishekmehra002/science-exam,Kaggle - LLM Science Exam
14545,147058204,4.0,0.4297919214283305,1,3,/chumajin/commonlit2-4th-place-inference,CommonLit - Evaluate Student Summaries
14546,145902061,9.0,0.4569263930543844,0,16,/takoihiraokazu/sub-ex263-seq4200,CommonLit - Evaluate Student Summaries
14547,140108707,10.0,0.4978674574959583,0,3,/leehann/commonlit-inference,CommonLit - Evaluate Student Summaries
14548,142954448,23.0,,0,0,/catchbat/eda-on-the-target,CommonLit - Evaluate Student Summaries
14549,146458836,7.0,0.456217148291918,0,0,/emiria/cess-private-0-454-only-for-entertainment,CommonLit - Evaluate Student Summaries
14550,141167394,106.0,,0,11,/vikramsandu/dl-nlp-commonlit-summaries,CommonLit - Evaluate Student Summaries
14551,145757853,16.0,,0,1,/conjuring92/g11-augmentations,CommonLit - Evaluate Student Summaries
14552,139968014,32.0,,0,12,/raki21/summary-examples-by-content-and-wording,CommonLit - Evaluate Student Summaries
14553,146044818,49.0,0.4334506490801868,0,4,/rohitsingh9990/commonlit-ensemble-new-v2,CommonLit - Evaluate Student Summaries
14554,147579268,3.0,0.428232768684937,0,0,/koba35/infer-commonlit,CommonLit - Evaluate Student Summaries
14555,144071703,73.0,,0,1,/nlchen/commonlit-create-lgbm-features-new,CommonLit - Evaluate Student Summaries
14556,146217535,99.0,1.5281474942563715,9,59,/bulivington/transformers-predictions-base,CommonLit - Evaluate Student Summaries
14557,138991770,42.0,,0,1,/luki493/eda-scoring-stats-wc-lda,CommonLit - Evaluate Student Summaries
14558,140322755,1013.0,,7,100,/alejopaullier/introduction-to-transformers,CommonLit - Evaluate Student Summaries
14559,141533423,891.0,0.5788837037493473,0,0,/ileln0414/notebookc7f8bfec78,CommonLit - Evaluate Student Summaries
14560,143275626,84.0,,0,4,/youwbpyr/filtering-prompt-text-using-tfidfvectorizer-cosi,CommonLit - Evaluate Student Summaries
14561,137394363,86.0,,0,13,/javigallego/commonlit-complete-eda-using-nltk,CommonLit - Evaluate Student Summaries
14562,143592761,79.0,,0,13,/kimseunghee/kr-code-comments-beginner-friendly-bert,CommonLit - Evaluate Student Summaries
14563,140054844,629.0,,0,3,/seungjunlim/notebookc187d58ee5,CommonLit - Evaluate Student Summaries
14564,137938817,52.0,,0,23,/sercanyesiloz/commonlit-tf-idf-xgb-baseline,CommonLit - Evaluate Student Summaries
14565,144154896,526.0,,0,3,/damikaanupama/eda-spellcheck-comparison,CommonLit - Evaluate Student Summaries
14566,141763213,665.0,,1,7,/kononenko/commonlit-ess-text-readability-eda,CommonLit - Evaluate Student Summaries
14567,138637832,368.0,0.5067669931271843,0,0,/neos960518/commonlit-inference,CommonLit - Evaluate Student Summaries
14568,141243059,182.0,0.566525304740451,0,2,/dttjrhk/first-try-with-deberta-of-evaluate-summaries,CommonLit - Evaluate Student Summaries
14569,146030565,497.0,,0,2,/bhavesjain/commonlit-2023-train,CommonLit - Evaluate Student Summaries
14570,141693623,983.0,0.5159190695041098,1,15,/ao9mame/commonlit-deberta-with-transformers,CommonLit - Evaluate Student Summaries
14571,137397120,487.0,0.5991389393502442,3,8,/docxian/commonlit-explore-train-summaries,CommonLit - Evaluate Student Summaries
14572,136633745,184.0,0.8397774354606169,0,18,/pjmathematician/commonlit-similarity-vs-scores-simple-inference,CommonLit - Evaluate Student Summaries
14573,141120454,1025.0,0.6593581717321272,0,4,/omarvivas/cbmodel-v1,CommonLit - Evaluate Student Summaries
14574,140169236,252.0,,0,11,/adityaparikh668/tfidf-xgb-minimum-preprocessing,CommonLit - Evaluate Student Summaries
14575,143115870,394.0,,2,14,/prithviraj7387/commonlit-student-summaries-eda,CommonLit - Evaluate Student Summaries
14576,142688892,1031.0,1.728739216512134,1,7,/ianchute/magic-number-model,CommonLit - Evaluate Student Summaries
14577,144925886,383.0,,0,0,/rakesh82rawat/rrc3-commonlit-eval-student-summaries-non-llm,CommonLit - Evaluate Student Summaries
14578,141158557,742.0,,0,11,/thomasrochefort/a-simple-huggingface-dataset-class-to-get-started,CommonLit - Evaluate Student Summaries
14579,138038993,582.0,0.4989213077525192,1,10,/sourabhsingh03993493/transformers-predictions-base,CommonLit - Evaluate Student Summaries
14580,138038993,582.0,0.4989223788571579,1,10,/sourabhsingh03993493/transformers-predictions-base,CommonLit - Evaluate Student Summaries
14581,140897876,437.0,,0,1,/satheeshbhukya1/common-lit-using-tfdf,CommonLit - Evaluate Student Summaries
14582,140897876,437.0,,0,1,/satheeshbhukya1/common-lit-using-tfdf,CommonLit - Evaluate Student Summaries
14583,140984885,609.0,0.9808891853959486,1,5,/ahmedhassan0/commonlit-simple-siamese-network-tensorflow,CommonLit - Evaluate Student Summaries
14584,145823317,413.0,0.5605906028949603,0,5,,CommonLit - Evaluate Student Summaries
14585,144076565,201.0,0.5462002620149904,0,2,/xinyilea/deberta-v3-pytorch,CommonLit - Evaluate Student Summaries
14586,147761765,1004.0,,0,3,/kpfmma/efficiency-2nd-place-inference-catboost,CommonLit - Evaluate Student Summaries
14587,137684517,483.0,0.7529709124134047,0,0,/yuriao/commonlit-lgbm,CommonLit - Evaluate Student Summaries
14588,146190828,140.0,0.4597888279374388,0,5,/stochoshi/commonlit-d1-cpu-code-4,CommonLit - Evaluate Student Summaries
14589,147292386,1029.0,,0,2,/jhony1/9th-place-efficiency-solution,CommonLit - Evaluate Student Summaries
14590,141639259,511.0,,0,14,/alexandervc/commonlit-1,CommonLit - Evaluate Student Summaries
14591,139352199,493.0,0.5732264627204198,7,18,/santiagopedroza/svr-using-deberta-embeddings-baseline,CommonLit - Evaluate Student Summaries
14592,142648685,1100.0,,0,6,/hidebu/eda-deepen-understanding-for-feature-eng,CommonLit - Evaluate Student Summaries
14593,142343820,964.0,0.9804811123580924,0,3,/nithinreddy90/commonlit-student-summaries-evaluation,CommonLit - Evaluate Student Summaries
14594,142343820,964.0,0.979458752297842,0,3,/nithinreddy90/commonlit-student-summaries-evaluation,CommonLit - Evaluate Student Summaries
14595,142490390,974.0,,0,2,/natsumiarai/hisui-eda,CommonLit - Evaluate Student Summaries
14596,146184479,1038.0,0.4932289252884162,0,1,/geoffreybeulque/commonlit-efficiency-final-submission,CommonLit - Evaluate Student Summaries
14597,140331281,841.0,,2,6,/kimijima/prepare-for-ml-visualization-of-training-data,CommonLit - Evaluate Student Summaries
14598,140813248,179.0,,0,2,/tovvelie/simple-fine-tune-a-pretrained-model,CommonLit - Evaluate Student Summaries
14599,143769793,834.0,0.5953202573302192,2,15,/enricomanosperti/commonlit-evaluate-student-summaries-with-tfds,CommonLit - Evaluate Student Summaries
14600,138876285,206.0,,0,3,/mlffkr/common-lit-ess-train,CommonLit - Evaluate Student Summaries
14601,141722480,944.0,,0,6,/riadalmadani/debertav3-tf-4-fold-model,CommonLit - Evaluate Student Summaries
14602,138464419,1018.0,,0,1,/maria222222/embed-catboost-try,CommonLit - Evaluate Student Summaries
14603,143698565,1171.0,0.563775642160323,0,16,/synful/simple-distilroberta-base-10mins-to-train,CommonLit - Evaluate Student Summaries
14604,136891918,1373.0,,3,8,/fadmadahouz/getting-started-with-nlp-for-beginners,CommonLit - Evaluate Student Summaries
14605,137776009,1149.0,,7,28,/abhishek123maurya/fine-tuning-llm-for-scoring-llama-2,CommonLit - Evaluate Student Summaries
14606,139355145,1262.0,0.4825465303993359,0,0,/zizh3ngzhang/commonlit-inference,CommonLit - Evaluate Student Summaries
14607,139360039,1228.0,,1,39,/maverickss26/lb-0-482-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14608,139420082,1590.0,,8,37,/arviinndn/commonlit-student-summaries-debertaxlarge-rf,CommonLit - Evaluate Student Summaries
14609,138479969,1141.0,,0,5,/amirstash/extract-embeddings-text,CommonLit - Evaluate Student Summaries
14610,141302181,1250.0,,0,0,/locbaop/train-common-lit-eval-stu-sum-baseline,CommonLit - Evaluate Student Summaries
14611,146168160,1058.0,,1,12,,CommonLit - Evaluate Student Summaries
14612,139795420,1050.0,,0,5,/atamazian/cess-transformers-roberta-base-infer,CommonLit - Evaluate Student Summaries
14613,140378862,1076.0,0.4856422383178965,0,0,/atharvaingle/clt-ess-2023-hill-climbing-inference,CommonLit - Evaluate Student Summaries
14614,141326114,1107.0,0.6589185827512984,0,0,/jaloeffe92/commonlit-training,CommonLit - Evaluate Student Summaries
14615,139462352,1237.0,,1,9,/etaifour/visualize-sentences-in-2d-space,CommonLit - Evaluate Student Summaries
14616,137604724,1139.0,,0,3,/forrestluo/train-2x-t4,CommonLit - Evaluate Student Summaries
14617,139492481,1153.0,0.9257752363396954,0,2,/alesanmedvedeva/comp2-v2,CommonLit - Evaluate Student Summaries
14618,141909506,976.0,99.8246669489818,1,8,/fritzcremer/lb-probing,CommonLit - Evaluate Student Summaries
14619,151724775,1160.0,,23,69,/kevinmorgado/commonlit-summary-eda,CommonLit - Evaluate Student Summaries
14620,143262915,1337.0,0.5703200439112592,0,4,/anisharitakula/commonlit-model-deberta,CommonLit - Evaluate Student Summaries
14621,138778034,1295.0,,0,3,/unmol03/llm-v1,CommonLit - Evaluate Student Summaries
14622,144710385,1220.0,,0,13,/uygarkk/youtube-debertav3-autocorrect,CommonLit - Evaluate Student Summaries
14623,146146136,1329.0,,0,3,/yusuphmustaphaladi/implementing-fastai-tabular,CommonLit - Evaluate Student Summaries
14624,136921306,1192.0,,0,3,/akiyukikouyama/commonlit-sentencebert,CommonLit - Evaluate Student Summaries
14625,140508373,1273.0,0.8258271136400983,0,5,/thanhvu2611/t2m-first,CommonLit - Evaluate Student Summaries
14626,145819565,1355.0,0.5142954733277258,0,5,,CommonLit - Evaluate Student Summaries
14627,142273869,1368.0,0.5481335795534947,0,0,/ollyrennard/randomforests,CommonLit - Evaluate Student Summaries
14628,145821251,1315.0,0.5162671784400463,1,8,,CommonLit - Evaluate Student Summaries
14629,137979610,1227.0,,0,4,/yisberh/baseline-notebook-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14630,141384174,1661.0,0.566735599625896,0,2,/geogeolerigolo/notebook680e4a8b82,CommonLit - Evaluate Student Summaries
14631,142293438,1348.0,,0,5,/zurman/notebook-001,CommonLit - Evaluate Student Summaries
14632,136693807,1353.0,,1,8,/anthony35813/commonlit-first-look-at-the-data,CommonLit - Evaluate Student Summaries
14633,140309821,1205.0,,0,3,/wouldyoujustfocus/increase-batchsize-with-gradient-checkpoint-ddp-dp,CommonLit - Evaluate Student Summaries
14634,143437989,1419.0,,0,7,/theodorospsarras/deberta-mlskf,CommonLit - Evaluate Student Summaries
14635,143351067,1360.0,,0,0,/yuewang123/commonlit-ess-full-text-for-pseudo-labels,CommonLit - Evaluate Student Summaries
14636,145881653,1124.0,0.9850910923267272,0,1,/sridharnomulas/sridhar-nomlula-summaries,CommonLit - Evaluate Student Summaries
14637,139975519,1369.0,,6,28,/abinsingh/simple-linear-regression-5-cell-execution,CommonLit - Evaluate Student Summaries
14638,142006753,1500.0,,0,7,/dellalkhaled/outliers-detection,CommonLit - Evaluate Student Summaries
14639,141099164,1621.0,,0,1,/sumeetsawant/commonlit-evaluate-summary,CommonLit - Evaluate Student Summaries
14640,139492652,1389.0,,0,2,/dilthoms/commonlit-train,CommonLit - Evaluate Student Summaries
14641,141792577,1378.0,0.7779531000016208,0,3,/roberttrypuz/commonlit-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14642,140343393,1444.0,0.7073112515547884,0,11,/bytestorm/simple-tf-idf-xgb,CommonLit - Evaluate Student Summaries
14643,137765435,1384.0,0.6958801474715777,0,0,/paolorechia/run-pipeline,CommonLit - Evaluate Student Summaries
14644,141172126,1427.0,0.5905712238285366,34,73,/suraj520/beginner-friendly-bert,CommonLit - Evaluate Student Summaries
14645,144566105,1599.0,0.844188469952503,0,0,/pazzionon/commonlit-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14646,140251282,1447.0,,0,23,/junjitakeshima/comlit-easy-roberta-starter-eng,CommonLit - Evaluate Student Summaries
14647,142563958,1575.0,,0,2,/latticetower/commonlit-fine-tuning-with-sentencetransformers,CommonLit - Evaluate Student Summaries
14648,141280347,1533.0,,0,4,/kaggleaccount2112/commonlit-summaries-eda,CommonLit - Evaluate Student Summaries
14649,142988357,1104.0,0.8247396395051604,0,6,/j13mehul/simple-deberta-solution,CommonLit - Evaluate Student Summaries
14650,144500740,1432.0,0.6262512621387293,0,8,/arwani/predict-score-for-wording-and-content-with-rfr,CommonLit - Evaluate Student Summaries
14651,143061923,1591.0,,1,8,/jvthunder/pytorch-simple-baseline-bert-model,CommonLit - Evaluate Student Summaries
14652,143580496,1615.0,0.5997810626772058,0,0,/alexeyb/sklearn-pipeline-notebook,CommonLit - Evaluate Student Summaries
14653,143873866,1552.0,0.8507315474078692,1,3,/omrigruman/baseline-mean-on-train-set,CommonLit - Evaluate Student Summaries
14654,143266879,1638.0,,0,1,/subham07/fine-tuning-bert-score-0-58,CommonLit - Evaluate Student Summaries
14655,145025423,1399.0,0.5857708576671908,1,1,/marekm4/commonlit-mpl-simple-nlp-library-non-llm,CommonLit - Evaluate Student Summaries
14656,140434479,1739.0,1.1593724622828518,0,7,/maramalhinai/numerical-feature,CommonLit - Evaluate Student Summaries
14657,138004217,1558.0,0.6005264825002995,0,8,/dmitriygakh/commonlit-beginner-polyfit-text-size,CommonLit - Evaluate Student Summaries
14658,142467588,1631.0,0.5885741239784585,0,1,/imonefk/commonlit-regression-eda-fe-version-1,CommonLit - Evaluate Student Summaries
14659,143137062,1496.0,0.5956181135951415,4,25,/lilac07/eda-advanced-feature-engineering,CommonLit - Evaluate Student Summaries
14660,144960396,1740.0,,0,1,/ziadhamadafathy/evaluate-student-summaries-with-transformers,CommonLit - Evaluate Student Summaries
14661,141261577,1524.0,0.6018586746715304,0,2,/jbyrne/student-summaries-1,CommonLit - Evaluate Student Summaries
14662,142612558,1634.0,1.04252899115867,8,16,/neupane9sujal/sentencetransformers-starter,CommonLit - Evaluate Student Summaries
14663,145173804,1604.0,,0,0,/vinitkp/student-summaries-tensorflow,CommonLit - Evaluate Student Summaries
14664,140717654,1645.0,0.7070863865149228,0,3,/sergeychernykh/serial-experemets,CommonLit - Evaluate Student Summaries
14665,143272947,1456.0,,0,1,/mechallenge/beginner-friendly-bert,CommonLit - Evaluate Student Summaries
14666,144299617,1714.0,0.6142156141527747,0,3,/coinshot/evaluate-student-summaries-nlp-model,CommonLit - Evaluate Student Summaries
14667,145942963,1613.0,,0,1,/oleksiyshabo/homework-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14668,143495564,1543.0,,0,6,/farhanarahman82/commonlit-nltk2,CommonLit - Evaluate Student Summaries
14669,142470922,1504.0,,0,11,/alkanerturan/commonlit,CommonLit - Evaluate Student Summaries
14670,137679792,1755.0,,2,11,/michaelshekasta/eda-on-the-target,CommonLit - Evaluate Student Summaries
14671,146164021,1696.0,0.6379291428109726,0,0,/animeshagrawal23/notebookf0048ffed0,CommonLit - Evaluate Student Summaries
14672,146164021,1696.0,0.6310977942654182,0,0,/animeshagrawal23/notebookf0048ffed0,CommonLit - Evaluate Student Summaries
14673,136974220,1687.0,,0,1,/sokifukuda/notebook9d20069037,CommonLit - Evaluate Student Summaries
14674,144205452,1713.0,0.6332159977097758,0,0,/fong144/commonlit-student-summaries-evaluated,CommonLit - Evaluate Student Summaries
14675,140183390,1700.0,0.6336092813676752,12,71,/gusthema/commonlit-evaluate-student-summaries-w-tfdf,CommonLit - Evaluate Student Summaries
14676,141348673,1532.0,0.6349971984179463,0,3,/sivasankarm/distilbert-tokenizer-fine-tuning-model,CommonLit - Evaluate Student Summaries
14677,141470258,1649.0,0.6350363681259844,0,4,/onwunyichisomebi/notebook7f42ea8f2e-b95465,CommonLit - Evaluate Student Summaries
14678,141470258,1649.0,0.6356777424013687,0,4,/onwunyichisomebi/notebook7f42ea8f2e-b95465,CommonLit - Evaluate Student Summaries
14679,144173765,1741.0,,0,3,/vrivier/linear-regression-on-summary-length,CommonLit - Evaluate Student Summaries
14680,136801382,1781.0,,0,6,/bchoffin/baseline-summary-length-rf,CommonLit - Evaluate Student Summaries
14681,142640697,1805.0,1.2220757439780456,0,1,/lordxerxes/basic-tfidf-model,CommonLit - Evaluate Student Summaries
14682,137290974,1503.0,0.6623625368278576,1,6,/aliasgherman/simple-sklearn-pipeline,CommonLit - Evaluate Student Summaries
14683,143154486,1872.0,,0,3,/chezhira/students-evaluation,CommonLit - Evaluate Student Summaries
14684,143975925,1535.0,0.8755658780297664,0,3,/mohamedelmetwaly81/commonlit-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14685,144802241,1874.0,1.1989583882221646,0,4,/dosharui/trying-to-reproduce-baseline-random-forest,CommonLit - Evaluate Student Summaries
14686,148498618,1887.0,,0,0,/jeniagerasimov/nlp-iasa-course-homework-5-commonlit-transformers,CommonLit - Evaluate Student Summaries
14687,136794135,1808.0,,0,4,/dhruvkhatri/eda-commonlit-cosine-similarity,CommonLit - Evaluate Student Summaries
14688,140620721,1842.0,,0,2,/bendurham441/first-submission,CommonLit - Evaluate Student Summaries
14689,144644175,1840.0,1.4175648798127385,0,0,/ballisticrage/using-cosine-sim,CommonLit - Evaluate Student Summaries
14690,138000524,1838.0,0.7844402890316768,0,1,/harshpriye/summary-evaluation,CommonLit - Evaluate Student Summaries
14691,141380422,1970.0,2.0153960086783744,0,3,/krooz0/commonlit-lda-randomforest-baseline,CommonLit - Evaluate Student Summaries
14692,137860389,1883.0,0.8343525741599619,0,9,/christph/gzip-language-model,CommonLit - Evaluate Student Summaries
14693,137779412,1859.0,,0,1,/skylartiptpon/winning-solution-commonlit-readibility,CommonLit - Evaluate Student Summaries
14694,136916368,1929.0,0.8404421129978745,4,4,/jocelyndumlao/evaluating-and-improving-summarization-skills,CommonLit - Evaluate Student Summaries
14695,139927555,1960.0,1.2116505287236508,0,2,/mjason98/similarity-predictions,CommonLit - Evaluate Student Summaries
14696,137629911,1722.0,0.8559049282415274,0,3,/jaga360/commonlit-summarization-score-baseline,CommonLit - Evaluate Student Summaries
14697,137063495,1991.0,0.8747684421739688,0,2,/prosperalikizang/commonlit,CommonLit - Evaluate Student Summaries
14698,139716314,1869.0,0.895202022453749,0,5,/panjinhua/rf-svr,CommonLit - Evaluate Student Summaries
14699,139666916,1974.0,2.1642283249305696,0,12,/chiennguyendev/generative-adversarial-network-gan,CommonLit - Evaluate Student Summaries
14700,139666916,1974.0,1.5475740818888393,0,12,/chiennguyendev/generative-adversarial-network-gan,CommonLit - Evaluate Student Summaries
14701,139666916,1974.0,1.310776294317881,0,12,/chiennguyendev/generative-adversarial-network-gan,CommonLit - Evaluate Student Summaries
14702,142092391,1903.0,0.9366756840140832,0,8,/rajatraj0502/commonlit-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14703,141378515,2007.0,1.929658585836581,0,3,/jaberjaber/commonlit-nlp-power-with-pytorch-and-bert,CommonLit - Evaluate Student Summaries
14704,143531009,2010.0,,2,7,/pariyawan02/simplest-with-tfidf,CommonLit - Evaluate Student Summaries
14705,138115942,1995.0,,0,1,/natayakusheva/use-regression-but-through-probability,CommonLit - Evaluate Student Summaries
14706,137566570,2003.0,47.05642127772423,0,1,/vishalsinghbaraiya/notebook7e41f16424,CommonLit - Evaluate Student Summaries
14707,137566570,2003.0,47.05642127772423,0,1,/vishalsinghbaraiya/notebook7e41f16424,CommonLit - Evaluate Student Summaries
14708,144374504,2021.0,,0,0,/speedforceyt/commonlit-evaluate-student-summaries,CommonLit - Evaluate Student Summaries
14709,138362988,2019.0,1.406405821511406,3,4,/rajat95gupta/baseline-sbert-svr,CommonLit - Evaluate Student Summaries
14710,144311974,1996.0,,0,0,/nasutionizh/commonlit-evaluate-student-summaries-w-lr,CommonLit - Evaluate Student Summaries
14711,141481841,2053.0,5.128701298279581,0,4,/sathanandh/notebook4070befba0,CommonLit - Evaluate Student Summaries
14712,136801726,2059.0,20.69874633056944,2,7,/fazorglitz1/students-summary-evaluator-model,CommonLit - Evaluate Student Summaries
14713,143396153,2060.0,29.9702000202642,0,5,/amanmukati/common-lit-summaries-1,CommonLit - Evaluate Student Summaries
14714,139325565,2062.0,105.57645049200148,0,15,/golammostofas/evaluate-student-for-beginner-s,CommonLit - Evaluate Student Summaries
14715,146760769,1.0,0.3133919817123977,0,12,/tugstugi/bengali-ai-asr-competition,Bengali.AI Speech Recognition
14716,146887184,4.0,0.3534618362387385,0,0,/hanx2smile/4th-place-solution-inference-code,Bengali.AI Speech Recognition
14717,147008264,14.0,,5,5,/neilus/16th-place-solution,Bengali.AI Speech Recognition
14718,147243621,17.0,0.3598816642214828,1,2,/nyleve/giantlm-dat6-step2-at-111k-add-punctuation,Bengali.AI Speech Recognition
14719,142418381,20.0,0.4442041678885775,6,27,/snnclsr/0-444-optimize-decoding-parameters-with-optuna,Bengali.AI Speech Recognition
14720,147039276,15.0,,0,1,/slava715/w2v-bengali-1b-inference,Bengali.AI Speech Recognition
14721,146982429,24.0,0.3977205992038149,0,0,/bayartsogtya/submit-to-restore-punctuation,Bengali.AI Speech Recognition
14722,142683389,29.0,0.5794812901936993,2,1,/baohaoliao/bengali-m4t-submission,Bengali.AI Speech Recognition
14723,137178678,31.0,0.7510500525864033,8,22,/mbmmurad/submission-using-public-finetuned-whisper-model,Bengali.AI Speech Recognition
14724,154967701,37.0,,0,1,/arunodhayan/fork-of-finetuning,Bengali.AI Speech Recognition
14725,141070575,39.0,0.4973886475216724,6,88,/nischaydnk/bengali-finetuning-baseline-wav2vec2-inference,Bengali.AI Speech Recognition
14726,144553245,43.0,0.4391971769798572,6,46,/takanashihumbert/bengali-sr-wav2vec-v1-bengali-inference,Bengali.AI Speech Recognition
14727,146397589,44.0,0.4203032666637952,0,0,/yuliknormanowen/bengali-sr-wav2vec-v1-bengali-inference-for-v4,Bengali.AI Speech Recognition
14728,141896437,41.0,,0,1,/aphysict/whisper-data-prepare,Bengali.AI Speech Recognition
14729,148075844,57.0,,0,1,/aisyahhrazak/inference-wav2vec2-kenlm,Bengali.AI Speech Recognition
14730,145699292,81.0,0.438788826148264,2,32,/goelyash/bengali-ai-wave-2-vec-2,Bengali.AI Speech Recognition
14731,144847537,78.0,0.4349835847488821,0,0,/pritamsinha23/bengali-speech-kaggle-wav2vec2-v6,Bengali.AI Speech Recognition
14732,143710243,97.0,,0,5,/jonathanchan/csc494-id-last2digits-optimize-with-optuna,Bengali.AI Speech Recognition
14733,141231094,124.0,,4,12,/jjleesunny/converting-mp3-to-wav-is-an-efficient-way,Bengali.AI Speech Recognition
14734,137160979,67.0,,0,11,/umongsain/wav2vec2-n-gram-lm-inference,Bengali.AI Speech Recognition
14735,145623814,158.0,,1,17,/abhranta/4-bit-lora-whisper-large-v2-finetuning,Bengali.AI Speech Recognition
14736,137280211,271.0,,0,2,/ksmcg90/bengali-datasets-hf-hub,Bengali.AI Speech Recognition
14737,143763565,276.0,,1,29,/dangnguyen97/lb-0-443-change-the-decoding-parameters-vote-up,Bengali.AI Speech Recognition
14738,143821023,258.0,,0,2,/chaiva/submissionnotebookwithoutlm,Bengali.AI Speech Recognition
14739,138526544,242.0,0.5057450256080379,1,42,/jasonyangcode/annotation-lb-0-506-inference-w-previous,Bengali.AI Speech Recognition
14740,137083177,148.0,,0,14,/seshurajup/bengali-ai-speech-recognition-eda,Bengali.AI Speech Recognition
14741,143119877,162.0,0.4442041678885775,0,7,/royalacecat/lb-0-442-the-best-decoding-parameters,Bengali.AI Speech Recognition
14742,140238703,248.0,,0,3,/stpeteishii/bengali-one-two-word-s-mel-spectrogram,Bengali.AI Speech Recognition
14743,141230493,335.0,0.4459173951849268,0,2,/anmspro/lb-0-445-wav2vec2-inference,Bengali.AI Speech Recognition
14744,137687193,370.0,,0,0,/texopher/bengali-text-to-speech,Bengali.AI Speech Recognition
14745,144569427,376.0,0.4442041678885775,0,5,,Bengali.AI Speech Recognition
14746,147005175,382.0,0.4831552347383245,0,6,/emericjim/bengali-bnlp-for-sample,Bengali.AI Speech Recognition
14747,137616559,345.0,,0,1,/itsuki9180/hf-wav2vec2-0-preprocess-baseline,Bengali.AI Speech Recognition
14748,146917341,437.0,,1,1,/level14taken/bengali-main-pytorch,Bengali.AI Speech Recognition
14749,143632751,447.0,,0,7,/davidramos18/inference-whisper,Bengali.AI Speech Recognition
14750,145410806,454.0,,0,5,/gehrmanyu/bengaliai-datapreprocessing,Bengali.AI Speech Recognition
14751,137210579,466.0,,2,8,/hengck23/local-wer-0-2600-nemo-baseline-conformer,Bengali.AI Speech Recognition
14752,140462329,492.0,,17,99,/sujaykapadnis/bengali-speech-recognition-for-everyone,Bengali.AI Speech Recognition
14753,140455292,496.0,,2,7,/sourabhsingh03993493/speech-to-bengali,Bengali.AI Speech Recognition
14754,155869153,630.0,,0,3,/aneekeshkumar/bengali-ai-speech-recognition,Bengali.AI Speech Recognition
14755,139546898,633.0,0.5057450256080379,0,3,/rameezraja1/annotation-lb-0-506-inference-w-previous,Bengali.AI Speech Recognition
14756,137162907,536.0,0.5087868493128606,5,77,/reasat/yellowking-dlsprint-inference,Bengali.AI Speech Recognition
14757,139445917,577.0,0.5087868493128606,0,3,/fazorglitz1/yellowking-dlsprint-inference,Bengali.AI Speech Recognition
14758,139445917,577.0,0.5087868493128606,0,3,/fazorglitz1/yellowking-dlsprint-inference,Bengali.AI Speech Recognition
14759,145164436,659.0,,0,5,/msthil/bengali-data-augmentation,Bengali.AI Speech Recognition
14760,146813846,699.0,0.7027842708364423,0,1,/saeidehmousavi/bengali-competition-notebook,Bengali.AI Speech Recognition
14761,137129768,722.0,,3,21,/pjmathematician/bengaliai-asr-baseline-whisper-inference,Bengali.AI Speech Recognition
14762,140495042,732.0,,0,1,/seydifaye/create-vocabulary-words-pieces-vocabulary,Bengali.AI Speech Recognition
14763,139719647,2.0,,12,91,/theoviel/get-started-quicker-dicom-png-conversion,RSNA 2023 Abdominal Trauma Detection
14764,146675749,1.0,0.35241877371944,1,7,/nischaydnk/rsna-super-mega-lb-ensemble,RSNA 2023 Abdominal Trauma Detection
14765,147650003,7.0,0.4024434288575029,0,0,/hongx0615/rsna-2023-7th-place-solution-inference,RSNA 2023 Abdominal Trauma Detection
14766,147146851,10.0,,0,3,/ren4yu/rsna2023-align-two-voxels,RSNA 2023 Abdominal Trauma Detection
14767,141973649,40.0,,1,2,/yutoshimomura/rsna-2023-atd-segmentation-eda,RSNA 2023 Abdominal Trauma Detection
14768,140504512,55.0,0.8739992758609293,0,9,/north344/resample-with-simpleitk-for-test-set,RSNA 2023 Abdominal Trauma Detection
14769,143005656,79.0,,0,0,/chrisrichardmiles/rsna-ab-trauma-eda,RSNA 2023 Abdominal Trauma Detection
14770,138526156,92.0,0.6854238479069186,0,18,/jasonyangcode/annotation-rsna23-weighted-mean-baseline,RSNA 2023 Abdominal Trauma Detection
14771,138167094,94.0,,0,9,/yeonghyeon/rsna23-easy-dicom-confirmation-volume-generation,RSNA 2023 Abdominal Trauma Detection
14772,146733149,731.0,,0,9,/raki21/faulty-any-injury-in-metric-demonstration,RSNA 2023 Abdominal Trauma Detection
14773,141749718,243.0,,1,3,/greysky/rsna-segmentation,RSNA 2023 Abdominal Trauma Detection
14774,141735458,397.0,,0,10,/satyaprakashshukl/eda-abdominal-detection,RSNA 2023 Abdominal Trauma Detection
14775,145011853,535.0,,0,2,/krsushantsk/rsna-abdominal-trauma-detection-train,RSNA 2023 Abdominal Trauma Detection
14776,145492181,553.0,0.6536168447009375,17,79,/jasonheesanglee/rsna23-scale-h-implementation,RSNA 2023 Abdominal Trauma Detection
14777,147641990,330.0,,2,14,/joebeachcapital/rsna-eda-starter,RSNA 2023 Abdominal Trauma Detection
14778,144981355,570.0,,0,0,/arkadiptachatterjee/kerascv-starter-notebook-infer,RSNA 2023 Abdominal Trauma Detection
14779,146517664,378.0,,2,14,/dangnguyen97/lb-0-66-change-sf,RSNA 2023 Abdominal Trauma Detection
14780,144527381,362.0,0.7511271897856843,0,10,/lidiashishina/rsna23-weighted-mean-baseline-scale-adj-at-end,RSNA 2023 Abdominal Trauma Detection
14781,145163107,792.0,,0,0,/chenboluo/rsna-training,RSNA 2023 Abdominal Trauma Detection
14782,139693409,406.0,,1,13,/sreekanthpolu/rsna-2023-abdominal-trauma-detection,RSNA 2023 Abdominal Trauma Detection
14783,145170645,608.0,1.3558760975543398,5,4,/sanghyunlee94/rsna-2-5d-cnn-inference-pytorch,RSNA 2023 Abdominal Trauma Detection
14784,144093239,222.0,0.6556548487241974,0,13,/satheeshbhukya1/abdominal-trauma,RSNA 2023 Abdominal Trauma Detection
14785,144546801,101.0,,1,8,/ueight8/cnn-road-map,RSNA 2023 Abdominal Trauma Detection
14786,143445074,773.0,0.9574870558588398,0,1,/mirenaborisova/rsna-1,RSNA 2023 Abdominal Trauma Detection
14787,142630762,224.0,0.6553774441584538,0,0,/limamateus/rsna-other-parameters,RSNA 2023 Abdominal Trauma Detection
14788,142010269,237.0,,1,20,/noir3747/rsna-v1,RSNA 2023 Abdominal Trauma Detection
14789,141189937,238.0,,2,15,/juliengenzling/rnsa2023-complete-eda,RSNA 2023 Abdominal Trauma Detection
14790,141350063,244.0,0.7192452480934216,0,0,/jaimecastillo/local-overfit-search-baseline,RSNA 2023 Abdominal Trauma Detection
14791,145430726,348.0,0.9755460789216138,1,10,/amanmukati/rsna-abdominal-2023,RSNA 2023 Abdominal Trauma Detection
14792,142698432,279.0,,0,0,/lwr6608/rsna-2023,RSNA 2023 Abdominal Trauma Detection
14793,140520599,354.0,,0,6,/shangjianzhong/extract-data-with-segmentation,RSNA 2023 Abdominal Trauma Detection
14794,140211550,312.0,,2,11,/kensomeya/dicom-to-3dnumpy,RSNA 2023 Abdominal Trauma Detection
14795,145982832,338.0,,0,3,/ataracsia/rsna-atd-convnextv2-tiny-1k-224,RSNA 2023 Abdominal Trauma Detection
14796,141019118,368.0,,0,1,/pcjimmmy/rsna-submission-pc-jimmmy,RSNA 2023 Abdominal Trauma Detection
14797,144126859,95.0,,0,2,/glipko/rsna-volumes-128x64x64,RSNA 2023 Abdominal Trauma Detection
14798,144466563,519.0,,0,3,/noam1977/resizing-dicom,RSNA 2023 Abdominal Trauma Detection
14799,143404215,106.0,,0,6,/rickpack/rsna23-weighted-mean-baseline-scale-adj-at-end,RSNA 2023 Abdominal Trauma Detection
14800,141220796,755.0,,0,1,/jina3784/kaggle-test,RSNA 2023 Abdominal Trauma Detection
14801,141782120,425.0,,0,3,/neerajkaroshi/rsna-train-keras-yolov8,RSNA 2023 Abdominal Trauma Detection
14802,142872088,750.0,0.8132621367043983,0,1,/rickylu/rsna2023-abd-infer-3dcnn,RSNA 2023 Abdominal Trauma Detection
14803,147279939,439.0,,0,0,/alejandrolunamtz/inference-rsna-atd-fv,RSNA 2023 Abdominal Trauma Detection
14804,141821423,453.0,0.6670803550117629,0,0,/anmspro/rsna-0-66-lb,RSNA 2023 Abdominal Trauma Detection
14805,142551845,479.0,,0,0,/maxsemakov/totalsegmentator-offline-work,RSNA 2023 Abdominal Trauma Detection
14806,138964121,398.0,,29,79,/parhammostame/construct-3d-arrays-from-dcm-nii-3-view-angles,RSNA 2023 Abdominal Trauma Detection
14807,138511797,123.0,,0,13,/b11gden/rsna-2023-segmentation-visualization-with-plotly,RSNA 2023 Abdominal Trauma Detection
14808,138342146,125.0,0.6757024331479551,1,22,/vishakkbhat/rsna23-weighted-mean-baseline,RSNA 2023 Abdominal Trauma Detection
14809,138302991,400.0,,2,48,/jakebrusca/rsna23-weighted-mean-baseline,RSNA 2023 Abdominal Trauma Detection
14810,138212318,743.0,,2,15,/franklinshih0617/rsna-abdominal-trauma-detect-eda-animation,RSNA 2023 Abdominal Trauma Detection
14811,140330244,748.0,,1,5,/harsha1999/eda-with-3d-visualization,RSNA 2023 Abdominal Trauma Detection
14812,141316459,753.0,,0,1,/finlay/rsna-training,RSNA 2023 Abdominal Trauma Detection
14813,141471524,538.0,,0,2,/llleeeoooh/rsna-atd-2023-data-preprocess,RSNA 2023 Abdominal Trauma Detection
14814,145091077,779.0,,0,1,/pankajpansari/baseline-1-2d-cnn-image-level-prediction-train,RSNA 2023 Abdominal Trauma Detection
14815,146999506,800.0,,0,0,/ashery/rsna-2023-abdominal-trauma-detection-training,RSNA 2023 Abdominal Trauma Detection
14816,146222136,824.0,,0,4,/lanzy007/rsna-abdominal-injury-classification,RSNA 2023 Abdominal Trauma Detection
14817,144166481,816.0,,0,0,/xiaozhiren/kerascv-starter-notebook-train,RSNA 2023 Abdominal Trauma Detection
14818,147696464,856.0,3.9642307665943206,0,0,/tyjh22005/resnet-infer,RSNA 2023 Abdominal Trauma Detection
14819,139389776,854.0,,3,17,/victorshlepov/1st-step-to-3d-eda-and-dicom-to-nifti-transform,RSNA 2023 Abdominal Trauma Detection
14820,139767388,884.0,,0,2,/johnsonchishimba/rsna-atd-2023-eda,RSNA 2023 Abdominal Trauma Detection
14821,141495049,971.0,,0,1,/gabrielrudloff/rsna-atd-512x512-png-cropped,RSNA 2023 Abdominal Trauma Detection
14822,145485709,968.0,,0,2,/noelyoda/fork-of-dr-oi-model-w-h5,RSNA 2023 Abdominal Trauma Detection
14823,139949842,927.0,,0,2,/chauyh/rsna-shape-2-3-fail,RSNA 2023 Abdominal Trauma Detection
14824,140497488,936.0,,1,7,/arminajdehnia/rsna-2023-deep-insight-tfx,RSNA 2023 Abdominal Trauma Detection
14825,140364290,944.0,,0,5,/hemanthhari/rsna-dcm-to-png,RSNA 2023 Abdominal Trauma Detection
14826,138687134,960.0,,0,5,/vinitkp/rsna-trauma-detection,RSNA 2023 Abdominal Trauma Detection
14827,139048001,964.0,,0,6,/stpeteishii/abdominal-trauma-dicom-image-type-classify,RSNA 2023 Abdominal Trauma Detection
14828,145339276,980.0,0.9511084003150287,0,2,/sarashahin/rsna-2023-abdominal-trauma-detection,RSNA 2023 Abdominal Trauma Detection
14829,141996771,984.0,,0,6,/artemzapara/rsna-2023-abdominal-trauma-detection-eda,RSNA 2023 Abdominal Trauma Detection
14830,146515142,1001.0,,0,2,/johnycoder/rsna-make-dataset-segmentation,RSNA 2023 Abdominal Trauma Detection
14831,151766078,1027.0,,0,0,/soollv/notebook325f4ffcae,RSNA 2023 Abdominal Trauma Detection
14832,146272985,1069.0,,2,1,/magnussesodia/exploring-kerascv-for-rsna-trauma,RSNA 2023 Abdominal Trauma Detection
14833,139177640,1076.0,,0,17,/aritrag/eda-train-csv,RSNA 2023 Abdominal Trauma Detection
14834,141879823,1110.0,12.648955091547512,0,0,/zhiyiho/kerascv-starter-notebook-infer,RSNA 2023 Abdominal Trauma Detection
14835,143851901,1124.0,,2,20,/j2letters/rsna-2023-eda,RSNA 2023 Abdominal Trauma Detection
14836,140041773,113.0,,14,64,/patrick0302/clustering-might-help,Predict CO2 Emissions in Rwanda
14837,140355540,15.0,,1,3,/wentinglu/more-adjustment,Predict CO2 Emissions in Rwanda
14838,140619131,232.0,,0,4,/tesnimglen/pse320-last-minute-predictions-for-rwanda,Predict CO2 Emissions in Rwanda
14839,139290622,144.0,23.022316965184864,15,51,/danbraswell/no-ml-public-lb-23-02231,Predict CO2 Emissions in Rwanda
14840,140329000,185.0,23.35768787402034,47,107,/kacperrabczewski/rwanda-co2-step-by-step-guide,Predict CO2 Emissions in Rwanda
14841,140249813,151.0,20.54111440478152,1,8,/anilreddyvv/simple-20-54111pb,Predict CO2 Emissions in Rwanda
14842,145415021,193.0,,11,83,/yaaangzhou/pg-s3-e20-eda-modeling,Predict CO2 Emissions in Rwanda
14843,139561529,25.0,,7,15,/johnsmith44/ps3e20-co2-emissions-in-rwanda-compact-trick,Predict CO2 Emissions in Rwanda
14844,140303844,208.0,,12,32,/javohirtoshqorgonov/predict-co2-emission-in-rwanda,Predict CO2 Emissions in Rwanda
14845,139219248,206.0,,0,10,/rishabh15virgo/s3e20-eda-findings-baseline-exponential-smoothing,Predict CO2 Emissions in Rwanda
14846,140603970,220.0,,0,3,/mehdicherif/predict-co2-emission-using-lgbm,Predict CO2 Emissions in Rwanda
14847,140622795,222.0,,0,5,/muhriddinmalik/easiest-solution-using-math-with-visualisation,Predict CO2 Emissions in Rwanda
14848,139079968,145.0,28.61399782519096,2,14,/bassemgouty/ps3e20-ensembling-with-score-nudge,Predict CO2 Emissions in Rwanda
14849,140200775,147.0,23.022316965184864,0,5,/pixelshooter/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14850,139567564,125.0,21.88798030492164,0,2,/lucasbruzzone/playground-series-s3e20-study,Predict CO2 Emissions in Rwanda
14851,149364745,124.0,,0,1,/leonliur/rwanda-co2-prediction-lb-9,Predict CO2 Emissions in Rwanda
14852,139944429,290.0,,6,8,/aaachen/ps3e20-xgboost-lgbm,Predict CO2 Emissions in Rwanda
14853,140594236,212.0,18.73702551650321,2,13,/shivampandit/co2-prediction-best-result-18-6,Predict CO2 Emissions in Rwanda
14854,138637230,138.0,31.36873646001424,0,11,/nivedithavudayagiri/co2-emissions-eda-fe-submission-wip,Predict CO2 Emissions in Rwanda
14855,140250012,217.0,,0,9,/adhoppin/predict-co2-emissions-gradient-boosting,Predict CO2 Emissions in Rwanda
14856,139339392,219.0,,0,6,/pembekanton/effective-sample-baseline,Predict CO2 Emissions in Rwanda
14857,139512330,215.0,40.048965495296365,0,6,/szulky/a-lightgbm-model-with-score-40,Predict CO2 Emissions in Rwanda
14858,138616927,282.0,,0,7,/joemedley/index-data-with-random-forests,Predict CO2 Emissions in Rwanda
14859,140679554,143.0,21.724817919023742,0,8,/roberttrypuz/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14860,139618283,323.0,41.80460650585316,0,2,/shubhamgupta012/xgboostregressor,Predict CO2 Emissions in Rwanda
14861,138830983,325.0,168.27715577018137,0,6,/priyamsaha17/predict-co2-emissions-in-rwanda-using-autogluon,Predict CO2 Emissions in Rwanda
14862,140083240,327.0,23.022316965184864,1,8,/jbm1966/no-ml-from-python-to-r,Predict CO2 Emissions in Rwanda
14863,138685495,417.0,180.84604259715923,0,4,/yunsuxiaozi/pss3e20-baseline-lightgbm,Predict CO2 Emissions in Rwanda
14864,139967737,422.0,,0,2,/mohammadaquib02/rawanda-co2-emissions-prediction-challenge,Predict CO2 Emissions in Rwanda
14865,139589609,404.0,,20,76,/iqbalsyahakbar/ps3e20-time-series-for-beginners,Predict CO2 Emissions in Rwanda
14866,138797177,345.0,,0,2,/loki4514/pss3e20-eda,Predict CO2 Emissions in Rwanda
14867,140202284,382.0,,6,11,/ansh0072/ps3e20-regressormodels-eda-submission,Predict CO2 Emissions in Rwanda
14868,140641678,94.0,,4,18,/alvinleenh/11-98-private-s3e20-rf-ensemble,Predict CO2 Emissions in Rwanda
14869,143450162,318.0,,0,2,/dbzadnen/predict-co2-emissions-in-rwanda-multivariate-ts,Predict CO2 Emissions in Rwanda
14870,144139379,301.0,,4,8,/loikloikl/ploty-animated-map-of-emission,Predict CO2 Emissions in Rwanda
14871,140695541,1202.0,,0,4,/kzz1056/eda-quick-model,Predict CO2 Emissions in Rwanda
14872,139499071,139.0,,1,1,/stevesimons/query-your-pandas-dataframes-with-fuguesql,Predict CO2 Emissions in Rwanda
14873,138731384,242.0,,0,4,/indropal/pss3e20-preview-emission-pattern-time-series,Predict CO2 Emissions in Rwanda
14874,139444557,403.0,169.1937454306304,1,7,/artificialmindset/first-attempt,Predict CO2 Emissions in Rwanda
14875,139970017,110.0,29.78210971424766,1,2,/trhgquan/ps3e20,Predict CO2 Emissions in Rwanda
14876,139211723,420.0,,2,19,/docxian/ps-s3-e20-co2-emissions-deep-dive,Predict CO2 Emissions in Rwanda
14877,142016257,103.0,,2,5,/fredrickkariuki/predict-co2-emission-in-rwanda,Predict CO2 Emissions in Rwanda
14878,138546963,348.0,40.51445703166879,0,5,/chiranjeevisrinivas/playground-series-s3e20-automl,Predict CO2 Emissions in Rwanda
14879,140523686,3.0,25.361492557903222,3,15,/xuebinjiang/s3e20-random-forest-model,Predict CO2 Emissions in Rwanda
14880,140602150,467.0,27.80325513974393,3,19,/jimgruman/co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14881,139967213,18.0,,2,9,/omkarkhade7/co2-emissions-in-rwanda-prediction-using-ann,Predict CO2 Emissions in Rwanda
14882,140694444,40.0,,0,4,/ajatix/40th-parallel-processing-using-prophet,Predict CO2 Emissions in Rwanda
14883,140641001,55.0,,0,2,/jackchengjianzhu/rwanda-co2-combine-predictions-from-multiple,Predict CO2 Emissions in Rwanda
14884,140644852,58.0,26.107497078895985,0,5,/yapwh1208/playground-s3e20-rf,Predict CO2 Emissions in Rwanda
14885,140212766,333.0,26.175496775806,0,9,/viji1609/pgs3-e20-diluted-convolution-model,Predict CO2 Emissions in Rwanda
14886,139752198,32.0,29.38253201369323,0,5,/mohdph/predicting-rawanda-s-co2-emission-by-random-forest,Predict CO2 Emissions in Rwanda
14887,140278708,85.0,26.78787121564089,0,5,/hidetaketakahashi/geospatial-analysis-of-gas-emission-in-rwanda,Predict CO2 Emissions in Rwanda
14888,140551148,653.0,,2,8,/sho124/predict-co2-emissions-with-lightgbm,Predict CO2 Emissions in Rwanda
14889,140898295,84.0,,4,8,/ahana09/ps-s3e20-eda-rabdomforest,Predict CO2 Emissions in Rwanda
14890,139315953,97.0,27.43720383265916,0,2,/cheekati1/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14891,139413697,257.0,29.404253940358693,0,6,/yudavid/eng-kor-from-preprocessing-to-modeling,Predict CO2 Emissions in Rwanda
14892,140569243,37.0,27.48819156493994,9,27,/nazimcherpanov/prediction-emissions-in-rwanda-using-lgbm,Predict CO2 Emissions in Rwanda
14893,139917651,624.0,,0,6,/martincampbell/using-seasonality,Predict CO2 Emissions in Rwanda
14894,139267897,140.0,32.38593528425072,0,1,/amaliavr/s3e20-first-steps-explore-submit,Predict CO2 Emissions in Rwanda
14895,138670176,126.0,29.93085227435993,0,8,/lucasboesen/simple-catboost-6-features-cv-21-7,Predict CO2 Emissions in Rwanda
14896,138894636,460.0,30.24376080301958,8,21,/utkarshx27/co2-emissions-eda-pred,Predict CO2 Emissions in Rwanda
14897,139919601,678.0,,0,5,/khaledabdelgaber/co2-competition,Predict CO2 Emissions in Rwanda
14898,140201264,243.0,,0,7,/coronatianmao/ps3e20-carbon-emission-analysis,Predict CO2 Emissions in Rwanda
14899,139897902,50.0,,0,2,/michaszymaski/cross-validating-time-series-data,Predict CO2 Emissions in Rwanda
14900,140475117,239.0,29.61901435854088,1,8,/adelinmil/co2-emission-ts-notebook-lb-score-29-6,Predict CO2 Emissions in Rwanda
14901,138668814,604.0,32.03082223464848,0,9,/cozyhn/autogluon-co2-emissions-in-rwanda-pg-series,Predict CO2 Emissions in Rwanda
14902,139852772,506.0,29.85857294579969,0,2,/geraldnyeo/ps3e20-eda-fe-baseline,Predict CO2 Emissions in Rwanda
14903,140081410,517.0,,0,11,/ahmedanwar89/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14904,139475890,14.0,168.02958724249154,2,14,/averma111/pytorch-ps3e20,Predict CO2 Emissions in Rwanda
14905,139973307,509.0,30.07092493585242,0,1,/satyamkathait/notebook179be1986f,Predict CO2 Emissions in Rwanda
14906,139189183,446.0,30.11850047254152,0,3,/benigmatic/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14907,138548151,531.0,,2,7,/akiyukikouyama/ps3e20-eda-and-build-baseline,Predict CO2 Emissions in Rwanda
14908,138798730,508.0,,0,1,/kukazucker/co2-emissions-notebook,Predict CO2 Emissions in Rwanda
14909,140510245,539.0,,4,11,/aranpandey/rwanda-co2-eda-rf-preds,Predict CO2 Emissions in Rwanda
14910,140592911,603.0,30.454116265500275,0,4,/alirezajavid1999/predict-co2-emissions-in-rwanda-using-ml-algorithm,Predict CO2 Emissions in Rwanda
14911,139016887,595.0,30.51811054733928,0,16,/cybersimar08/co2-emission-eda-random-forest,Predict CO2 Emissions in Rwanda
14912,139077898,600.0,,0,3,/mridul2003/eda-co2-emission,Predict CO2 Emissions in Rwanda
14913,140607479,497.0,,16,27,/debamritapaul/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14914,140356092,394.0,30.561815448422767,0,1,/danishelahi/carbon-emission,Predict CO2 Emissions in Rwanda
14915,140356092,394.0,30.561815448422767,0,1,/danishelahi/carbon-emission,Predict CO2 Emissions in Rwanda
14916,141179846,596.0,,6,9,/muthumeenakshi11/prediction-of-co2-using-xgb-regressor,Predict CO2 Emissions in Rwanda
14917,139072854,507.0,30.9453220719502,0,2,/alexkalita/simple-xgboost-fe-optuna,Predict CO2 Emissions in Rwanda
14918,140373708,584.0,30.81565753805,0,1,/shaunakmandal/co2-emission-model,Predict CO2 Emissions in Rwanda
14919,140279981,633.0,30.87544697935118,0,3,/christph/h2o-automl,Predict CO2 Emissions in Rwanda
14920,138537820,511.0,51.78350950076978,0,4,/harshavardhanbabu/catboost-model-beating-baseline,Predict CO2 Emissions in Rwanda
14921,140620675,725.0,,0,6,/radbear/using-tensorflow-for-playground-series-3-20,Predict CO2 Emissions in Rwanda
14922,140319708,472.0,,1,3,/acdundore/s3-e20-eda-imputation-arima,Predict CO2 Emissions in Rwanda
14923,138909673,605.0,,0,7,/kamrantanwari/basic-feature-engineering-and-tf-baseline,Predict CO2 Emissions in Rwanda
14924,138803142,456.0,,1,7,/ashishjagdishsharma/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14925,138574420,452.0,47.182046508499226,3,7,/masarusan/s3e20-beginner-just-using-kaggle-learn-knowledge,Predict CO2 Emissions in Rwanda
14926,138843533,617.0,31.626031151517925,2,16,/kkuri00/s3e20-simple-eda-xgboost-model,Predict CO2 Emissions in Rwanda
14927,140573332,659.0,,0,3,/matasferrn/rwanda-co2-emissions,Predict CO2 Emissions in Rwanda
14928,150554377,652.0,,0,12,/nikhil1e9/s3-e20-eda-fe-modeling,Predict CO2 Emissions in Rwanda
14929,139578544,414.0,,4,26,/akioonodera/ps-3-20-lgbm-reg,Predict CO2 Emissions in Rwanda
14930,139901827,526.0,33.49344533316754,0,6,/suharshmahajan/co2-emission-prediction,Predict CO2 Emissions in Rwanda
14931,139077244,703.0,,0,7,/dishaasinghi/playground-s3e20-co2-emission,Predict CO2 Emissions in Rwanda
14932,140676840,501.0,,0,2,/bibhumohapatra18/rwanda-co2-predictions,Predict CO2 Emissions in Rwanda
14933,140356549,523.0,,3,17,/antimoni/co2-emission-model,Predict CO2 Emissions in Rwanda
14934,140582800,541.0,,0,2,/kidkrinkles/s3e20-random-forest-c02-emissions-submission,Predict CO2 Emissions in Rwanda
14935,152410474,696.0,,3,13,/sjagkoo7/predict-co2-emissions-s3ep20,Predict CO2 Emissions in Rwanda
14936,140560571,683.0,,0,3,/suvammistry/ps-s03e20-work-in-progress,Predict CO2 Emissions in Rwanda
14937,139096763,684.0,,0,2,/deshram/baseline-submission-time-series-carbon-emission,Predict CO2 Emissions in Rwanda
14938,139966847,535.0,33.389583566528934,0,4,/atuljo/simple-model-to-start-2,Predict CO2 Emissions in Rwanda
14939,139226224,510.0,33.38965345870224,2,12,/camillechurch/simple-model-randomforest,Predict CO2 Emissions in Rwanda
14940,138739174,592.0,,1,9,/edwardhuangtw/ps-s3e20-eda,Predict CO2 Emissions in Rwanda
14941,138739723,704.0,,0,3,/stpeteishii/pss3-ep20-emission-change,Predict CO2 Emissions in Rwanda
14942,139735161,712.0,,0,0,/gitashojaee/co2-emissions-in-rwanda-histgradientboosting,Predict CO2 Emissions in Rwanda
14943,140008674,462.0,34.02588824570951,0,9,/coinshot/co2-emission-model,Predict CO2 Emissions in Rwanda
14944,141127735,713.0,,1,4,/atom1991/predict-co2-emissions-in-rwanda-ps-s3e20,Predict CO2 Emissions in Rwanda
14945,138558784,802.0,,6,13,/salazhiev/easy-for-beginners-37-31299,Predict CO2 Emissions in Rwanda
14946,140588946,593.0,34.756252386817685,1,8,/ashx010/ps3e20-eda-fe-ml-model,Predict CO2 Emissions in Rwanda
14947,140638531,727.0,,0,1,/rautaishwarya/co2-emission-prediction,Predict CO2 Emissions in Rwanda
14948,140543418,601.0,35.47820478916024,0,3,/neupane9sujal/rwanda-co2-prediction-xgb-baseline,Predict CO2 Emissions in Rwanda
14949,139417532,801.0,,0,9,/mexwell/ps3e20-eda-cluster-lightgbm,Predict CO2 Emissions in Rwanda
14950,139662992,720.0,35.89985482219285,1,7,/christophercoffee/feature-engineering-using-tabpfn,Predict CO2 Emissions in Rwanda
14951,140481203,488.0,,0,5,/valentinbelyaev/feature-selection-rf-xgboost,Predict CO2 Emissions in Rwanda
14952,139528267,965.0,37.82877869097974,0,8,/sainikhil26/eda-with-ensemble-model-hypertuning,Predict CO2 Emissions in Rwanda
14953,140214704,655.0,36.32021225912354,0,6,/bcscuwe1/co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14954,148565504,464.0,,0,2,/akekowsik/co2-prediction2,Predict CO2 Emissions in Rwanda
14955,139872595,961.0,36.89186332812896,1,4,/kagankoral/ps-s03e20-rwanda-co2-emission-eda-model,Predict CO2 Emissions in Rwanda
14956,140568320,716.0,133.96785464902106,1,23,/abhashrai/predicting-co2-emissions-ps-s3e20,Predict CO2 Emissions in Rwanda
14957,140308026,1019.0,44.63937645095697,0,4,/apovidlo/ts-forecasting-with-fedot-automl,Predict CO2 Emissions in Rwanda
14958,138530184,787.0,,2,8,/gauravduttakiit/pss3e20-lazypredict,Predict CO2 Emissions in Rwanda
14959,147984460,711.0,,0,1,/mohammadbolandraftar/pycaret-the-power-of-low-code-machine-learning,Predict CO2 Emissions in Rwanda
14960,140132008,777.0,,6,30,/taeefnajib/eda-of-co2-emission,Predict CO2 Emissions in Rwanda
14961,140018624,750.0,,0,6,/enesaltun/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14962,140373001,979.0,39.774934542262336,0,1,/nullifi3d/rwanda-co2-predictions-using-xgboost,Predict CO2 Emissions in Rwanda
14963,140373001,979.0,39.774934542262336,0,1,/nullifi3d/rwanda-co2-predictions-using-xgboost,Predict CO2 Emissions in Rwanda
14964,138667212,788.0,176.9527788653805,0,3,/thomasmeiner/ps3e20-lstm-on-differentiation-residuals,Predict CO2 Emissions in Rwanda
14965,138707347,775.0,,0,9,/iqmansingh/co2-emission-optuna-xgb-lgbm,Predict CO2 Emissions in Rwanda
14966,138651735,753.0,,0,3,/anuragmuk/simple-catboost,Predict CO2 Emissions in Rwanda
14967,139952548,939.0,,0,9,/vladislavonufrienko/ps3e20-eda-randomforestregressor,Predict CO2 Emissions in Rwanda
14968,138753380,810.0,,2,12,/lyxbash/random-forest-correlation-matrix-co2-emissions,Predict CO2 Emissions in Rwanda
14969,139671248,832.0,45.241909242998936,0,5,/prathameshprege/ps-s3-e20-co2-emissions-rwanda-xgb-model,Predict CO2 Emissions in Rwanda
14970,139525432,1025.0,,1,9,/samu2505/carbon-eda-fe-cv,Predict CO2 Emissions in Rwanda
14971,140310607,792.0,134.93383998260765,0,4,/catadanna/tab-s3-e20,Predict CO2 Emissions in Rwanda
14972,162576210,865.0,,0,1,/vinodkumargurjar/ai-ml-predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14973,140198358,803.0,,0,6,/hardikonds/co2-emmisions,Predict CO2 Emissions in Rwanda
14974,140498699,1092.0,,0,6,/mariabistro/predicting-co2-emissions-n-hits,Predict CO2 Emissions in Rwanda
14975,140544882,823.0,41.29640410189307,0,2,/somboonpradit/predict-co2-emission-beginner,Predict CO2 Emissions in Rwanda
14976,139906358,1039.0,41.566814404496775,3,15,/klaidenx/s3-e3-co2-emission,Predict CO2 Emissions in Rwanda
14977,138820734,885.0,49.17592927714077,0,1,/manohar77/co2-emission-simple-approach,Predict CO2 Emissions in Rwanda
14978,140200810,789.0,920.397507348108,0,9,/imonefk/s3e20-lstm-starter-notebook-for-hyperparam-tuning,Predict CO2 Emissions in Rwanda
14979,140090864,1005.0,41.62679876563471,0,1,/abdelrhmandemo/predict-co2-v1,Predict CO2 Emissions in Rwanda
14980,140324657,861.0,148.87180097122732,12,17,/suraj520/voting-ensemble-multiple-approaches,Predict CO2 Emissions in Rwanda
14981,140476908,876.0,46.77364100543323,0,0,/mohammadabdelhalim/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14982,140168448,822.0,41.97536132665074,1,6,/thefortunetellers/short-and-simple-co2-notebook,Predict CO2 Emissions in Rwanda
14983,139825778,912.0,,0,4,/muratgulcan/rawanda-co2-emissions-prediction,Predict CO2 Emissions in Rwanda
14984,140883734,904.0,,0,9,/harshitkumarsaxena1/predction-co2-by-random-forest,Predict CO2 Emissions in Rwanda
14985,140311303,1014.0,42.426149969592885,0,10,/sagorkumarmitra/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
14986,140103137,883.0,,0,4,/phanendrasairam/s3e20-co2-emission,Predict CO2 Emissions in Rwanda
14987,139819921,901.0,42.69871694544067,0,4,/manavgupta92/s3e20-rwanda-eda-that-can-improve-your-rank,Predict CO2 Emissions in Rwanda
14988,140385977,919.0,,0,3,/priya2701/co2-emissions-prediction-in-rwanda,Predict CO2 Emissions in Rwanda
14989,140490632,936.0,,0,6,/muhannadmansour/eda-voting-randomforest-xgboost-catboost,Predict CO2 Emissions in Rwanda
14990,140007521,1000.0,46.837150721922605,0,5,/johnzhuoliu/simple-steps-for-co2-emission-prediction,Predict CO2 Emissions in Rwanda
14991,140007521,1000.0,46.837150721922605,0,5,/johnzhuoliu/simple-steps-for-co2-emission-prediction,Predict CO2 Emissions in Rwanda
14992,139722722,1127.0,,0,1,/johnycooly/co2-emission-plotly-et-shape,Predict CO2 Emissions in Rwanda
14993,140409921,1034.0,48.16376414237806,0,3,/kuryakin/predict-co2-xgboost-for-default-dataset,Predict CO2 Emissions in Rwanda
14994,138929844,986.0,45.7766604597691,0,1,/viviansam/co2-emissions-random-forest-regressor,Predict CO2 Emissions in Rwanda
14995,140441521,909.0,172.16958109480078,0,5,/kimijima/xgboost-for-ml-and-missing-value-imputation,Predict CO2 Emissions in Rwanda
14996,139099325,1051.0,,0,6,/tuhinm2002/predict-co2-emissions-in-rwanda-simple-solution,Predict CO2 Emissions in Rwanda
14997,140512075,1098.0,50.79145296032759,0,1,/vibe95/predict-co2-in-rwanda,Predict CO2 Emissions in Rwanda
14998,139816330,1096.0,46.9671828732042,0,7,/rajeevbhadola/predict-co2-emissions-in-rwanda-rb,Predict CO2 Emissions in Rwanda
14999,138604270,1120.0,,0,6,/mirabirhossain/first-look-map-visualize-train-valid-split-etc,Predict CO2 Emissions in Rwanda
15000,140125613,959.0,48.07847026454999,0,9,/golammostofas/predict-co2-emissions-for-beginners,Predict CO2 Emissions in Rwanda
15001,139371448,1067.0,48.16376393373191,0,2,/jiprud/simple-submission,Predict CO2 Emissions in Rwanda
15002,138867770,1116.0,,0,11,/warriorwizard/ps3e20-co2-emission,Predict CO2 Emissions in Rwanda
15003,140218392,1001.0,50.47993942297303,1,6,/kotukw/co2-emissions-in-rwanda-using-xgboost,Predict CO2 Emissions in Rwanda
15004,140575949,1113.0,,0,5,/smilikasangam/co2-emission-eda,Predict CO2 Emissions in Rwanda
15005,138614913,1158.0,,7,30,/sujaykapadnis/interactive-eda-w-plotly,Predict CO2 Emissions in Rwanda
15006,139710902,1141.0,52.403721414947775,0,5,/robertturro/rf-xgboost-pipeline-with-optuna,Predict CO2 Emissions in Rwanda
15007,139718517,1089.0,52.6414657913464,0,0,/narendrati/narendra-emission-predict,Predict CO2 Emissions in Rwanda
15008,138679703,1152.0,54.75903751722215,1,19,/kim145/first-cut-xgboost,Predict CO2 Emissions in Rwanda
15009,138747019,1153.0,54.75903751722215,0,5,/abhinavkimothi/first-cut-xgboost,Predict CO2 Emissions in Rwanda
15010,140222432,1164.0,,0,0,/sebastiantarebustos/co2emissions,Predict CO2 Emissions in Rwanda
15011,140072295,1058.0,,0,3,/asprant/playground-series-co2-emission-prediction-1,Predict CO2 Emissions in Rwanda
15012,140518097,1114.0,69.99819156709505,0,10,/cv13j0/predict-co2-emissions-in-rwanda-ideas,Predict CO2 Emissions in Rwanda
15013,139604501,1197.0,,0,8,/pratul007/sentinel5p-emissions-modeling-with-gpu,Predict CO2 Emissions in Rwanda
15014,139242806,1204.0,109.5945117915294,0,5,/pohzixiang/predicting-co2-emissions,Predict CO2 Emissions in Rwanda
15015,140228481,1220.0,112.82247365604503,0,6,/ayushpratap113/co2-emmision-prediction,Predict CO2 Emissions in Rwanda
15016,140290323,1217.0,115.01421791154004,2,7,/vinitkp/getting-started-modeling,Predict CO2 Emissions in Rwanda
15017,140558961,1209.0,,0,4,/ayodatascientist/emmission-in-rwanda,Predict CO2 Emissions in Rwanda
15018,140594098,1284.0,142.08544677551637,2,10,/vasudevak/co2-emissions-using-fastai-tabular-learner,Predict CO2 Emissions in Rwanda
15019,138999893,1240.0,,0,19,/amalsp220/emissions-prediction-with-randomforestregressor,Predict CO2 Emissions in Rwanda
15020,139472101,1242.0,143.95171150082535,0,4,/sourabhsingh03993493/co2-emission,Predict CO2 Emissions in Rwanda
15021,138871986,1256.0,,0,1,/ghkhaz/pcer-or-predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
15022,139834096,1288.0,,0,1,/arnaudpoudrai/predict-co2-emission-in-rwanda-eda,Predict CO2 Emissions in Rwanda
15023,138677041,1279.0,175.65458301919202,0,7,/tracyporter/play-3-20-tf,Predict CO2 Emissions in Rwanda
15024,140539721,1295.0,159.59488354993914,1,8,/satishpb/rwanda-carbondioxide-emissions,Predict CO2 Emissions in Rwanda
15025,140291343,1304.0,161.75182271892098,1,6,/armaanseth6702/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
15026,139550051,1374.0,,0,2,/iftekharalammitu/multiple-model-explore-96-accuracy,Predict CO2 Emissions in Rwanda
15027,138676206,1324.0,167.85183253564162,0,4,/anzarwani2/beginner-notebook-playground-series-s3-ep20,Predict CO2 Emissions in Rwanda
15028,139737178,1319.0,,0,0,/eduardomarinho44/rwanda-emissions-competition,Predict CO2 Emissions in Rwanda
15029,140359293,1343.0,168.93780321495035,1,9,/singhayush16/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
15030,138665645,1354.0,169.19377910477715,4,17,/jocelyndumlao/co2-prediction-in-rwanda,Predict CO2 Emissions in Rwanda
15031,139626231,1348.0,,0,1,/nesredinhaji/notebook810e968251,Predict CO2 Emissions in Rwanda
15032,139043708,1404.0,176.41153878248423,0,5,/drissdo23/predict-co2,Predict CO2 Emissions in Rwanda
15033,139043708,1404.0,176.41153878248423,0,5,/drissdo23/predict-co2,Predict CO2 Emissions in Rwanda
15034,140606867,1402.0,,0,4,/ahmetyasinaytar/pca-baseline,Predict CO2 Emissions in Rwanda
15035,140356567,1406.0,180.6227014960862,1,5,/mustafamegahed/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
15036,140356567,1406.0,180.6227014960862,1,5,/mustafamegahed/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
15037,140356567,1406.0,180.6227014960862,1,5,/mustafamegahed/predict-co2-emissions-in-rwanda,Predict CO2 Emissions in Rwanda
15038,138703467,1418.0,,0,4,/ashishtop/eda-geo-features-others,Predict CO2 Emissions in Rwanda
15039,139717345,1422.0,,1,8,/poushalimukherjee/co2-emissions-eda-toxic-gases,Predict CO2 Emissions in Rwanda
15040,139481019,1424.0,198.68345559338545,0,3,/klyushnik/getting-started-vol-1,Predict CO2 Emissions in Rwanda
15041,140648722,374.0,,0,6,/wentinglu/exploratory-data-analysis,Improve a Fixed Model the Data-Centric Way!
15042,141501233,820.0,1.8883505505596312,1,17,/sanjanasatish68l/s3-e21-model-with-feature-importance,Improve a Fixed Model the Data-Centric Way!
15043,142325724,809.0,1.3297315068932591,4,42,/adelinmil/data-centric-way-eda-outliers-fs,Improve a Fixed Model the Data-Centric Way!
15044,141891319,669.0,,0,4,/smailaar/playground-series-s3-e21,Improve a Fixed Model the Data-Centric Way!
15045,141141042,765.0,,4,50,/eishkaran/shortest-code-possible-lb-1-32,Improve a Fixed Model the Data-Centric Way!
15046,141227831,839.0,1.3979402667456833,1,2,/nhttinnguynbch/submit-1,Improve a Fixed Model the Data-Centric Way!
15047,142583945,690.0,,0,6,/kanikasinghaljindal/play-with-lb-ub-in-clipping-data,Improve a Fixed Model the Data-Centric Way!
15048,143163983,507.0,1.2630063969786582,16,62,/arunklenin/in-depth-analysis-five-anomaly-detection-methods,Improve a Fixed Model the Data-Centric Way!
15049,141136760,840.0,,0,12,/rishabh15virgo/s3e21-basic-approaches-that-makes-sense-v1-1-369,Improve a Fixed Model the Data-Centric Way!
15050,141318913,845.0,1.6074880708420858,0,5,/vasudevak/nans-need-all-your-attention,Improve a Fixed Model the Data-Centric Way!
15051,142752058,388.0,,0,1,/radbear/playground-series-3-21,Improve a Fixed Model the Data-Centric Way!
15052,140630630,462.0,1.4115208623532016,0,8,/daaadaaa/s3e21-fixed-model-ctgan,Improve a Fixed Model the Data-Centric Way!
15053,140835098,680.0,1.4060261739544118,3,17,/patrick0302/remove-features-by-setting-zeros-0,Improve a Fixed Model the Data-Centric Way!
15054,142184204,798.0,1.301435184397152,3,23,/franciscofeng/drop-rows-with-low-clipped-target-value,Improve a Fixed Model the Data-Centric Way!
15055,142271324,800.0,,0,7,/nathaniellybrand/lb-1-32613-eda-iso-svm-lof-tutorial,Improve a Fixed Model the Data-Centric Way!
15056,141232886,364.0,,32,83,/achusanjeev/best-score-simple-feature-importance-and-outliers,Improve a Fixed Model the Data-Centric Way!
15057,142354325,784.0,1.2779884126790324,5,16,/jokerinthapack/bring-in-the-noise-bring-in-the-funk,Improve a Fixed Model the Data-Centric Way!
15058,142622272,749.0,5.479686577854325,0,4,/jailsonevora/ml-regression-problem-data-centric-way,Improve a Fixed Model the Data-Centric Way!
15059,140623487,865.0,,0,7,/hli111111/with-submission-original-prediction-task-preproc,Improve a Fixed Model the Data-Centric Way!
15060,141146705,576.0,1.3946410914984688,0,5,/dann12/feature-selection-corr-selectpercentile-k-and-mi,Improve a Fixed Model the Data-Centric Way!
15061,141145485,443.0,1.324233530150721,7,41,/act18l/added-lof-svm-iforest-very-simple-approach,Improve a Fixed Model the Data-Centric Way!
15062,142417403,646.0,,1,14,/mertbayraktar/various-feature-selection-methods,Improve a Fixed Model the Data-Centric Way!
15063,141624838,720.0,,11,22,/dhawan123/data-centric-way-statistical-approach,Improve a Fixed Model the Data-Centric Way!
15064,141357857,744.0,1.5167279754020362,0,2,/kuryakin/improve-a-fixed-model-xgboost,Improve a Fixed Model the Data-Centric Way!
15065,141357857,744.0,1.48565434482226,0,2,/kuryakin/improve-a-fixed-model-xgboost,Improve a Fixed Model the Data-Centric Way!
15066,142222482,710.0,1.305024483075412,2,14,/francescoliveras/ps-s3-e21-eda-model-en-es,Improve a Fixed Model the Data-Centric Way!
15067,142696832,622.0,,44,130,/alvinleenh/6-basic-feature-selection-techniques,Improve a Fixed Model the Data-Centric Way!
15068,146787463,485.0,,20,72,/yaaangzhou/pg-s3-e21-features-selection-and-tricks,Improve a Fixed Model the Data-Centric Way!
15069,141249019,559.0,1.322482793673919,9,48,/warcoder/lb-1-32253-lof-svm-iforest-cleanlab,Improve a Fixed Model the Data-Centric Way!
15070,141268728,183.0,1.952650305725524,7,30,/bennyfung/ps3e21-eda-and-data-wrangling,Improve a Fixed Model the Data-Centric Way!
15071,141213401,344.0,1.4040987483008287,2,10,/kimijima/improve-data-one-class-svm,Improve a Fixed Model the Data-Centric Way!
15072,141321800,522.0,1.3247810022189137,0,10,/adityakishor1/playground-s3-e21-selection-and-tricks,Improve a Fixed Model the Data-Centric Way!
15073,140897410,186.0,,2,12,/dreamboat26/dissolved-oxygen-prediction-model,Improve a Fixed Model the Data-Centric Way!
15074,141888640,628.0,1.3314585909102756,0,29,/pyrotech/simple-data-centric-code,Improve a Fixed Model the Data-Centric Way!
15075,141231905,445.0,1.5496255019188991,0,4,/bartuolgun/kaggle-playground-s3-e21,Improve a Fixed Model the Data-Centric Way!
15076,141027744,311.0,,2,5,/subramanyashenoy/pgs-s3e21-ipynb,Improve a Fixed Model the Data-Centric Way!
15077,141514885,369.0,1.3343993347484056,2,14,/nazimcherpanov/prediction-s3e21-using-lgbm-votting,Improve a Fixed Model the Data-Centric Way!
15078,142131162,793.0,1.334927941416362,0,2,/murugesann/fixedmodel-ds-prediction-svmoutlier,Improve a Fixed Model the Data-Centric Way!
15079,141082114,90.0,1.5152489604746555,5,22,/oscarm524/ps-s3-ep21-eda-modeling-submission,Improve a Fixed Model the Data-Centric Way!
15080,141082114,90.0,1.5675789249292575,5,22,/oscarm524/ps-s3-ep21-eda-modeling-submission,Improve a Fixed Model the Data-Centric Way!
15081,141082114,90.0,1.5429439727986087,5,22,/oscarm524/ps-s3-ep21-eda-modeling-submission,Improve a Fixed Model the Data-Centric Way!
15082,141176616,716.0,1.340128380055289,2,8,/cicinguyen/hyperparameter-tuning-for-clipping,Improve a Fixed Model the Data-Centric Way!
15083,140888130,673.0,1.3424807079648575,4,33,/docxian/ps-s3-e21-data-centric-oxygen-prediction,Improve a Fixed Model the Data-Centric Way!
15084,142628932,399.0,1.3448004141678511,1,17,/klyushnik/improve-a-fixed-model-vol2,Improve a Fixed Model the Data-Centric Way!
15085,141766840,707.0,,2,2,/yanniscanton/ps-s3e21-be-careful-with-stations-4-and-5,Improve a Fixed Model the Data-Centric Way!
15086,140939293,384.0,,0,7,/stuartmacgowan/data-hacking-walk-through-ps3e21,Improve a Fixed Model the Data-Centric Way!
15087,140885003,767.0,,0,7,/dilgekarakas/optuna-for-feature-selection,Improve a Fixed Model the Data-Centric Way!
15088,142620352,338.0,1.3465661905474704,1,1,/ricopue/data-centric-remove-similar-rows,Improve a Fixed Model the Data-Centric Way!
15089,141880411,670.0,1.4543832145641,0,6,/ikonuhov/s3e21-fixed-model-the-data-centric-rus,Improve a Fixed Model the Data-Centric Way!
15090,142531439,476.0,1.3500180302798646,0,2,/pavelgordeychuk/s3e21-not-the-best-but-honest-work,Improve a Fixed Model the Data-Centric Way!
15091,141767600,378.0,1.5388798024766237,2,7,/mattduerr/s3e21-eda-and-various-outlier-detection,Improve a Fixed Model the Data-Centric Way!
15092,141777158,598.0,1.3527023647873777,0,3,/weichens/ps3e21-eda-combine-trick-1-3527,Improve a Fixed Model the Data-Centric Way!
15093,141426003,535.0,1.354147422157397,0,5,/alexkalita/simple-cross-val-drop,Improve a Fixed Model the Data-Centric Way!
15094,142723689,12.0,,1,4,/hdrbozkurtt/private-lb-12-solution,Improve a Fixed Model the Data-Centric Way!
15095,141065096,324.0,1.5914078587837457,0,8,/pavelabr/submission-with-pca-splitting-and-smote-upsample,Improve a Fixed Model the Data-Centric Way!
15096,141065096,324.0,1.591407858783746,0,8,/pavelabr/submission-with-pca-splitting-and-smote-upsample,Improve a Fixed Model the Data-Centric Way!
15097,143183217,10.0,,0,6,/tomasluna/10th-position-simple-approach,Improve a Fixed Model the Data-Centric Way!
15098,141820926,58.0,,1,10,/chrisk321/data-centric-feature-manipulation-in-r,Improve a Fixed Model the Data-Centric Way!
15099,151948577,407.0,,18,100,/iqbalsyahakbar/ps3e21-data-centric-ai-for-beginners,Improve a Fixed Model the Data-Centric Way!
15100,140649661,300.0,1.3632866098428698,0,13,/pohzixiang/improving-fixed-model-zx,Improve a Fixed Model the Data-Centric Way!
15101,142290838,486.0,1.887115467773557,0,0,/wintersbae/playground-s3e21-water-quality-prediction,Improve a Fixed Model the Data-Centric Way!
15102,140743567,770.0,,1,7,/nivedithavudayagiri/ps3e21-remove-unwanted-rows,Improve a Fixed Model the Data-Centric Way!
15103,141011739,370.0,1.377730237564413,0,7,/debamritapaul/feature-importance-and-compare-different-dfs,Improve a Fixed Model the Data-Centric Way!
15104,141027990,587.0,1.3720311335986215,2,6,/saikatpanda/visualising-data-and-preprocessing,Improve a Fixed Model the Data-Centric Way!
15105,141210050,480.0,,5,19,/cv13j0/data-centric-way,Improve a Fixed Model the Data-Centric Way!
15106,142118929,545.0,,1,14,/yeoyunsianggeremie/s3e21-knowledge-distillation-starter-notebook,Improve a Fixed Model the Data-Centric Way!
15107,141941039,502.0,1.4564268424188738,0,1,/mickhirsh/improve-a-fixed-model-the-data-centric-way,Improve a Fixed Model the Data-Centric Way!
15108,141367247,530.0,1.3793146221107853,0,6,/muhannadmansour/ps3e21-data-centric-oxygen-prediction,Improve a Fixed Model the Data-Centric Way!
15109,141160046,92.0,,2,14,/lucasmorin/s3e21-data-and-error-exploration,Improve a Fixed Model the Data-Centric Way!
15110,142264359,605.0,1.3817876364589985,0,1,/syerramilli/ps3e21-eda-baseline,Improve a Fixed Model the Data-Centric Way!
15111,141574023,5.0,1.3837525690530503,2,9,/faysalmiah1721758/ps3e11-improve-a-fixed-model-the-data-centric-way,Improve a Fixed Model the Data-Centric Way!
15112,141741932,692.0,1.3840595155028008,1,8,/iqmansingh/data-centric-way-outlier-feature-selection,Improve a Fixed Model the Data-Centric Way!
15113,141429139,634.0,2.378936828515406,1,4,/thomasmeiner/ps-s3-21-gans-even-16-few-rows-is-enough,Improve a Fixed Model the Data-Centric Way!
15114,141313605,630.0,1.3936770515745684,1,9,/chiranjeevisrinivas/ps3e21,Improve a Fixed Model the Data-Centric Way!
15115,141313605,630.0,1.3895366159454252,1,9,/chiranjeevisrinivas/ps3e21,Improve a Fixed Model the Data-Centric Way!
15116,141526263,358.0,1.40776353798504,0,3,/ivanvaccari/ps3-e21-rfe-and-feature-selection-comparison,Improve a Fixed Model the Data-Centric Way!
15117,141549547,599.0,1.392169765575812,0,8,/satishpb/data-for-oxygen-prediction,Improve a Fixed Model the Data-Centric Way!
15118,141890843,340.0,1.3920068701586357,0,3,/muthumeenakshi11/improve-a-fixed-model-by-handling-outliers,Improve a Fixed Model the Data-Centric Way!
15119,141227826,304.0,,0,7,/hasancanakcolu/minor-improvement-through-cross-validation,Improve a Fixed Model the Data-Centric Way!
15120,142422504,360.0,8.481169534744604,8,20,/suraj520/optuna-kfold-voting-stacking-lof-iso-forest,Improve a Fixed Model the Data-Centric Way!
15121,142712479,335.0,1.3879675779609766,1,8,/asif00/clean-and-simple-beginner-feature-selection,Improve a Fixed Model the Data-Centric Way!
15122,142809136,49.0,,0,6,/m1y7k8/ps3e21-datacentric,Improve a Fixed Model the Data-Centric Way!
15123,142135884,1.0,,6,17,/thomaswrightanderson/ps3e21-1st-place-solution,Improve a Fixed Model the Data-Centric Way!
15124,142335310,701.0,1.4020043245125005,3,5,/manishkumar7432698/ps3-e21-a-data-centric-way,Improve a Fixed Model the Data-Centric Way!
15125,141796452,635.0,,0,12,/paddykb/ps3e21-evaluate-top-notebooks,Improve a Fixed Model the Data-Centric Way!
15126,141909876,75.0,1.4806097764990955,1,0,/vijaykris/75th-place-playground-s3e21-dissolved-oxygen-predn,Improve a Fixed Model the Data-Centric Way!
15127,142616464,4.0,1.4047995562530136,10,21,/maximeperez/4th-place-solution,Improve a Fixed Model the Data-Centric Way!
15128,140915777,295.0,,4,9,/viji1609/pgs3-e21-eda-with-trees-visualization,Improve a Fixed Model the Data-Centric Way!
15129,142262985,84.0,1.6484040580211785,0,10,/pratul007/feature-engineering-hyperparameter-tuning,Improve a Fixed Model the Data-Centric Way!
15130,142239331,119.0,1.8478712552461816,0,2,/bcscuwe1/data-cleaning-competition,Improve a Fixed Model the Data-Centric Way!
15131,141452279,122.0,,0,7,/ashx010/ps3e21-outlier-analysis-data-cleaning,Improve a Fixed Model the Data-Centric Way!
15132,140841357,129.0,1.4077635379850395,2,8,/jocelyndumlao/revamptraining-data-to-elevate-random-forest-model,Improve a Fixed Model the Data-Centric Way!
15133,141914246,150.0,1.5907928342378903,0,7,/ahmedali74/the-data-centric-way-feature-selection,Improve a Fixed Model the Data-Centric Way!
15134,140742003,310.0,,1,4,/ch124uec/eda-outlier-removal-stratified-sampling,Improve a Fixed Model the Data-Centric Way!
15135,140850899,185.0,,2,13,/manavgupta92/smallest-notebook-to-understand-competition,Improve a Fixed Model the Data-Centric Way!
15136,140901010,130.0,1.40776353798504,2,10,/dishaasinghi/random-forest-for-starters-ps3e21,Improve a Fixed Model the Data-Centric Way!
15137,142550115,571.0,1.465799642168581,0,1,/muhammadawn/mahalanobis-algorithm,Improve a Fixed Model the Data-Centric Way!
15138,141767768,239.0,,0,2,/moohamedelsayed/outliers-removal-methods,Improve a Fixed Model the Data-Centric Way!
15139,142296023,261.0,,0,5,/bingdaidata/generate-data-to-improve-a-model-in-progress,Improve a Fixed Model the Data-Centric Way!
15140,147499850,270.0,1.5070784318933816,0,3,/huyenle/which-features-to-remove-which-rows-to-keep,Improve a Fixed Model the Data-Centric Way!
15141,141095157,79.0,1.4252404445850997,1,7,/omarvivas/model3s21-v1,Improve a Fixed Model the Data-Centric Way!
15142,140643165,402.0,1.4087380739299835,0,6,/sourabhsingh03993493/the-way-of-data,Improve a Fixed Model the Data-Centric Way!
15143,141793966,44.0,1.4365020877752923,2,15,/golammostofas/improve-a-fixed-model-for-beginners,Improve a Fixed Model the Data-Centric Way!
15144,140738894,356.0,1.7791150673291265,0,5,/averma111/data-centric-pss3e21,Improve a Fixed Model the Data-Centric Way!
15145,141414040,386.0,1.4254756876844936,1,11,/ashishjagdishsharma/a-fairytale-of-data-transformation,Improve a Fixed Model the Data-Centric Way!
15146,141074676,465.0,,0,2,/moritzm00/eda-outlier-detection-with-pyod-lof-if-ecod,Improve a Fixed Model the Data-Centric Way!
15147,141149703,616.0,,0,7,/muhammadusmanfarooq/understanding-anomalies-detection-algorithms,Improve a Fixed Model the Data-Centric Way!
15148,141199913,655.0,,0,3,/acdundore/s3-e21-eda-feature-selection,Improve a Fixed Model the Data-Centric Way!
15149,141998999,544.0,,18,70,/magantiit/dissolved-o2-predictions-in-river-water,Improve a Fixed Model the Data-Centric Way!
15150,140632670,96.0,,6,16,/mpwolke/oxygen-focus-on-data-centric,Improve a Fixed Model the Data-Centric Way!
15151,141699139,850.0,,0,5,/heymihir/going-by-the-basics,Improve a Fixed Model the Data-Centric Way!
15152,140778988,541.0,1.4670831709611187,0,5,/coinshot/dissolved-oxygen-prediction-in-river-model,Improve a Fixed Model the Data-Centric Way!
15153,142513527,425.0,,2,8,/samu2505/datacentric-exponentialsmoothing,Improve a Fixed Model the Data-Centric Way!
15154,141429959,752.0,,0,9,/vladislavonufrienko/ps3e21-eda,Improve a Fixed Model the Data-Centric Way!
15155,141530650,773.0,,0,7,/kamrantanwari/s3e21-baseline-eda-advanced-regression,Improve a Fixed Model the Data-Centric Way!
15156,142558740,802.0,,0,1,/amrsaid1233/dissolved-oxygen-in-water,Improve a Fixed Model the Data-Centric Way!
15157,141579386,786.0,1.5688170404402255,0,3,/kuralamuthan300/data-refinement-for-rf-regressor,Improve a Fixed Model the Data-Centric Way!
15158,140933397,872.0,1.5546694391748146,0,5,/tracyporter/play-3-21,Improve a Fixed Model the Data-Centric Way!
15159,141714382,879.0,1.6159112344275144,0,4,/sergeyyakovlev1312/optimal-linear-estimation,Improve a Fixed Model the Data-Centric Way!
15160,141746322,894.0,,0,1,/viviansam/dissolved-o2-prediction-outlier-removal-iqr,Improve a Fixed Model the Data-Centric Way!
15161,141455441,888.0,1.5869835851610838,4,9,/borhanmukto/improve-a-fixed-model-the-data-centric-way,Improve a Fixed Model the Data-Centric Way!
15162,142288873,902.0,1.6287192267746966,1,8,/ayusov/multivariate-normal-model,Improve a Fixed Model the Data-Centric Way!
15163,140707548,904.0,1.955619858671352,0,7,/kotukw/dissolved-oxygen-prediction-in-improving-model,Improve a Fixed Model the Data-Centric Way!
15164,141718047,916.0,1.8580291240483569,1,3,/nitinpilkhwal/linear-lasso-and-ridge-using-cv-and-randomforest,Improve a Fixed Model the Data-Centric Way!
15165,141502203,933.0,,0,7,/rodrigostallsikora/doing-what-chatgpt-tells-me-to-do,Improve a Fixed Model the Data-Centric Way!
15166,141585058,952.0,,0,5,/rajatraj0502/improve-a-fixed-model-the-data-centric-way,Improve a Fixed Model the Data-Centric Way!
15167,142176450,24.0,0.1876673219564256,1,16,/chenboluo/tile-xla-end-to-end-train-infer-slight-change,Google - Fast or Slow? Predict AI Model Runtime
15168,150184486,42.0,0.1931500219159931,0,10,/goelyash/google-fast-or-slow-tile-xla,Google - Fast or Slow? Predict AI Model Runtime
15169,166618647,125.0,,0,0,/weiooocn/tile-xla-end-to-end-train-infer,Google - Fast or Slow? Predict AI Model Runtime
15170,141808838,156.0,,0,8,/ksmcg90/torchmetrics-for-tile,Google - Fast or Slow? Predict AI Model Runtime
15171,147099566,175.0,,4,34,/jasonheesanglee/checking-keys-and-values-all-file,Google - Fast or Slow? Predict AI Model Runtime
15172,141619818,172.0,,1,8,/jainam213/0-97val0-12lb,Google - Fast or Slow? Predict AI Model Runtime
15173,142247684,241.0,,0,9,/nithinreddy90/google-fast-or-slow,Google - Fast or Slow? Predict AI Model Runtime
15174,149955177,263.0,,4,8,/lewington/crikey-understand-the-data,Google - Fast or Slow? Predict AI Model Runtime
15175,141971667,369.0,0.1620033150166784,1,16,,Google - Fast or Slow? Predict AI Model Runtime
15176,145852387,286.0,,0,4,/geokocha/an-simple-introduction-to-tile-configuration,Google - Fast or Slow? Predict AI Model Runtime
15177,141968600,420.0,,0,7,/sourabhsingh03993493/submission-with-one-epoch,Google - Fast or Slow? Predict AI Model Runtime
15178,141785578,328.0,0.1480025719230566,0,6,/josh951/ai-model-runtime-base,Google - Fast or Slow? Predict AI Model Runtime
15179,142299050,287.0,0.1859892730257266,20,74,/werus23/tile-xla-end-to-end-train-infer,Google - Fast or Slow? Predict AI Model Runtime
15180,142017551,370.0,0.1620037924177011,0,14,/yinankaggle/improved-tile-xla-end-to-end-submission,Google - Fast or Slow? Predict AI Model Runtime
15181,148330904,443.0,,3,17,/skuldropr/predict-ai-model-runtime-tile-only,Google - Fast or Slow? Predict AI Model Runtime
15182,141895141,403.0,0.1556232714429955,1,15,/sreekanthpolu/google-fast-or-slow-submission,Google - Fast or Slow? Predict AI Model Runtime
15183,145799987,451.0,,2,2,/theheadmaster/starter-notebook-tensorflow-gnn,Google - Fast or Slow? Predict AI Model Runtime
15184,141614153,466.0,0.1475674906127076,2,26,/rishabh15virgo/first-impression-understand-data-eda-baseline-15,Google - Fast or Slow? Predict AI Model Runtime
15185,141473973,545.0,,2,45,/robikscube/thinking-fast-slower-runtime-predictions,Google - Fast or Slow? Predict AI Model Runtime
15186,144379519,567.0,,6,21,/chrisk321/fast-or-slow-initial-eda-submission-in-r,Google - Fast or Slow? Predict AI Model Runtime
15187,154293547,11.0,,3,62,/cdeotte/11th-place-gold-cv-835-public-lb-788,Child Mind Institute - Detect Sleep States
15188,153753738,23.0,0.7786775794250201,0,7,/schobbejak/cmi-submission-team-epoch,Child Mind Institute - Detect Sleep States
15189,143539309,7.0,,2,14,/robikscube/sleep-states-events-file-update-viz,Child Mind Institute - Detect Sleep States
15190,153933348,39.0,0.7612241103989719,0,3,/lizhecheng/detect-sleep-states-ensemble-lb-0-761-pb-0-804,Child Mind Institute - Detect Sleep States
15191,153615353,44.0,,0,13,/takanashihumbert/a-simple-way-trying-to-find-the-dark-zones,Child Mind Institute - Detect Sleep States
15192,143678548,31.0,,1,51,/tolgadincer/sleep-state-fast-data-access-with-parquet,Child Mind Institute - Detect Sleep States
15193,144536186,104.0,,0,6,/peilwang/infer-notebook-ensemabl-pub,Child Mind Institute - Detect Sleep States
15194,153754362,79.0,,0,1,/hutch1221/cmi-ensemble,Child Mind Institute - Detect Sleep States
15195,142133190,68.0,,1,12,/hidebu/eda-cmi-detect-sleep-states,Child Mind Institute - Detect Sleep States
15196,145199152,93.0,,0,2,/kaggledummie007/train-series-of-week-and-longer-w-o-nans,Child Mind Institute - Detect Sleep States
15197,152494646,63.0,0.707020774344218,1,6,/kazuakiohmori/averaging,Child Mind Institute - Detect Sleep States
15198,148997696,134.0,,0,1,/handlebee/detect-sleep-states-inference-explain-all,Child Mind Institute - Detect Sleep States
15199,147199248,162.0,,0,3,/mingkaizhu/train-series,Child Mind Institute - Detect Sleep States
15200,146249995,166.0,,11,40,/yeoyunsianggeremie/fe-ensemble-added-period-3600,Child Mind Institute - Detect Sleep States
15201,151117219,142.0,0.6567809531481748,5,34,/sambitmukherjee/d-s-s-faster-r-cnn-submission,Child Mind Institute - Detect Sleep States
15202,147531007,87.0,,12,59,/itsuki9180/detect-sleep-states-dataprepare,Child Mind Institute - Detect Sleep States
15203,151316849,175.0,,0,9,/chrisrichardmiles/eda-plotting-anglez-enmo-events-and-non-events,Child Mind Institute - Detect Sleep States
15204,144017545,226.0,,0,3,/sjlee101/how-to-use-a-metric-notebook-event-detection-ap,Child Mind Institute - Detect Sleep States
15205,142873650,174.0,0.1606044426016766,2,7,/anilreddyvv/tackling-out-of-memory-issue-on-test-set,Child Mind Institute - Detect Sleep States
15206,154378105,258.0,,0,1,/j112358/datavisualization,Child Mind Institute - Detect Sleep States
15207,150555913,245.0,,0,2,/nvithayapale/sleep-data-preprocessing,Child Mind Institute - Detect Sleep States
15208,142321796,119.0,,4,10,/quillen/sleepstates-daylight-saving-time,Child Mind Institute - Detect Sleep States
15209,148727954,207.0,,0,2,/unakarskywalker/mydataprepare,Child Mind Institute - Detect Sleep States
15210,146638915,289.0,,0,1,/yeskinkim/child-sleep-critical-point-regression,Child Mind Institute - Detect Sleep States
15211,150573921,321.0,0.0004882511023626,0,9,/atshimamura/datareviewandeasyprediction,Child Mind Institute - Detect Sleep States
15212,145641127,1207.0,,1,5,/riow1983/plotting-events-on-spectrograms,Child Mind Institute - Detect Sleep States
15213,143927887,334.0,,2,21,/dangnguyen97/lb-0-343-feature-eng-ideas-and-lightgbm-3,Child Mind Institute - Detect Sleep States
15214,146219505,328.0,0.4555164599316004,1,2,/pakornchunwirat/notebook9cf7adf42b,Child Mind Institute - Detect Sleep States
15215,150852699,484.0,,0,2,/tomu0106/miss-tom,Child Mind Institute - Detect Sleep States
15216,146917998,390.0,,0,0,/weiyangeliu/feature-awake-heatmap,Child Mind Institute - Detect Sleep States
15217,148680628,442.0,0.5915840023090371,0,10,/messi42/detect-sleep-states-inference,Child Mind Institute - Detect Sleep States
15218,144371297,761.0,,1,4,/miltiadesgeneral/detect-sleep-states-guidebook,Child Mind Institute - Detect Sleep States
15219,148234131,459.0,,3,19,/mitsuyasuhoshino/cmi-detectsleepstates-eda-visualization,Child Mind Institute - Detect Sleep States
15220,142527146,479.0,0.1586811550255336,0,18,,Child Mind Institute - Detect Sleep States
15221,144096315,703.0,,3,18,/renatoreggiani/zzzs-reduce-memory-usage-cmi,Child Mind Institute - Detect Sleep States
15222,146965196,496.0,0.5395979205931065,1,6,/aboutwonjun/ensemble-wonjun,Child Mind Institute - Detect Sleep States
15223,142341261,366.0,,3,12,/shivamsingh17072001/xgboost-starter-notebook,Child Mind Institute - Detect Sleep States
15224,144407254,558.0,0.4153895100417464,6,32,/siddhvr/cmi-feature-engg-with-ensemble-models,Child Mind Institute - Detect Sleep States
15225,145996325,576.0,,4,11,/michalinahulak/pl-easy-eda-sleep,Child Mind Institute - Detect Sleep States
15226,145949308,612.0,0.4756885724667886,4,44,/smnuruzzaman/feature-engineering-and-ensemble,Child Mind Institute - Detect Sleep States
15227,152704589,646.0,,0,0,/dongik9/1127227-randomforest,Child Mind Institute - Detect Sleep States
15228,150540120,762.0,,0,0,/linderlee/sleep1,Child Mind Institute - Detect Sleep States
15229,148643213,648.0,,1,1,/itzhv14/feature-selection-cv,Child Mind Institute - Detect Sleep States
15230,144940679,719.0,0.436169662046114,0,14,/ruiyaoyang/randomforest-version,Child Mind Institute - Detect Sleep States
15231,153078619,296.0,0.6844049505197393,0,0,/sjyangkevin/sleep-study-gru-inference,Child Mind Institute - Detect Sleep States
15232,144914187,794.0,,6,37,/junkoda/checking-daylight-saving-times,Child Mind Institute - Detect Sleep States
15233,156466241,854.0,,0,0,/tmvimfb/cmi-dss-polars-and-lightgbm-for-ram-management,Child Mind Institute - Detect Sleep States
15234,151682096,808.0,,0,0,/jeonghosuh/notebook77909844ad,Child Mind Institute - Detect Sleep States
15235,155036652,822.0,,0,0,/miraclejy/notebook880766feac,Child Mind Institute - Detect Sleep States
15236,152955392,904.0,,0,1,/zrwang2025/image-preprocess,Child Mind Institute - Detect Sleep States
15237,149543466,867.0,0.6505092828438028,0,0,/kevin1028/detect-sleep-states-submission-110303515,Child Mind Institute - Detect Sleep States
15238,147902097,1876.0,,3,10,/rubyhartono/eda-child-mind-institute-detect-sleep-states,Child Mind Institute - Detect Sleep States
15239,150029741,889.0,,0,1,/adheeshakalahegamage/group-notebook-group10-version-03,Child Mind Institute - Detect Sleep States
15240,150040445,890.0,,0,0,/adheeshagamage/detect-sleep-state-239316c,Child Mind Institute - Detect Sleep States
15241,146461280,912.0,,5,24,/enricomanosperti/detect-sleep-states-preprocessing-and-eda,Child Mind Institute - Detect Sleep States
15242,149525097,910.0,0.0250569816248913,0,0,/changtunghan/sleep-dummysubmission-110303520,Child Mind Institute - Detect Sleep States
15243,142091431,1060.0,,3,90,/carlmcbrideellis/zzzs-plots-of-all-277-anglez-and-enmo-series,Child Mind Institute - Detect Sleep States
15244,143356303,1036.0,,0,2,/zeyulau/eda-noob-friendly-ver,Child Mind Institute - Detect Sleep States
15245,143526761,1049.0,0.2489410411989335,0,6,/satheeshbhukya1/detect-sleep-states,Child Mind Institute - Detect Sleep States
15246,142501747,1017.0,,0,3,/sourabhsingh03993493/rfc-and-visualization,Child Mind Institute - Detect Sleep States
15247,142950527,1088.0,,1,5,/bkowshik/exploratory-data-analysis-detect-sleep-states,Child Mind Institute - Detect Sleep States
15248,148330510,1094.0,0.516378609788681,0,1,/fred20978/ensemble-model-cmi-fred,Child Mind Institute - Detect Sleep States
15249,152429993,1112.0,0.578691695876624,0,1,/oatsada/g13-sleepdetect-final,Child Mind Institute - Detect Sleep States
15250,152185506,1118.0,,0,0,/error404ntfound404/feature-engineering-and-random-forest-predi-e202bf,Child Mind Institute - Detect Sleep States
15251,147127576,1149.0,,2,17,/andreytikhomirov/eda-fe-introducing-seasons,Child Mind Institute - Detect Sleep States
15252,142608717,1145.0,,1,5,/josipvrdoljak/zzzs-xgb-feature-eng,Child Mind Institute - Detect Sleep States
15253,153797291,1170.0,0.4587533221976594,0,1,/timetoti/cmi-dss-infer-exponentially-dilated-u-net,Child Mind Institute - Detect Sleep States
15254,144467786,1147.0,0.312306773245955,0,2,/phamdinhduong/xgboost-bayesian,Child Mind Institute - Detect Sleep States
15255,148260954,1202.0,,0,0,/samandersson/sleep-critical-point-prepare-data,Child Mind Institute - Detect Sleep States
15256,142358201,1214.0,,19,64,/henriupton/efficient-loading-memory-usage-visualizations-cmi,Child Mind Institute - Detect Sleep States
15257,144836961,1242.0,9.820775645398176e-05,0,0,/alamhanz/hourly-bucket-rf,Child Mind Institute - Detect Sleep States
15258,145009287,1277.0,,2,16,/lccburk/sleep-data-exploration,Child Mind Institute - Detect Sleep States
15259,144520861,1332.0,0.4283959700168753,5,11,/wchan757/lb-0-428-feature-engineering-rf-prediction,Child Mind Institute - Detect Sleep States
15260,151521440,1329.0,,0,0,/philipjaq/cmi-data-analysis,Child Mind Institute - Detect Sleep States
15261,143867622,1338.0,,0,14,/marcinstasko/zzz-tutorial-on-code-profiling-and-pipelinin,Child Mind Institute - Detect Sleep States
15262,146542729,1340.0,,0,1,/hapiwang/oct10main-test,Child Mind Institute - Detect Sleep States
15263,143124551,1326.0,,5,7,/pauloyuncha/eda-which-makes-sense-beta,Child Mind Institute - Detect Sleep States
15264,144128920,1406.0,0.4027325655823039,8,94,/zhukovoleksiy/detect-sleep-states-baseline-solution,Child Mind Institute - Detect Sleep States
15265,142291430,1383.0,,2,14,/harriwashere/eda-accelerometer-based-sleep-analysis,Child Mind Institute - Detect Sleep States
15266,142299726,1346.0,,26,155,/patrick0302/viz-of-sleeping-time-series,Child Mind Institute - Detect Sleep States
15267,142652893,1489.0,,0,3,/uadithyan/detect-sleep-states-data-preparation,Child Mind Institute - Detect Sleep States
15268,144028930,1494.0,1.6079158936301796e-05,1,5,/zotovaa/cmi-gradient-boosting-insomnia-research,Child Mind Institute - Detect Sleep States
15269,142466885,1574.0,,3,14,/rimbax/statistical-feature-engineering,Child Mind Institute - Detect Sleep States
15270,143071191,1497.0,0.2884152136697906,1,15,,Child Mind Institute - Detect Sleep States
15271,144341878,1590.0,,5,3,/rohitchaudhari25/cmi-dss-23-94-86-reduction-20-14-line-scripts,Child Mind Institute - Detect Sleep States
15272,144179505,1504.0,,8,27,/seungmoklee/cmi-how-event-detection-ap-works,Child Mind Institute - Detect Sleep States
15273,152979078,1543.0,,0,0,/phuwichwinyutrakul/neural-network-child-sleep-pattern,Child Mind Institute - Detect Sleep States
15274,143739091,1533.0,,0,0,/gxkjh298/sleep-state1,Child Mind Institute - Detect Sleep States
15275,142870999,1558.0,,2,7,/vinitkp/sleepstate-eda-r,Child Mind Institute - Detect Sleep States
15276,148998357,1544.0,,0,10,/sumitai/zzzs-random-forest-classifier,Child Mind Institute - Detect Sleep States
15277,147915797,1541.0,0.2793369419791131,0,0,/zgnzekibozkurt/detect-sleep-states,Child Mind Institute - Detect Sleep States
15278,148592491,1517.0,,0,12,/shoabahamed/complete-incomplete-series-analysis,Child Mind Institute - Detect Sleep States
15279,145709482,1565.0,,5,14,/adelinmil/cmi-eda-chunked-ds-memory-reduction,Child Mind Institute - Detect Sleep States
15280,147068351,1660.0,,2,8,/gauravk123/interactive-eda-per-subject-train-series-ts,Child Mind Institute - Detect Sleep States
15281,143818622,1632.0,,0,0,/alikarbala/detect-sleep-data-prep-3,Child Mind Institute - Detect Sleep States
15282,146018624,1696.0,,0,1,/crischir/zzzs-make-small-starter-datasets-target,Child Mind Institute - Detect Sleep States
15283,142322813,1677.0,,0,2,/kuryakin/detect-sleep-states-merge-df,Child Mind Institute - Detect Sleep States
15284,153514066,1688.0,0.0869298310236052,0,0,/martinkatona/mat-2023-sleep,Child Mind Institute - Detect Sleep States
15285,149096503,1697.0,,1,3,/haiderali20/sleep-or-awake,Child Mind Institute - Detect Sleep States
15286,142517943,1691.0,0.0874396055451176,0,3,/adwitiya123/child-mind-institute-lgb-baseline,Child Mind Institute - Detect Sleep States
15287,142907149,1710.0,,0,13,/sarthak333/predict-sleep,Child Mind Institute - Detect Sleep States
15288,142216786,1705.0,,0,7,/fengvm/detect-sleep-states-fast-timing-diagram,Child Mind Institute - Detect Sleep States
15289,148041278,1695.0,0.0581200923043068,0,2,/brendanengh/ma-test-submission,Child Mind Institute - Detect Sleep States
15290,144921406,1716.0,,0,12,/loki003/elasticnet-with-gpu-using-cudf-and-cuml,Child Mind Institute - Detect Sleep States
15291,142330442,1733.0,,0,1,/oriolrabasseda/clean-dataset-dss,Child Mind Institute - Detect Sleep States
15292,149499345,1751.0,0.0250569816248913,0,3,/yihsuankao/sleep-dummysubmission,Child Mind Institute - Detect Sleep States
15293,150484584,1753.0,0.0250569816248913,0,0,/chenpengwei/sleep-dummysubmission-8344ed,Child Mind Institute - Detect Sleep States
15294,142411773,1739.0,,2,20,/alinasri/sleep-data-analysis-some-eda,Child Mind Institute - Detect Sleep States
15295,142174407,1782.0,0.0,0,6,/yunsuxiaozi/welcome-to-detect-sleep-states,Child Mind Institute - Detect Sleep States
15296,153746953,1790.0,0.0042631658504844,0,1,/coyamax/cmi-infer-final,Child Mind Institute - Detect Sleep States
15297,146329038,1788.0,,0,1,/steveshooty/cpu-data-preprocessing-reduce-84-92,Child Mind Institute - Detect Sleep States
15298,151317955,1799.0,,0,0,/brandonleetsai/572-final-draft-notebook,Child Mind Institute - Detect Sleep States
15299,150933617,1821.0,0.0004882511023626,0,1,/furusawatomoki/child,Child Mind Institute - Detect Sleep States
15300,150933617,1821.0,0.0004882511023626,0,1,/furusawatomoki/child,Child Mind Institute - Detect Sleep States
15301,142078896,1826.0,,3,39,/mpwolke/zzzs-wake-up-kagglers,Child Mind Institute - Detect Sleep States
15302,143239775,1815.0,0.0002482649625506,0,5,/munumbutt/signal-processing-techniques,Child Mind Institute - Detect Sleep States
15303,143837780,1855.0,0.0,12,44,/jocelyndumlao/sleep-event-detection-eda,Child Mind Institute - Detect Sleep States
15304,152751030,1872.0,0.0,0,0,/nontapatb/notebook30acfd67a5,Child Mind Institute - Detect Sleep States
15305,147192006,7.0,,2,15,/martynoveduard/save-csv-faster-using-polars,Stanford Ribonanza RNA Folding
15306,152513196,4.0,,0,2,/tattaka/contrafold-train-bpps-0-300000,Stanford Ribonanza RNA Folding
15307,150149976,38.0,,1,1,/venkatapadavala/rna-fm,Stanford Ribonanza RNA Folding
15308,147571371,10.0,,40,99,/shlomoron/srrf-transformer-tpu-training,Stanford Ribonanza RNA Folding
15309,151159361,29.0,,0,4,/enriquezaf/shared-sequences-between-training-set-public-lb,Stanford Ribonanza RNA Folding
15310,152790999,112.0,,8,35,/alberteinsten/so-what-do-i-have-to-do-srrf-edition,Stanford Ribonanza RNA Folding
15311,154162734,93.0,,0,0,/sacuscreed/bpp-emb-inference,Stanford Ribonanza RNA Folding
15312,150439445,59.0,,8,11,/konstantinboyko/convert-original-csv-file-to-tfrecord,Stanford Ribonanza RNA Folding
15313,154051069,181.0,,0,0,/yasinadyaman/separateinferencesliding,Stanford Ribonanza RNA Folding
15314,147081266,77.0,,3,6,,Stanford Ribonanza RNA Folding
15315,144297798,70.0,0.2998975903698225,0,32,/fnands/a-quick-gnn-baseline,Stanford Ribonanza RNA Folding
15316,150578739,379.0,0.1580350947780049,0,9,/liuyanfeng/stanford-rrf-tensorflow-tpu,Stanford Ribonanza RNA Folding
15317,142345338,367.0,,0,14,,Stanford Ribonanza RNA Folding
15318,148997138,475.0,,0,8,/something4kag/ribonanza-3d-coords-prep,Stanford Ribonanza RNA Folding
15319,146613795,233.0,0.2330555175356574,0,11,/rgieseking/ribonanza-baseline-average-per-nucleotide-acgu,Stanford Ribonanza RNA Folding
15320,157445662,517.0,,1,8,/yassinealouini/eda-rna-with-polars,Stanford Ribonanza RNA Folding
15321,142347287,540.0,,0,21,/jasonheesanglee/rna-science-checking-files,Stanford Ribonanza RNA Folding
15322,152066536,547.0,0.1547244470639874,0,1,,Stanford Ribonanza RNA Folding
15323,151843120,272.0,,6,3,/jainam213/fork-of-transformer-with-sliding-window,Stanford Ribonanza RNA Folding
15324,153311838,403.0,0.1580350947780049,0,0,,Stanford Ribonanza RNA Folding
15325,152386133,137.0,,0,0,/weiooocn/srrf-transformer-tpu-training,Stanford Ribonanza RNA Folding
15326,150272530,446.0,,0,8,/cevangelist/rna-main-dataset-eda,Stanford Ribonanza RNA Folding
15327,153624629,184.0,0.1859301953245928,8,31,/pranshubahadur/esm2-rmdb-rna-dataset,Stanford Ribonanza RNA Folding
15328,151135150,196.0,0.2958618407911958,0,0,/mirenaborisova/srrnaf-1,Stanford Ribonanza RNA Folding
15329,143051652,295.0,,0,6,/laythaljorani/data-viz,Stanford Ribonanza RNA Folding
15330,147853213,195.0,,0,17,/laetitialanfranchi/exploration-with-graphs-and-sequence-visualization,Stanford Ribonanza RNA Folding
15331,143530675,153.0,,0,3,/vitorbl/ribonanza-rna-simple-eda,Stanford Ribonanza RNA Folding
15332,148580341,390.0,,0,0,/nizamuddin/rna-starter,Stanford Ribonanza RNA Folding
15333,152913163,419.0,0.3397574610946817,0,0,/abhinavraj111/basic-xg-boost-for-rna-computing,Stanford Ribonanza RNA Folding
15334,151311488,679.0,0.302180880402632,0,1,/rgismeyssonnier/notebook-stanford-ribonanza-solution,Stanford Ribonanza RNA Folding
15335,149928019,658.0,,0,5,/jordanyoung993/sequence-images-cnn,Stanford Ribonanza RNA Folding
15336,154251376,653.0,,0,0,/bocatadecalamares/train-ribonanza-transformers,Stanford Ribonanza RNA Folding
15337,145517071,671.0,0.3017252872066053,1,8,/ilikedeeplearning/sample-submission-ribonanza-rna-folding,Stanford Ribonanza RNA Folding
15338,143669798,684.0,,0,8,/jonasthoenfaber/reactivity-prediction,Stanford Ribonanza RNA Folding
15339,149273232,686.0,0.3263120527125703,0,0,/kkityama/stanford-ribonanza-rna-folding,Stanford Ribonanza RNA Folding
15340,144637715,719.0,0.3397574610946817,9,46,/jocelyndumlao/rna-structure-prediction-performance-analysis,Stanford Ribonanza RNA Folding
15341,146261645,725.0,0.3397574610946817,0,5,/adityad23/rna-structure-prediction,Stanford Ribonanza RNA Folding
15342,147940511,730.0,0.3397574610946817,0,7,/josephkibira/stanford-ribonanza-rna-folding-notebook,Stanford Ribonanza RNA Folding
15343,147940511,730.0,0.3397574610946817,0,7,/josephkibira/stanford-ribonanza-rna-folding-notebook,Stanford Ribonanza RNA Folding
15344,152433607,734.0,0.3397574610946817,0,10,/bhanupratapbiswas/stanford-ribonanza-rna-folding-01,Stanford Ribonanza RNA Folding
15345,142766349,517.0,,0,13,/nithinreddy90/neurips-2023,NeurIPS 2023 - Machine Unlearning
15346,148668696,51.0,,5,50,/scottclowe/run-unlearn-finetune-with-classweights,NeurIPS 2023 - Machine Unlearning
15347,143198597,363.0,0.0,7,41,/asarvazyan/unlearn-faces-or-cifar10-submit-w-o-exceptions,NeurIPS 2023 - Machine Unlearning
15348,143319824,1075.0,,9,20,/izammohammed/run-unlearn-finetune-with-classweights,NeurIPS 2023 - Machine Unlearning
15349,147606479,373.0,,3,3,/divyanshbhadauria1/unlearn-faces-or-cifar10-submit-w-o-exceptions,NeurIPS 2023 - Machine Unlearning
15350,143394679,1068.0,0.0,2,8,/amanmukati/neurips-detrain-model,NeurIPS 2023 - Machine Unlearning
15351,151832608,680.0,,8,32,,NeurIPS 2023 - Machine Unlearning
15352,146223094,1091.0,0.0,0,3,/w2yoon/w2y-ssd,NeurIPS 2023 - Machine Unlearning
15353,144714301,37.0,,0,0,/timo13113/neg-ft-on-forget-pos-ft-on-similar-by-p-hash,NeurIPS 2023 - Machine Unlearning
15354,146622453,348.0,,0,0,/sanmaprogramming/unlearning-distilation,NeurIPS 2023 - Machine Unlearning
15355,144758108,822.0,,0,1,/adhithyasrinivasan/unlearn,NeurIPS 2023 - Machine Unlearning
15356,147234642,315.0,,0,16,/dangnguyen97/neurips-finetuned-efa0bc,NeurIPS 2023 - Machine Unlearning
15357,145156729,897.0,,7,21,/luispintoc/selective-synaptic-dampening-ssd,NeurIPS 2023 - Machine Unlearning
15358,152160725,67.0,,0,3,/guy477/notebook4fc7757a9b,NeurIPS 2023 - Machine Unlearning
15359,155045761,318.0,0.0,0,1,/rfeng12/multiplied-loss-by-0-3-and-training-on-forget-set,NeurIPS 2023 - Machine Unlearning
15360,150418001,661.0,,2,25,/mgorinova/machine-unlearning-evaluation-on-cifar-10,NeurIPS 2023 - Machine Unlearning
15361,157084157,651.0,0.0,0,1,/chenboluo/2nd-place-machine-unlearning-solution,NeurIPS 2023 - Machine Unlearning
15362,150730292,800.0,,0,4,/imessam/neurips-2023-machine-unlearning,NeurIPS 2023 - Machine Unlearning
15363,153043280,551.0,,0,0,/fasihuoe/prune-and-repair-819ffb,NeurIPS 2023 - Machine Unlearning
15364,152485624,829.0,,0,1,/francescorubbo/adversarial-unlearning-finetuning,NeurIPS 2023 - Machine Unlearning
15365,149251634,317.0,,0,0,/kindngng/unlearning-maximum-entropy,NeurIPS 2023 - Machine Unlearning
15366,158574451,10.0,,0,2,/kuohsintu/saliency-based-unlearning-10th-place-solution,NeurIPS 2023 - Machine Unlearning
15367,151485872,406.0,,0,0,/gmalik1998/fork-of-fork-of-run-unlearn-finetune-3bd4dc-06b85a,NeurIPS 2023 - Machine Unlearning
15368,148177520,372.0,,0,1,/shivankgarg21/lora-unlearn-linear,NeurIPS 2023 - Machine Unlearning
15369,162112230,988.0,,0,0,/andrssebastian/neurips-baseline,NeurIPS 2023 - Machine Unlearning
15370,152915108,671.0,,2,2,/abidhasan99/shuffling-the-targets,NeurIPS 2023 - Machine Unlearning
15371,152599771,226.0,,0,0,/jaidevchittoria/unlearnchallenge-weights-manipulation,NeurIPS 2023 - Machine Unlearning
15372,155297123,6.0,,7,11,/stathiskaripidis/unlearning-by-resetting-layers-6th-on-private-lb,NeurIPS 2023 - Machine Unlearning
15373,153098524,8.0,,0,2,/jaesinahn/forget-set-free-approach-9th-on-private-lb,NeurIPS 2023 - Machine Unlearning
15374,152266319,405.0,,0,1,,NeurIPS 2023 - Machine Unlearning
15375,153137657,1.0,0.0,0,11,/fanchuan/2nd-place-machine-unlearning-solution,NeurIPS 2023 - Machine Unlearning
15376,153004982,4.0,,2,9,/sebastianoleszko/prune-re-init-entropy-regularized-fine-tuning,NeurIPS 2023 - Machine Unlearning
15377,153058674,885.0,,0,1,/saillaser/seq-forget-retain-histogram-mod-matching-ewc,NeurIPS 2023 - Machine Unlearning
15378,153137296,146.0,,0,0,/limyewon/unlearning-with-membership-inference-attack,NeurIPS 2023 - Machine Unlearning
15379,152349962,111.0,,0,0,/salmanhabeeb/run-unlearn-finetune-03,NeurIPS 2023 - Machine Unlearning
15380,147340801,54.0,,6,3,/jainam213/custom-unlearn,NeurIPS 2023 - Machine Unlearning
15381,147763138,7.0,,0,13,/sunkroos/submission-csv-not-found-solution,NeurIPS 2023 - Machine Unlearning
15382,153481813,3.0,,0,4,/seifachour12/unlearning-solution-3rd-rank,NeurIPS 2023 - Machine Unlearning
15383,147764956,911.0,,0,17,/hmasui/debugging-notebook-based-on-run-unlearn-finetune,NeurIPS 2023 - Machine Unlearning
15384,152543309,75.0,,0,9,/mohitgurnanirajesh/confusion-unlearning,NeurIPS 2023 - Machine Unlearning
15385,152542459,5.0,0.0,0,6,/marvelworld/toshi-k-rotate-and-marvel-pseudo-blend48-52,NeurIPS 2023 - Machine Unlearning
15386,144659258,814.0,,0,4,/lucasbruzzone/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15387,144670179,139.0,,1,3,/abramova/ps3-e22-simple-models-optuna-lb-correlation,Predict Health Outcomes of Horses
15388,144447470,453.0,,18,46,/jasonheesanglee/email-notification-colab-session-autoshutdown,Predict Health Outcomes of Horses
15389,143290532,129.0,,5,13,/moazeldsokyx/playgrounds3e22-ensemble-learning,Predict Health Outcomes of Horses
15390,143411399,336.0,,1,8,/nithinreddy90/equine-medical-diagnosis-with-random-forests,Predict Health Outcomes of Horses
15391,144025161,472.0,,2,12,/adelinmil/pg-s03e22-eda-fe,Predict Health Outcomes of Horses
15392,142743437,191.0,,1,6,/kuryakin/s3-e22-eda,Predict Health Outcomes of Horses
15393,143770245,194.0,0.8048780487804877,0,1,/kerrysun/lb-82317-pb-0-76818-lightgbm-oputna,Predict Health Outcomes of Horses
15394,142696581,41.0,0.7012195121951219,3,10,/daaadaaa/s3e22-eda-catboost-xgb-baseline,Predict Health Outcomes of Horses
15395,144426021,206.0,,2,13,/itsnobita/horse-health-prediction,Predict Health Outcomes of Horses
15396,147536126,133.0,,3,18,/nikhil1e9/s3-e22-full-feature-analysis,Predict Health Outcomes of Horses
15397,144601751,130.0,,0,1,/igoryashchenko/simple-solution-using-catboost,Predict Health Outcomes of Horses
15398,144847941,304.0,0.7987804878048782,0,2,/yuchan509/voting-model2,Predict Health Outcomes of Horses
15399,144588765,520.0,0.8475609756097561,10,20,/ankurlimbashia/pg-s3e22-simple-lightgbm,Predict Health Outcomes of Horses
15400,144751627,62.0,0.8292682926829268,6,16,/astitwaagarwal/horse-survival,Predict Health Outcomes of Horses
15401,144434370,63.0,0.823170731707317,1,9,/yuraslastya/2-separate-predictions-approach,Predict Health Outcomes of Horses
15402,143428529,68.0,,13,38,/egorkainov/eda-conclusions-visualization-catboost-rf,Predict Health Outcomes of Horses
15403,144117513,74.0,0.8475609756097561,0,0,/nhttinnguynbch/horse-survival,Predict Health Outcomes of Horses
15404,142922096,239.0,,1,28,/osamaabobakr/predict-health-outcomes-of-horses-85,Predict Health Outcomes of Horses
15405,143860938,555.0,0.7682926829268293,0,4,/krystianlata/playground-s03e22-horses,Predict Health Outcomes of Horses
15406,143615557,594.0,,0,11,/jominjae/using-smote-grid-lgbm,Predict Health Outcomes of Horses
15407,143937980,249.0,,0,1,/nagendramantrabuddi/health-outcome-of-horses,Predict Health Outcomes of Horses
15408,151883766,256.0,,13,39,/dumanmesut/happy-horses-eda-lgbm-xgb,Predict Health Outcomes of Horses
15409,152292873,197.0,0.823170731707317,23,54,/huseyinbaytar/horse,Predict Health Outcomes of Horses
15410,144906894,90.0,0.8475609756097561,0,35,/endofnight17j03/horses-health-prediction,Predict Health Outcomes of Horses
15411,142790286,198.0,,1,13,/taeefnajib/eda-horse-health-outcome-prediction,Predict Health Outcomes of Horses
15412,145023436,702.0,0.8475609756097561,0,6,/pixelshooter/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15413,143679106,154.0,0.7987804878048782,3,15,/apovidlo/s3-ep22-starting-baseline-with-autogluon-automl,Predict Health Outcomes of Horses
15414,144784209,521.0,0.7804878048780488,30,94,/kacperrabczewski/horse-health-a-beginner-friendly-guide,Predict Health Outcomes of Horses
15415,144529968,466.0,,0,6,/anzarwani2/horse-health-outcome-baseline,Predict Health Outcomes of Horses
15416,145303778,769.0,,0,3,/atom1991/predict-health-outcomes-of-horses-ps-s3e22,Predict Health Outcomes of Horses
15417,143120662,265.0,0.823170731707317,3,14,/krviswanathan/horse-health-eda-predictive-modelling,Predict Health Outcomes of Horses
15418,144156527,500.0,0.8109756097560975,0,0,/yateng/notebook962dd8b5aa,Predict Health Outcomes of Horses
15419,144571331,504.0,0.6585365853658537,0,0,/jamalghobrial/predicting-health-outcome-of-horses,Predict Health Outcomes of Horses
15420,144202693,34.0,,0,15,/bkowshik/automl-with-autogluon-horse-health-outcomes,Predict Health Outcomes of Horses
15421,144902573,473.0,,1,4,/brokerus/ml-health-outcomes-of-horses-4-models,Predict Health Outcomes of Horses
15422,144382294,451.0,0.8048780487804877,2,10,/emirbilir/playground-season-3-episode-22,Predict Health Outcomes of Horses
15423,144838453,667.0,0.8353658536585366,0,4,/ucas0v0zhuoqunli/automl-benchmark-horse,Predict Health Outcomes of Horses
15424,144887458,57.0,,1,4,/maximeperez/horse-survival-optuna,Predict Health Outcomes of Horses
15425,145028721,467.0,0.7865853658536586,10,63,/akioonodera/ps-3-22-lgbm-multiclass,Predict Health Outcomes of Horses
15426,143143516,97.0,0.8292682926829268,4,26,/mattop/ps-s3-e22-xgboost-preprocessing,Predict Health Outcomes of Horses
15427,143344953,591.0,0.8292682926829268,4,34,/eishkaran/shortest-code-possible,Predict Health Outcomes of Horses
15428,143374490,593.0,0.7682926829268293,0,6,/shreyanshibhatt/ps3e22-xgboost-easy-explanation,Predict Health Outcomes of Horses
15429,143213982,712.0,0.7865853658536586,1,11,/vaibhavsanepara/health-outcomes-of-horses-competition-eda,Predict Health Outcomes of Horses
15430,143546644,147.0,,2,9,/aaachen/ps3e22-xgbclassifer-lightgbm-catboost,Predict Health Outcomes of Horses
15431,143581059,27.0,0.7987804878048782,0,1,/eeeeee4563/s3e22-h2o-flow-with-data-prepared-in-kaggle,Predict Health Outcomes of Horses
15432,143091581,141.0,,3,9,/vaishakhraveendran/eda-and-base-season-3-episode-22,Predict Health Outcomes of Horses
15433,144341386,951.0,0.7865853658536586,0,5,/sergeyyakovlev1312/xgboost-somethibg-else,Predict Health Outcomes of Horses
15434,144639503,696.0,0.8292682926829268,6,31,/francescoliveras/ps-s3-e22-eda-model-en-es,Predict Health Outcomes of Horses
15435,144810702,566.0,0.7865853658536586,0,0,/jimmyknox/prediction4,Predict Health Outcomes of Horses
15436,143300971,300.0,0.6463414634146342,2,7,/yoshifumimiya/s3e22-randomforest-ver-1,Predict Health Outcomes of Horses
15437,142739681,96.0,,1,11,/rishabh15virgo/first-impression-data-understanding-eda-baseline,Predict Health Outcomes of Horses
15438,143529235,640.0,,0,3,/nicoletacilibiu/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15439,143200910,548.0,,0,15,/sasakitetsuya/try-adding-some-features,Predict Health Outcomes of Horses
15440,143234720,91.0,,5,38,/mcpenguin/ps3e22-eda-fe-prediction,Predict Health Outcomes of Horses
15441,166754589,474.0,,0,3,/wintersbae/playground-s3e22-predict-horse-survival,Predict Health Outcomes of Horses
15442,142947255,103.0,0.7682926829268293,0,2,/yunsuxiaozi/pss3e22-baseline,Predict Health Outcomes of Horses
15443,145040103,660.0,,2,6,/scientiapotentia/short-easy-horse-health-prediction-model,Predict Health Outcomes of Horses
15444,144891383,45.0,0.8170731707317073,0,2,/grantgonnerman/ps-e3-s22-eda-and-modeling,Predict Health Outcomes of Horses
15445,144891383,45.0,0.8048780487804877,0,2,/grantgonnerman/ps-e3-s22-eda-and-modeling,Predict Health Outcomes of Horses
15446,144891383,45.0,0.823170731707317,0,2,/grantgonnerman/ps-e3-s22-eda-and-modeling,Predict Health Outcomes of Horses
15447,144921093,295.0,0.8170731707317073,2,10,/alvinleenh/ps3e22-horse-health-lgb-baseline,Predict Health Outcomes of Horses
15448,143605438,477.0,,0,6,/hongseoi/se22-kr-histgradientboostingclassifier,Predict Health Outcomes of Horses
15449,145019692,301.0,,0,3,/pradhammummaleti/horse-health-lgbm-classifier-with-k-fold,Predict Health Outcomes of Horses
15450,151948549,108.0,,8,68,/iqbalsyahakbar/ps3e22-multi-class-classification-for-beginners,Predict Health Outcomes of Horses
15451,142911920,1024.0,,1,8,/pratul007/predictive-modeling-using-ensemble-technique,Predict Health Outcomes of Horses
15452,143006686,1174.0,0.8170731707317073,0,3,/abhijit89kumar/horsihealth,Predict Health Outcomes of Horses
15453,143390207,1175.0,0.8170731707317073,3,11,/amanmukati/health-outcomes-horses,Predict Health Outcomes of Horses
15454,143846000,736.0,,0,3,/matthewmaddock/ps-s3-e22-random-forest-hyperparameter-tuning,Predict Health Outcomes of Horses
15455,142712738,565.0,,0,5,/stpeteishii/pss3-ep22-histplot,Predict Health Outcomes of Horses
15456,145666092,286.0,,0,0,/andrybevcuk/pca-as-prep-for-classefication,Predict Health Outcomes of Horses
15457,148006121,162.0,,1,4,/aniskhan25/playground-series-s03e22,Predict Health Outcomes of Horses
15458,145033278,247.0,0.8109756097560975,0,3,/livecle/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15459,144999182,815.0,0.7865853658536586,0,9,/commentsm/horse-health,Predict Health Outcomes of Horses
15460,144946318,1017.0,,1,4,/xpehutta/deep-nn-with-pytorch,Predict Health Outcomes of Horses
15461,142911703,584.0,0.8109756097560975,1,9,/jokerinthapack/optuna-searching,Predict Health Outcomes of Horses
15462,142927015,586.0,0.8048780487804877,0,4,/hli111111/cleaner-code-sklearn-impute-model-ensemble-pipe,Predict Health Outcomes of Horses
15463,143478588,439.0,0.8109756097560975,0,2,/kavin1125/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15464,144186711,606.0,,0,3,/gaelherc/predict-horses-health-notebook,Predict Health Outcomes of Horses
15465,144894623,525.0,,0,3,/halanassar/horses-health-outcomes,Predict Health Outcomes of Horses
15466,145134357,220.0,0.7987804878048782,0,3,/anthonyweaver/health-horses-catboost-3-22,Predict Health Outcomes of Horses
15467,142929920,635.0,0.8048780487804877,5,14,/jeremyhaakenson/horse-pca-and-xgboost,Predict Health Outcomes of Horses
15468,144768807,489.0,,0,4,/fathyalin/easy-approch-80-487,Predict Health Outcomes of Horses
15469,143054121,388.0,,0,2,/akiyukikouyama/ps3e22-eda-and-build-baseline,Predict Health Outcomes of Horses
15470,144175208,362.0,,2,9,/wonmorgan/s3e24-lightgbm-baseline,Predict Health Outcomes of Horses
15471,144055564,831.0,0.8048780487804877,3,10,/neupane9sujal/catboost-model-starter,Predict Health Outcomes of Horses
15472,143664037,405.0,0.8048780487804877,2,8,/nathaniellybrand/s3-ep22-lgbm-feature-selection-baseline,Predict Health Outcomes of Horses
15473,143692278,642.0,,0,4,/abidammar/playgrounds3e22-base-model,Predict Health Outcomes of Horses
15474,144101991,983.0,,0,1,/jamiedonnelly/sparse-feature-model,Predict Health Outcomes of Horses
15475,143914935,982.0,,0,1,/bluewall/horsey-outcomes,Predict Health Outcomes of Horses
15476,144460074,561.0,0.7926829268292683,0,6,/ikonuhov/s3e22-optuna-big-enssemble-rus,Predict Health Outcomes of Horses
15477,144569484,455.0,,10,23,/lusfernandotorres/s03e22-simple-approach-ensemble-optuna,Predict Health Outcomes of Horses
15478,144689229,3.0,,7,6,/jasmeendahak/health-of-horses,Predict Health Outcomes of Horses
15479,144824892,739.0,0.7317073170731707,1,6,/jacobgvu/ps-s3e22,Predict Health Outcomes of Horses
15480,144934305,1076.0,,0,4,/aashishshrestha11/predicted-health-horses-outcome,Predict Health Outcomes of Horses
15481,142737261,583.0,,0,7,/gauravduttakiit/pss3e22-lazypredict,Predict Health Outcomes of Horses
15482,143155315,264.0,,6,11,/gabrielbuchhorn/something-is-wrong,Predict Health Outcomes of Horses
15483,143537332,396.0,0.7987804878048782,0,3,/hudasaleh1/s3e22-eda-stacking-pycaret,Predict Health Outcomes of Horses
15484,144047698,610.0,0.7804878048780488,1,15,/enricomanosperti/health-of-horses-eda-processing-model,Predict Health Outcomes of Horses
15485,144204931,510.0,0.7987804878048782,0,3,/bryan2001/health-outcomes-of-horses-prediction,Predict Health Outcomes of Horses
15486,143826652,517.0,,2,9,/mariodelacruzjr/analysis,Predict Health Outcomes of Horses
15487,144638382,459.0,0.6707317073170732,0,3,/dristantadas/nn-horse,Predict Health Outcomes of Horses
15488,144747980,461.0,0.7865853658536586,1,7,/mehmetarifkuzgunnn/ps3e22-horse-health-prediction-using-lgbm,Predict Health Outcomes of Horses
15489,145003432,573.0,0.75,0,9,/kaviga/simple-eda-lgbm-xgbm-logreg,Predict Health Outcomes of Horses
15490,144920844,742.0,0.7987804878048782,10,36,/dennisbucklin/health-outcomes-for-horses-competition,Predict Health Outcomes of Horses
15491,144926207,743.0,0.7987804878048782,0,11,/adityakishor1/outcomes-of-health-for-horses-competition,Predict Health Outcomes of Horses
15492,144960860,746.0,0.7987804878048782,0,3,/maheshmohna/task-2,Predict Health Outcomes of Horses
15493,143345157,755.0,,1,16,/chrisk321/health-outcomes-of-horses-eda-xgblinear-submit,Predict Health Outcomes of Horses
15494,144036459,604.0,0.7743902439024389,5,31,/achusanjeev/best-features-in-this-dataset,Predict Health Outcomes of Horses
15495,144983646,688.0,0.6646341463414634,0,3,/mozammil12/horse-health-prediction-ann-boosting,Predict Health Outcomes of Horses
15496,145028797,922.0,,0,1,/ahmedgamalibrahimali/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15497,144634733,1015.0,0.7926829268292683,0,5,/tuhinm2002/horse-health-eda-80-acc,Predict Health Outcomes of Horses
15498,144720229,846.0,0.7926829268292683,0,3,/dsmeena/predict-horse-status-onehotencoder-imputer-xgb,Predict Health Outcomes of Horses
15499,143881399,195.0,,0,7,/eastonlarson/playground-series-s3-e22-notebook,Predict Health Outcomes of Horses
15500,151363313,531.0,,0,10,/alizgrdede/horse-health-playground-series-3-22,Predict Health Outcomes of Horses
15501,142926806,1274.0,0.7804878048780488,0,4,/sunnywhile/the-simplest-nn-by-pytorch,Predict Health Outcomes of Horses
15502,142883567,825.0,0.7621951219512195,6,29,/tatianakushniruk/horses-health-outcomes-eda-lightgbm,Predict Health Outcomes of Horses
15503,142866239,971.0,0.7865853658536586,2,4,/thomasmeiner/playground-s3e22-auto-eda-ml-with-bluecast,Predict Health Outcomes of Horses
15504,144646392,901.0,0.676829268292683,2,14,/klyushnik/outcomes-vol-3,Predict Health Outcomes of Horses
15505,143244355,350.0,0.7865853658536586,3,16,/ignaciotigurius/multiclass-predict-health-of-xgb-cat-lgb,Predict Health Outcomes of Horses
15506,143557358,227.0,,2,6,/armanzhalgasbayev/horse-health-outcome-prediction,Predict Health Outcomes of Horses
15507,144094046,1135.0,0.75,1,8,/barbagrande007/bbg007-s3e22-horsesurvival,Predict Health Outcomes of Horses
15508,144080778,771.0,,0,6,/eminztrk/predict-health-outcomes-of-horses-flaml-automl,Predict Health Outcomes of Horses
15509,145023725,250.0,,1,4,/jrkhops/playground-s3-ep22,Predict Health Outcomes of Horses
15510,143051859,1108.0,0.7439024390243903,1,7,/trhgquan/ps3e22-xgboost-and-feature-selection,Predict Health Outcomes of Horses
15511,143887857,1317.0,,2,7,/prajyotbirajdar/horse-life-prediction,Predict Health Outcomes of Horses
15512,143146695,944.0,,0,2,/kotukw/health-outcomes-of-horses-eda,Predict Health Outcomes of Horses
15513,144759960,911.0,0.7682926829268293,2,8,/atuljo/a-simple-model,Predict Health Outcomes of Horses
15514,144097367,509.0,0.7134146341463414,0,6,/lonewalker29/pytorch-neural-network-baseline,Predict Health Outcomes of Horses
15515,154238131,127.0,,1,10,/tushirsahu/automl-and-horse-health-outcomes,Predict Health Outcomes of Horses
15516,146595962,792.0,,8,26,/kumudithasilva/horse-health-multiclass-classification,Predict Health Outcomes of Horses
15517,144976310,932.0,,0,5,/anubhavtyagi1212/horse-care-pycaret-0-78048,Predict Health Outcomes of Horses
15518,145024138,1104.0,,2,5,/osamaakhaled/horse-health-playground-s3-e22,Predict Health Outcomes of Horses
15519,142718340,933.0,,0,3,/vladislavonufrienko/pss3e22-eda-catboostclassifier,Predict Health Outcomes of Horses
15520,143912248,1163.0,0.7560975609756099,1,5,/debamritapaul/playground-s3-e22,Predict Health Outcomes of Horses
15521,144430453,1286.0,0.7621951219512195,0,5,/satishpb/health-outcome-of-horses,Predict Health Outcomes of Horses
15522,145227038,1116.0,,0,2,/pranjalameta/health-detection-of-horse-with-different-modals,Predict Health Outcomes of Horses
15523,143679087,940.0,0.7743902439024389,1,17,/kanikasinghaljindal/r-notebook,Predict Health Outcomes of Horses
15524,143831877,313.0,0.7621951219512195,5,14,/thomasheitz/xgboost-simple-code-with-finetuning,Predict Health Outcomes of Horses
15525,144860005,379.0,0.7743902439024389,1,12,/kubes57/predicting-health-outcomes-of-horses,Predict Health Outcomes of Horses
15526,144693372,1140.0,0.7743902439024389,0,5,/rohit265/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15527,144415085,926.0,,2,16,/philopateergeorgei/eda-random-forest,Predict Health Outcomes of Horses
15528,142692653,899.0,,0,3,/mohitguptaasu/s3e22-start-quickly-baseline-model,Predict Health Outcomes of Horses
15529,143215935,1048.0,0.7621951219512195,0,8,/synchrocyclotron/catboost-baseline-solution,Predict Health Outcomes of Horses
15530,143327957,937.0,,0,3,/janithkariyawasam/horse-health-competition,Predict Health Outcomes of Horses
15531,143738612,834.0,0.7682926829268293,0,8,/rswaswa/predict-health-outcomes-of-horses-competition,Predict Health Outcomes of Horses
15532,143834264,942.0,0.7682926829268293,2,10,/chiranjeevisrinivas/playgroundseries-s3e22,Predict Health Outcomes of Horses
15533,144452459,731.0,,1,15,/muhannadmansour/eda-multi-class-classification,Predict Health Outcomes of Horses
15534,144041449,1099.0,,0,4,/shivampal7722/hourse-health-prediction,Predict Health Outcomes of Horses
15535,144876409,1191.0,,2,6,/benzilla987/ps-s3-ep22-eda-modeling-submission,Predict Health Outcomes of Horses
15536,145016098,988.0,0.7682926829268293,0,4,/prathameshprege/ps-s3-e22-predict-health-outcomes-horse,Predict Health Outcomes of Horses
15537,149803851,924.0,,13,42,/sjagkoo7/health-of-horses-s3-ep22-xgb-lgbm-catboost,Predict Health Outcomes of Horses
15538,151361483,1199.0,,0,1,/jaci24/playground-s3e22-predict-health-outcome-of-horse,Predict Health Outcomes of Horses
15539,145021478,1158.0,0.7682926829268293,0,7,/ompawar9174/horse-survival-random-forest,Predict Health Outcomes of Horses
15540,143056612,1145.0,0.7621951219512195,2,11,/josephinelsy/horses-health-prediction,Predict Health Outcomes of Horses
15541,143673603,1202.0,0.7621951219512195,0,3,/athirasudevankeerthy/predict-health-outcomes-of-horses-competition,Predict Health Outcomes of Horses
15542,145618520,943.0,,0,1,/witoldnowogrski/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15543,144111075,1271.0,,11,20,/jrsuri/predict-health-eda,Predict Health Outcomes of Horses
15544,144709867,1236.0,0.7317073170731707,2,18,/danielgalili/playground-series-season-3-episode-22,Predict Health Outcomes of Horses
15545,144709867,1236.0,0.7317073170731707,2,18,/danielgalili/playground-series-season-3-episode-22,Predict Health Outcomes of Horses
15546,144709867,1236.0,0.7317073170731707,2,18,/danielgalili/playground-series-season-3-episode-22,Predict Health Outcomes of Horses
15547,144361867,1227.0,0.7621951219512195,4,13,/ahmedali6102001/health-outcomes-with-python,Predict Health Outcomes of Horses
15548,144420284,615.0,0.7621951219512195,0,3,/pohzixiang/horse-health-prediction-zx,Predict Health Outcomes of Horses
15549,145007983,855.0,,1,5,/vayllanvictordesouza/outcome-of-horses,Predict Health Outcomes of Horses
15550,144919645,1282.0,,0,3,/keenanzhuo/horse-health-simple-rfe-ensemble,Predict Health Outcomes of Horses
15551,143749894,1299.0,0.7134146341463414,0,2,/fadynabilmofeed/hourse,Predict Health Outcomes of Horses
15552,144277853,727.0,,6,9,/singhayush16/horse-health-prediction,Predict Health Outcomes of Horses
15553,144707865,1343.0,0.7256097560975608,0,4,/afedorchuk/k-nearest-illness-neighbors,Predict Health Outcomes of Horses
15554,144104490,686.0,,0,7,/ahmetyldrr/predict-eda-randomforest-0-75-00,Predict Health Outcomes of Horses
15555,144964960,1043.0,0.676829268292683,0,8,/prasadmeesala/horses-health-prediction-knn-classifier,Predict Health Outcomes of Horses
15556,143067095,1129.0,0.75,0,7,/minjonyfilm/health-outcomes-of-horses-prediction,Predict Health Outcomes of Horses
15557,143834174,684.0,,0,13,/samuelgachuhi/gachuhi-ml-prediction-horses-health,Predict Health Outcomes of Horses
15558,147266246,1262.0,,0,1,/scook4242/horses,Predict Health Outcomes of Horses
15559,144666177,1153.0,0.75,0,1,/ashwaniraj679/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15560,144695752,1073.0,,0,3,/shahvinit/happyhorselife2,Predict Health Outcomes of Horses
15561,145174215,1126.0,0.7134146341463414,2,6,/suraj520/multi-approaches-rf-stacking-optuna-k-fold,Predict Health Outcomes of Horses
15562,144448173,1349.0,0.7012195121951219,0,1,/matthewsfarmer/ps-s3-e22-horse-survival-prediction,Predict Health Outcomes of Horses
15563,145048125,1327.0,,0,1,/hosesoh/micro-averaged-f1-score-predicting-horse-health,Predict Health Outcomes of Horses
15564,144978754,1089.0,,0,1,/vartikajaiswal17/notebook69150155be,Predict Health Outcomes of Horses
15565,143299147,1052.0,,1,11,/soyabulislamlincoln/horse-health-basic-simple-eda,Predict Health Outcomes of Horses
15566,143771137,1252.0,0.7317073170731707,0,4,/natchaphonkamhaeng/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15567,144442785,1064.0,,4,30,/magantiit/horse-predictions-using-rf-classification,Predict Health Outcomes of Horses
15568,142814480,1107.0,,0,3,/nakamurasyuta/ps-s3-ep22-for-now-submit-with-lightgbm,Predict Health Outcomes of Horses
15569,142739337,1416.0,0.6646341463414634,1,8,/yapwh1208/playground-s3e22-rf,Predict Health Outcomes of Horses
15570,144960192,1311.0,0.7256097560975608,2,1,/irfanarisani/based-for-horse-survival-prediction,Predict Health Outcomes of Horses
15571,144965198,1306.0,0.7012195121951219,1,2,/tsihoryjigdaliaenoch/multiclass-strategy-feature-engineering,Predict Health Outcomes of Horses
15572,161411924,1230.0,,0,5,/tanyajain3108/health-outcome-random-forest,Predict Health Outcomes of Horses
15573,144944824,1395.0,,0,8,/akshatarya/horse-care-checklist,Predict Health Outcomes of Horses
15574,143531897,1321.0,0.7012195121951219,0,10,/azadshahvaladov/using-only-gridsearch-and-a-few-features,Predict Health Outcomes of Horses
15575,145992053,1432.0,,0,3,/sagayaabinesh/predict-health-outcomes-of-horses-2-ml-buddies,Predict Health Outcomes of Horses
15576,144616424,1364.0,,0,4,/azraimohamad/horse-survival-eda-prediction,Predict Health Outcomes of Horses
15577,142744129,1426.0,0.6280487804878049,0,3,/geraldnyeo/ps3e22-eda-baseline,Predict Health Outcomes of Horses
15578,143990126,1461.0,,0,2,/ebraheemriad/notebookd6f901a34d,Predict Health Outcomes of Horses
15579,144519731,1435.0,0.6097560975609756,0,1,/hemakarapu/predict-health-outcomes-horses,Predict Health Outcomes of Horses
15580,145013953,1469.0,0.5792682926829268,0,6,/asif00/horsey-in-the-random-forest,Predict Health Outcomes of Horses
15581,142788975,1454.0,0.4939024390243902,0,2,/tracyporter/play-3-22-jax-mn-lr,Predict Health Outcomes of Horses
15582,143425039,1465.0,,0,6,/leonhardpiff/horsing-around-with-neural-networks,Predict Health Outcomes of Horses
15583,143604466,1466.0,0.5182926829268293,0,8,/junjuly123/horse-health-prediction-sklearn-deep-learning,Predict Health Outcomes of Horses
15584,144988103,1482.0,0.5,0,9,/nisargbhatt/how-rse-you-doin-complete-eda-and-ml,Predict Health Outcomes of Horses
15585,143444868,1477.0,0.4634146341463415,0,9,/warriorwizard/ps3-e22-predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15586,144548802,1476.0,,0,6,/kicjung/playground-s3-e22-predict-health-outcomes-horses,Predict Health Outcomes of Horses
15587,143045677,1489.0,,2,10,/jocelyndumlao/exploring-horse-survival-prediction,Predict Health Outcomes of Horses
15588,143596873,1491.0,,0,3,/padmavathishilpa/health-outcome-of-horses,Predict Health Outcomes of Horses
15589,143805344,1494.0,0.4634146341463415,0,4,/anoopjohny/horse-health-outcome-prediction,Predict Health Outcomes of Horses
15590,145006094,1506.0,,0,6,/mohamedsaber121/predict-health-outcomes-of-horses-nootbook-asta2,Predict Health Outcomes of Horses
15591,144130982,1518.0,,1,4,/ammarahabib/horses-health-outcomes,Predict Health Outcomes of Horses
15592,143415419,1531.0,,33,41,/muhammadali786/horse-health-prediction-using-random-forest-ps3e22,Predict Health Outcomes of Horses
15593,143749424,1521.0,0.3597560975609756,0,5,/malikmuhammadahmed/predict-health-outcomes-of-horses,Predict Health Outcomes of Horses
15594,144649900,16.0,,5,18,/pablormier/op2-biologically-aware-dimensionality-reduction,Open Problems – Single-Cell Perturbations
15595,143418784,34.0,,0,18,/yoshifumimiya/analysis-with-normal-distribution-and-ranking,Open Problems – Single-Cell Perturbations
15596,154113225,10.0,,2,10,/mori123/single-cell-perturbations-part-a-model-training,Open Problems – Single-Cell Perturbations
15597,153150805,25.0,,2,19,/ivanlydkin/dummy-cell-normalization-idea,Open Problems – Single-Cell Perturbations
15598,153091491,207.0,0.5304217573539348,0,0,,Open Problems – Single-Cell Perturbations
15599,153070483,206.0,,0,11,,Open Problems – Single-Cell Perturbations
15600,145274654,197.0,,0,5,,Open Problems – Single-Cell Perturbations
15601,148661450,58.0,0.5884104234062907,0,7,/jjleesunny/0-583-ensemble-submition-op,Open Problems – Single-Cell Perturbations
15602,150481827,59.0,0.5862625684296521,0,0,/hideyukizushi/op-train-inf-exp003-lstm,Open Problems – Single-Cell Perturbations
15603,143253431,178.0,,0,4,/insiyajafferji/op-single-cell-dataset-and-cell-type-distribution,Open Problems – Single-Cell Perturbations
15604,148820638,182.0,,0,6,/shadie520/chemberta-nn-regression,Open Problems – Single-Cell Perturbations
15605,147071460,187.0,0.5904803671431449,0,5,/chesterx/op2-better-weights-slightly-better-than-0-59,Open Problems – Single-Cell Perturbations
15606,147914014,31.0,0.638006383302763,0,13,/mirenaborisova/scp-mean-median-quantile-lb-0-638,Open Problems – Single-Cell Perturbations
15607,143859797,237.0,0.6042557088472856,0,11,,Open Problems – Single-Cell Perturbations
15608,147808945,494.0,,1,7,/wguesdon/op2-smiles-and-gene-ontology-encoding-xgboost,Open Problems – Single-Cell Perturbations
15609,147069609,229.0,,2,24,/awater1223/op2-00-basic-metadata-eda,Open Problems – Single-Cell Perturbations
15610,150999849,208.0,0.6292264892202493,0,12,/lonnieqin/single-cell-perturbation-with-conv1d,Open Problems – Single-Cell Perturbations
15611,147833962,95.0,0.589805695242516,0,1,/miteshadake/op2-eda-linearsvr-regressor,Open Problems – Single-Cell Perturbations
15612,150574046,166.0,,0,1,,Open Problems – Single-Cell Perturbations
15613,150785101,107.0,,0,0,/marangoz/data-tan-ma,Open Problems – Single-Cell Perturbations
15614,143704241,50.0,,0,12,/vendekagonlabs/op2-single-cell-eda-10x-multiome,Open Problems – Single-Cell Perturbations
15615,152623819,126.0,,2,16,,Open Problems – Single-Cell Perturbations
15616,143494741,804.0,,5,29,/alekseytrepetsky/create-chemberta-embed,Open Problems – Single-Cell Perturbations
15617,150325374,693.0,,0,1,/shunsukekikuchi/smiles,Open Problems – Single-Cell Perturbations
15618,145273445,159.0,0.5998711658638032,0,3,,Open Problems – Single-Cell Perturbations
15619,148467184,119.0,,0,3,,Open Problems – Single-Cell Perturbations
15620,152396580,108.0,0.5375425012016398,1,12,,Open Problems – Single-Cell Perturbations
15621,147504961,118.0,,0,4,,Open Problems – Single-Cell Perturbations
15622,147506022,73.0,,1,6,,Open Problems – Single-Cell Perturbations
15623,152955686,30.0,,0,1,/frenio/open-problems-super-ensemble-submission,Open Problems – Single-Cell Perturbations
15624,158040193,20.0,,0,4,/jalilnourisa/post-eda,Open Problems – Single-Cell Perturbations
15625,154081699,471.0,0.6206801331866818,0,1,/masaishi/opscp-m-nb019,Open Problems – Single-Cell Perturbations
15626,151859071,68.0,,0,1,/al2953072/only-lb-dont-select-as-final-submission-ens-f65bbe,Open Problems – Single-Cell Perturbations
15627,150198053,24.0,,3,8,/makio323/fork-of-nlp-regression-12a31a-0-594,Open Problems – Single-Cell Perturbations
15628,143908842,325.0,,0,13,/qihuaz/mean-rowwise-root-mean-squared-error,Open Problems – Single-Cell Perturbations
15629,144582685,488.0,,0,10,/dangnguyen97/linearsvr,Open Problems – Single-Cell Perturbations
15630,149873551,285.0,,2,21,/altynbulmers/scp-blend-0-580,Open Problems – Single-Cell Perturbations
15631,147920287,449.0,,5,14,/superdanielshao/op2-multivi-for-additional-cell-embeddings,Open Problems – Single-Cell Perturbations
15632,151306569,286.0,0.6046154462217056,0,1,/gefen8/pyboost-secret-grandmaster-s-tool,Open Problems – Single-Cell Perturbations
15633,151308406,265.0,0.6030079569744754,5,24,/stasborodynkin/pyboost-secret-grandmaster-s-tool,Open Problems – Single-Cell Perturbations
15634,144293041,18.0,0.6292265380324205,5,46,/ambrosm/scp-quickstart,Open Problems – Single-Cell Perturbations
15635,145728730,436.0,,0,2,/inoue0426/autoencoder-from-known-comb-to-unknown-w-drug,Open Problems – Single-Cell Perturbations
15636,145192088,23.0,0.6303915025128798,4,14,/masato114/scp-quickstart-another-cv-strategy,Open Problems – Single-Cell Perturbations
15637,144691977,364.0,,1,8,/laurasisson/exploring-the-lincs-gene-metadata,Open Problems – Single-Cell Perturbations
15638,152037919,423.0,0.6179341758609697,7,27,/enricomanosperti/single-cell-perturbations,Open Problems – Single-Cell Perturbations
15639,151637865,369.0,0.6058090486988961,0,3,/dxdydx/pyboost-secret-grandmaster-s-tool,Open Problems – Single-Cell Perturbations
15640,152274449,433.0,0.608200344459828,0,17,/nazimcherpanov/single-cell-perturbations,Open Problems – Single-Cell Perturbations
15641,146932962,431.0,,0,1,/gkhanergen/cnn-model,Open Problems – Single-Cell Perturbations
15642,145511964,491.0,,0,3,/serhiikharchuk/my-chatexpruen-gptj-with-gradio,Open Problems – Single-Cell Perturbations
15643,145273285,507.0,,0,4,/doxonjohnson/streamlined-baseline-approach-6eb25a,Open Problems – Single-Cell Perturbations
15644,151399103,495.0,0.6042645329109618,0,5,/pavrostiva/pyboost-secret-grandmaster-s-tool,Open Problems – Single-Cell Perturbations
15645,143322339,626.0,,6,33,/zmcxjt/streamlined-baseline-approach,Open Problems – Single-Cell Perturbations
15646,142801251,670.0,,2,12,/hiramcho/open-problems-chemical-descriptors-langchain,Open Problems – Single-Cell Perturbations
15647,148383710,726.0,,0,3,/raniahelmy/op-scp-eda,Open Problems – Single-Cell Perturbations
15648,144999584,601.0,0.7065350344386547,3,12,/pavelabr/explore-dispersions-of-p-values,Open Problems – Single-Cell Perturbations
15649,150337685,766.0,,0,2,/aemulcahy/using-pywgcna-to-find-gene-modules,Open Problems – Single-Cell Perturbations
15650,143942977,796.0,0.6141068228117498,2,8,/bhavesh1335/open-problems-single-cell-perturbations-notebook,Open Problems – Single-Cell Perturbations
15651,151963138,729.0,0.616108438420693,0,1,/sridharnomulas/sridhar-pt,Open Problems – Single-Cell Perturbations
15652,147271317,740.0,,2,5,/xueerchen/first-look-at-scgpt-s-genes,Open Problems – Single-Cell Perturbations
15653,145260049,791.0,0.6319163734936666,1,3,/rafaelmmoraes/op2-training-base-models,Open Problems – Single-Cell Perturbations
15654,148189977,873.0,,0,3,/josephkibira/single-cell-pertubations-competitions,Open Problems – Single-Cell Perturbations
15655,152991584,889.0,0.6961754276655335,0,0,/goodyvesning/op-scp-lgbm,Open Problems – Single-Cell Perturbations
15656,145507226,874.0,,0,2,/joelsiby02/abt-randomforestregressor,Open Problems – Single-Cell Perturbations
15657,146696211,945.0,,0,16,/willianpina/competition-overview-new-explanations,Open Problems – Single-Cell Perturbations
15658,143165959,1023.0,,0,8,/colewelkins/pert30,Open Problems – Single-Cell Perturbations
15659,146478823,967.0,,0,1,/alinacram/pytorch-solution,Open Problems – Single-Cell Perturbations
15660,152710964,1010.0,0.6660089955919086,0,0,/vinitkp/eda-baseline-s,Open Problems – Single-Cell Perturbations
15661,150578622,1027.0,,0,4,/scienceenthusiast/effect-of-cell-pertubations-model,Open Problems – Single-Cell Perturbations
15662,151351067,1028.0,0.6661393157420359,0,9,/bhanupratapbiswas/open-problems-single-cell-perturbations,Open Problems – Single-Cell Perturbations
15663,146478935,985.0,,1,6,/jeskowagner/converting-input-files-to-anndata,Open Problems – Single-Cell Perturbations
15664,143169320,987.0,,0,30,/jocelyndumlao/cell-perturbations-insights-analysis,Open Problems – Single-Cell Perturbations
15665,153066677,1007.0,0.6669924654198259,0,3,/bbhaswati/regression-with-neural-network-in-pytorch,Open Problems – Single-Cell Perturbations
15666,143231920,1078.0,,0,15,/hosen42/open-problems-single-cell-perturbations,Open Problems – Single-Cell Perturbations
15667,143398015,1081.0,,0,7,/laxminarayanasahu/single-cell-patribution,Open Problems – Single-Cell Perturbations
15668,143391772,1083.0,0.9342849983622048,1,14,/amanmukati/single-cells-perturbations-1,Open Problems – Single-Cell Perturbations
15669,144159965,5.0,,0,6,/jonathanchan/lux-ai-challenge-neurips-23-tutorial-python,Lux AI Season 2 - NeurIPS Stage 2
15670,150045255,36.0,,0,5,/aliibrahimali/easly-notebook-feature-engineering-catboost,Linking Writing Processes to Writing Quality
15671,158385371,1.0,,0,0,/tomooinubushi/reduce-unseen-test-events-with-ftfy,Linking Writing Processes to Writing Quality
15672,145990880,77.0,,2,19,/ravi20076/writingquality-preprocesseddataset,Linking Writing Processes to Writing Quality
15673,154299545,42.0,,5,17,/raki21/essay-reconstruction-error-in-word-count,Linking Writing Processes to Writing Quality
15674,158395648,18.0,,0,3,/takai380/typing-debertav3-baseline-infer,Linking Writing Processes to Writing Quality
15675,146770871,426.0,,0,5,/kentatanaka1data/eda-distribution-of-train-dataset,Linking Writing Processes to Writing Quality
15676,156293634,491.0,0.5834935059579553,0,4,/watehell/lightgbm-with-simple-preprocess,Linking Writing Processes to Writing Quality
15677,155560355,473.0,0.5841961259805633,4,34,/iurigabriel/lgbm-xgboost,Linking Writing Processes to Writing Quality
15678,158377354,72.0,,0,0,/yamanity/function-convert-to-timeseries-data-1,Linking Writing Processes to Writing Quality
15679,148032777,81.0,0.6087180437977766,0,10,/awqatak/simple-average-blend-in-a-single-cell,Linking Writing Processes to Writing Quality
15680,160743744,427.0,,4,17,/keishibata/lwpwq-simple-eda-en,Linking Writing Processes to Writing Quality
15681,145842420,75.0,1.0094222232325285,2,8,/utm529fg/lwpwq-eng-initial-eda,Linking Writing Processes to Writing Quality
15682,145154239,404.0,0.6598685538037264,4,24,/takaito/lwpwq-public-baseline-notebook,Linking Writing Processes to Writing Quality
15683,149341939,186.0,,2,7,/natsumiarai/first-hisui-lwp-eda-ja-en,Linking Writing Processes to Writing Quality
15684,145349467,206.0,,0,12,/dangnguyen97/h2o-hyperparameters-grid-search,Linking Writing Processes to Writing Quality
15685,145682194,211.0,,2,22,/akscodes/eda-and-feature-engineering-keystroke-measures,Linking Writing Processes to Writing Quality
15686,145626003,236.0,0.7813083719419215,0,3,/yuriao/lgbm-baseline,Linking Writing Processes to Writing Quality
15687,146765252,286.0,0.6901103447712963,0,6,/ianchute/1-univariate-model,Linking Writing Processes to Writing Quality
15688,148980366,338.0,,0,2,/joehirose/eda-writing-process-as-image-time-x-cursor-pos,Linking Writing Processes to Writing Quality
15689,145805942,340.0,,4,42,/abhranta/lgbm-finetuning-with-optuna,Linking Writing Processes to Writing Quality
15690,146654473,608.0,0.6116418936202828,0,5,/sooyoungher/basemodel-ver02-writing-quality,Linking Writing Processes to Writing Quality
15691,146725157,405.0,0.7347583790424198,0,4,/luispintoc/sample-submission,Linking Writing Processes to Writing Quality
15692,157542144,767.0,0.6663995958525657,0,6,/showering/catboost,Linking Writing Processes to Writing Quality
15693,152781071,811.0,,0,4,/magnussesodia/writing-processes-eda,Linking Writing Processes to Writing Quality
15694,157406139,753.0,,0,12,/jaloeffe92/fasttext-linkingwriting-prcs-to-writing-quality,Linking Writing Processes to Writing Quality
15695,145675025,714.0,0.6133568302870605,15,95,/hengzheng/link-writing-simple-lgbm-baseline,Linking Writing Processes to Writing Quality
15696,155985240,720.0,0.5812569685280746,4,39,/snnclsr/581-3-models-optimized-weights-165-features,Linking Writing Processes to Writing Quality
15697,152376339,873.0,0.7720694303051548,0,0,/rishabh15virgo/writing-quality-eda-multiclass-all-models-baseline,Linking Writing Processes to Writing Quality
15698,146820143,639.0,0.610629173068604,2,13,/somesh88/pycaret-baseline-eda-writing-quality,Linking Writing Processes to Writing Quality
15699,147402380,655.0,0.6630123772465079,0,5,/adityaparikh668/xgboost-tuning-feature-extraction,Linking Writing Processes to Writing Quality
15700,149581501,661.0,0.6139584562034309,0,1,/tanishphopalkar/essay-quality-boosted-trees-model,Linking Writing Processes to Writing Quality
15701,146553120,695.0,,1,21,/docxian/writing-processes-2-quality-starter,Linking Writing Processes to Writing Quality
15702,155899540,1013.0,0.5824049716608262,0,4,/manikantasanjayv/catboost-xgboost-regressor,Linking Writing Processes to Writing Quality
15703,155899540,1013.0,0.5824049716608262,0,4,/manikantasanjayv/catboost-xgboost-regressor,Linking Writing Processes to Writing Quality
15704,155899540,1013.0,0.5824049716608262,0,4,/manikantasanjayv/catboost-xgboost-regressor,Linking Writing Processes to Writing Quality
15705,155899540,1013.0,0.5824049716608262,0,4,/manikantasanjayv/catboost-xgboost-regressor,Linking Writing Processes to Writing Quality
15706,155904804,832.0,,0,5,/taichiuemura/understanding-feature-generation-functions,Linking Writing Processes to Writing Quality
15707,157130806,952.0,0.5843946224628622,0,10,/haris33/linking-writing,Linking Writing Processes to Writing Quality
15708,153209366,601.0,0.971045889244074,0,0,/amer77228833f/phase1,Linking Writing Processes to Writing Quality
15709,152126658,844.0,0.6086602113834246,13,26,/neupane9sujal/quality-of-writing-attempt-to-conformal-prediction,Linking Writing Processes to Writing Quality
15710,145384526,1036.0,,1,15,/oreehovich3/the-longer-the-better,Linking Writing Processes to Writing Quality
15711,145161945,1156.0,0.6598685538037264,0,9,/nhttinnguynbch/lwpwq-public-baseline-notebook,Linking Writing Processes to Writing Quality
15712,147963680,1213.0,,6,30,/furduisorinoctavian/short-eda-plotting-data-according-to-score,Linking Writing Processes to Writing Quality
15713,150830890,1252.0,0.6148915415451615,0,6,/synful/catboost-default-hyperparameters-cv-0-56-lb-0-61,Linking Writing Processes to Writing Quality
15714,148033906,1268.0,0.6042503920362661,0,3,/muranstr/writing-processes-to-quality-baseline,Linking Writing Processes to Writing Quality
15715,155671934,1309.0,0.6047913422109128,0,2,/huhuajin1/writing-processes-to-quality-baseline,Linking Writing Processes to Writing Quality
15716,155671934,1309.0,0.6047913422109128,0,2,/huhuajin1/writing-processes-to-quality-baseline,Linking Writing Processes to Writing Quality
15717,149284443,1251.0,,9,110,/datark1/eda-for-better-data-understanding,Linking Writing Processes to Writing Quality
15718,148714708,1215.0,,1,3,/vyacheslavefimov/simple-eda-for-writing-quality-dataset,Linking Writing Processes to Writing Quality
15719,145598683,1150.0,,1,4,/pehahn/keystroke-measures-in-r,Linking Writing Processes to Writing Quality
15720,148859584,1356.0,,2,31,/eishkaran/simplest-lgbm,Linking Writing Processes to Writing Quality
15721,151878854,1390.0,,4,48,/iqmansingh/quality-of-writing-eda-fs-lgbm-xgb-optuna,Linking Writing Processes to Writing Quality
15722,146626164,1431.0,,0,1,/edchang1992/writing-processes-to-quality-linreg-baseline,Linking Writing Processes to Writing Quality
15723,147779185,1416.0,1.119616567873115,0,4,/azraimohamad/linking-writing-with-essay-score-lr,Linking Writing Processes to Writing Quality
15724,157293607,1412.0,0.6289683204649799,0,0,/halilergul/train-on-all-data,Linking Writing Processes to Writing Quality
15725,145013445,1524.0,,2,13,/olegzholobov/parlorsky-simple-eda,Linking Writing Processes to Writing Quality
15726,155993503,1483.0,0.657062575439326,0,2,/farinesfari/notebookcd13fc3cd3,Linking Writing Processes to Writing Quality
15727,158357629,1529.0,0.653831054657495,0,0,/elna4os/xgboost,Linking Writing Processes to Writing Quality
15728,149408310,1504.0,,1,5,/klyushnik/writing-quality,Linking Writing Processes to Writing Quality
15729,145510323,1582.0,0.6619108682011876,0,6,/chrisk321/linking-writing-processes-eda-submission,Linking Writing Processes to Writing Quality
15730,155396584,1574.0,0.6552530780941668,0,2,/ehabelkady/notebook559efe1a32,Linking Writing Processes to Writing Quality
15731,146560612,1606.0,0.6775361834444937,2,13,/guidosalimbeni/writing-quality-prediction-in-picture,Linking Writing Processes to Writing Quality
15732,148358667,1551.0,0.7966941401387072,0,2,/lordxerxes/baseline-solution,Linking Writing Processes to Writing Quality
15733,145119801,1603.0,0.659788283537017,2,16,/j13mehul/understanding-the-competition,Linking Writing Processes to Writing Quality
15734,146943205,1557.0,0.6607035852939508,0,7,/qwerty29544/baseline-reggression,Linking Writing Processes to Writing Quality
15735,152921584,1558.0,0.6610173974462021,0,2,/jenilgajjar/linking-writing-processes-to-writing-quality,Linking Writing Processes to Writing Quality
15736,145803877,1491.0,,0,3,/bkowshik/down-and-up-times-of-successive-events,Linking Writing Processes to Writing Quality
15737,152838065,1669.0,,5,35,/crispychurch/keyboard-shortcuts-and-reliance-on-the-mouse,Linking Writing Processes to Writing Quality
15738,146332914,1613.0,0.6681763746956018,0,3,/kelvinquansah/gradient-boosting-regression,Linking Writing Processes to Writing Quality
15739,150012949,1631.0,,0,10,/vachiry/writing-linking-model,Linking Writing Processes to Writing Quality
15740,152781782,1670.0,,3,4,/josephthibault/kld-thibault1-ezfeatures,Linking Writing Processes to Writing Quality
15741,152781782,1670.0,,3,4,/josephthibault/kld-thibault1-ezfeatures,Linking Writing Processes to Writing Quality
15742,154216963,1646.0,0.6811072223472157,0,2,/ruijing0429/writing-behavior-writing-score,Linking Writing Processes to Writing Quality
15743,149527562,1647.0,0.6815151628389599,0,2,/jagdmir/feature-engineering-models-comparison-cv-kfold,Linking Writing Processes to Writing Quality
15744,157168911,1668.0,,7,19,/jairanjan/edabasiclightgbm,Linking Writing Processes to Writing Quality
15745,151455264,1634.0,,0,8,/chuboy/simple-essay-reconstructor,Linking Writing Processes to Writing Quality
15746,145332422,1688.0,0.6919727469874012,0,10,/vidhikishorwaghela/keystroke-analysis-for-essay-quality-rf-mse-0-4,Linking Writing Processes to Writing Quality
15747,166884511,1676.0,,0,10,/alexeyk12/choosing-a-boosting-algorithm,Linking Writing Processes to Writing Quality
15748,156832130,1699.0,0.6951165123638864,0,0,/yaolinqingill/notebookad6d7b8e7d,Linking Writing Processes to Writing Quality
15749,152528318,1701.0,0.6986332519189782,0,1,/ducminhphy/gradient-boosting-regression,Linking Writing Processes to Writing Quality
15750,145584832,1695.0,0.7032496329614428,0,2,/shaikikozashvili/base-model,Linking Writing Processes to Writing Quality
15751,154215760,1689.0,0.7040685602206803,0,1,/jrazdolsky1/linking-writing-process-to-quality,Linking Writing Processes to Writing Quality
15752,153852206,1745.0,2.038581011240683,0,0,/anastasijarammul/random-forest-default-params,Linking Writing Processes to Writing Quality
15753,154210782,1738.0,0.7422789660979691,0,0,/pauljojr/linking-writing-process-to-quality,Linking Writing Processes to Writing Quality
15754,152842179,1759.0,,14,28,/suraj520/word2vec-voting-gpu-k-fold-cv-optuna,Linking Writing Processes to Writing Quality
15755,156600004,1750.0,0.7657684141428394,0,9,/shradz18/building-neural-network-model,Linking Writing Processes to Writing Quality
15756,156227324,1786.0,0.9908688558445998,0,3,/scottnewcomer/writing-quality-xgboost-numeric,Linking Writing Processes to Writing Quality
15757,151559113,1790.0,,5,10,/erivanoliveirajr/r-0-9-the-number-of-events-and-score,Linking Writing Processes to Writing Quality
15758,147079163,1801.0,0.9965959802974592,1,30,/rajatsurana979/predicting-essay-quality-from-typing-behavior,Linking Writing Processes to Writing Quality
15759,145275129,1787.0,1.0613046485768087,0,4,/marekm4/writing-process,Linking Writing Processes to Writing Quality
15760,153781019,1827.0,1.378994993116006,0,1,/timbouris/linking-writing-processes-to-quality-full-process,Linking Writing Processes to Writing Quality
15761,146844472,1839.0,,9,64,/alexia/kerasnlp-starter-notebook-writing-quality,Linking Writing Processes to Writing Quality
15762,157815860,1856.0,,0,0,/vinitkp/writingprocesses-randomforestregressor,Linking Writing Processes to Writing Quality
15763,154229226,1872.0,3.8647481808817328,0,0,/mingjiaodiao/writing-qualities,Linking Writing Processes to Writing Quality
15764,164687552,3.0,,0,0,/dantee/lunit-attention-mil-inference-for-ovarian-cancer,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15765,157867328,7.0,0.5862040303726195,3,16,/m1dsolo/ubc-ocean-7th-submission,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15766,157196502,8.0,,1,1,/forcewithme/ocean-tmp-using,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15767,156135170,23.0,,0,1,/xuyangsong/ubc-ocean,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15768,157614936,27.0,,2,17,/yuto0712/view-annotation-file,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15769,148822653,10.0,,4,45,/gunesevitan/ubc-ocean-eda,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15770,156965593,21.0,,11,39,/shiyunlong07/pytorch-baseline-by-resnet-pretrained,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15771,151243226,14.0,,6,11,/yannan90/ubc-tiling,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15772,153918706,49.0,,4,9,/junxhuang/use-c-to-crop-images,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15773,147890930,93.0,0.1666666666666666,3,7,/yukkyo/probing-all-test-sample-have-thumbnail,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15774,148108728,86.0,,0,2,/holmes0610/eda-ubc-ocean,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15775,147203686,50.0,,0,2,/mohammedessam97/ubc-stratified-k-fold-quick-training,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15776,156495848,94.0,,3,23,/aliabbasi/ubc-eda-with-pyvips,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15777,157534827,249.0,0.4635104555256709,0,0,/hideyukizushi/ubc-infv2other-alef-a-203-b3,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15778,153421110,469.0,,0,0,/nanerwei/train1,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15779,154134707,699.0,,0,10,/aikhmelnytskyy/cancer-subtype-tpu,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15780,149878326,283.0,,0,5,/mozattt/arcface-with-effiv2-l,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15781,156280048,472.0,0.4557391988069064,4,37,/xiaocao123/lb-0-45,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15782,145860859,248.0,,1,4,/malabhbakshi/ubc-starter-notebook,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15783,145860859,248.0,,1,4,/malabhbakshi/ubc-starter-notebook,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15784,150346563,487.0,,0,0,/manasjohri/ubc-ocean-inffer,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15785,147158439,96.0,,0,1,/seeingtimes/threw-exception-error,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15786,156618954,320.0,,1,7,/pushkar007/learn-multiclass-semantic-segmentation-unet-miou,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15787,155495236,216.0,,0,7,/samu2505/ubc-imagedataset,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15788,156980377,335.0,0.4557391988069064,0,12,/mfmfmf3/clean-code-ubc-ovarian-cancer,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15789,156122940,352.0,,0,0,/minemine12345678/ubc-ocean-tf-efficientnet-b2-ns-submit,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15790,145599224,353.0,,4,10,/utm529fg/ubco-initial-eda,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15791,154320658,361.0,,0,18,/anilyagiz/notebookda3c754847,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15792,155248538,103.0,,11,69,/jirkaborovec/cancer-subtype-eda-load-wsi-segmentation,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15793,151789733,366.0,,0,2,/awawaz/231122-densenet121,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15794,145695346,384.0,,0,11,/dheerajmpai/ubc-ocean-tile-down-large-images-for-cnn-baseline,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15795,156853253,286.0,0.4557391988069064,2,17,,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15796,147340716,482.0,0.2812493023722548,0,12,/yinankaggle/ensemble-inference-resnet50,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15797,147836875,442.0,,0,4,/yavuzhanbaykara/ubc-data-augmentation-for-synthetic-data-gen,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15798,149470115,448.0,,1,9,/dhinkris/top-10-informative-patches-based-on-std-dev,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15799,157309447,452.0,,0,10,/pouyan89/ubc-ocean-eda-patch-images-and-masks,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15800,156401356,287.0,0.449621809322377,0,0,/shivamardeshna/lb-0-57,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15801,145527758,237.0,,0,8,/motono0223/image-thumbnails,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15802,147674786,773.0,0.1475844250217512,0,2,/uncledrew0205/test-version,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15803,145545194,570.0,,0,9,/rainfalllove/using-mil-prepare-dataset,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15804,149162045,580.0,,1,7,/liuyanfeng/ml-tensorflow-cnn,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15805,147324348,98.0,,3,23,/icagatta/ecosystem-dataset-prep-convnext-finetuning,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15806,155823385,260.0,,0,9,/orzlala/generate-tumor-image-patch,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15807,147317220,650.0,,0,5,/sytuannguyen/ovarian-cancer-classification,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15808,145964817,229.0,,1,13,/yusaku5739/stainnet-get-the-stain-normalized-image,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15809,149033173,531.0,,0,0,/bhuynguyn/inference-note-single-model,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15810,148771958,142.0,,0,0,/cyberblack0/start-with-it-1,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15811,150335931,663.0,,0,5,/xiejili/ubc-eda-feature-engineering-visiualization,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15812,151813299,95.0,,0,0,/yuan368858/ubc-ocean-generate-tiles-for-training,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15813,156310669,161.0,,0,0,/naocanzouyihui/ubc-ovarian-cancer-subtype-classification,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15814,156101320,740.0,,0,1,/rickycorte/ubc-model-test-pre-tiled-dataset-2048-512,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15815,154884007,92.0,0.3834110605761545,0,0,/dukgiim/cancer-subtype-lightning-torch-inference-tiles,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15816,153520202,685.0,0.1877093666052127,0,0,/lichangheng0107/copy2,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15817,155597970,125.0,,0,11,/sonujha090/fastai-ubc-ovarian-cancer-subtype,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15818,151194192,889.0,,0,0,/seojunelee/ovarian-cancer-crop,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15819,157525151,900.0,0.1895233553059825,0,5,/serhiikharchuk/trythisnew,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15820,150143944,215.0,,0,0,/yamitomo/i-need-help,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15821,150754133,771.0,,0,2,/mdquilindo/ubc-training-thumbnails,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15822,152025700,127.0,0.1557674557237082,0,1,/omiran/ubc-ovarian-cancer,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15823,145922040,691.0,,2,2,/kodainagano/all-train-images,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15824,151038358,117.0,,0,2,/usmansafdar09/test-wsi-patches-256x256,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15825,146290917,759.0,,0,4,/parhamgousheh/ovarian-cancer,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15826,147255949,809.0,,0,1,/debojitbasak02/ovarian-cancer-classification-using-the-csv-file,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15827,150629796,812.0,,2,2,/dinkelma/notebooke742149a85,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15828,150749788,755.0,,0,0,/kenc1995/duplicate-check-by-image-hash,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15829,146108229,824.0,0.3127768546067523,0,1,/viveksahukar/model-1-resnet50-cpu-inference,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15830,148057006,823.0,,0,1,/irinamishneva/eda-ubc-ocean,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15831,155257538,763.0,,4,9,/shubham219/starter-code-effnetv2s-training,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15832,149858509,831.0,,0,0,/lmyybh/ubco-eda,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15833,145808128,1026.0,0.1331410348931387,0,11,/satyaprakashshukl/ubc-analysis-eda-wip,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15834,157762093,842.0,,0,8,/rishabh0517/ubcbaselinetrain,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15835,145867748,998.0,,30,114,/jefersonpazze/eda-baseline,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15836,150435482,841.0,,7,3,/cortomalt/fastai-advanced-fine-tuning,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15837,147898259,989.0,,0,1,/theobervanakis/ubco-tiled-256-train,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15838,157200912,1048.0,0.2398079143963167,0,0,/fstolarczyk/ubc-model,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15839,154179259,1042.0,,0,2,/atamazian/ubc-ocean-tf-swin-large-inference-debug,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15840,152687433,853.0,,0,0,/mohamedbaantar/final-project-phase-1,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15841,147054811,1108.0,,0,3,/onkur7/eda-ovarian-cancer,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15842,146954078,978.0,,0,3,/datascienceconcepts/cnn-pytorch-solution,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15843,149988219,971.0,,0,8,/emiz6413/image-colorfulness-to-filter-uninformative-patches,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15844,146819152,848.0,,0,0,/woodmanaigret/ubc-ocean-reduce-png-to-you-need,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15845,155662899,1089.0,,0,0,/jinstat/cropping-threshold,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15846,154345332,1126.0,,3,20,/vinitkp/ovariancancerclassification-cnn,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15847,146982497,1173.0,0.1666666666666666,16,107,/aritrag/kerascv-train-and-infer-on-thumbnails,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15848,152303457,844.0,0.1666666666666666,0,0,/rayanaloufi/ubc-ocean-inffer,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15849,148026505,961.0,,0,0,/japancolorado/fast-ai-first-pass,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15850,147946758,1130.0,0.2033205165071894,0,0,/buringstraw/ubc-ocsc2,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15851,154366672,1056.0,,1,16,/sunilthite/ubc-ocean-transfer-learning-45,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15852,161302542,1182.0,,0,0,/stephanschweitzer/pmc-test-1,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15853,149368551,1052.0,,0,2,/pranavkural/ovarian-cancer-subtype-efficientnet-fine-tuned,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15854,154165272,1292.0,0.201469146010807,0,9,/mukaffimoin/ubc-ovarian-cancer-mobilenetv3,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15855,146097472,1208.0,,0,5,/stpeteishii/ovarian-image-appearance-by-label,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15856,155650077,1293.0,0.1823344096048688,0,1,/cymcym/ubc-submission,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15857,147822303,1200.0,,0,0,/slaine22/final-project-phase-1,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15858,147822303,1200.0,,0,0,/slaine22/final-project-phase-1,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15859,157620538,1186.0,,0,0,/luckypen/grad-cam-heatmap-for-model-evaluation,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15860,152912288,1262.0,,0,1,/zeus101/notebook,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15861,149948287,1134.0,,0,0,/kilmtoki/submission-csv,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15862,154592771,1302.0,,1,3,/erfansaeedi/simple,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15863,156603421,1143.0,0.1628023062772019,0,5,/yungchopps/custom-resnet-model-with-training-and-inferencing,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15864,152921423,1205.0,,0,0,/azswsxdetw/notebook0d6c379fa9,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15865,152602662,1317.0,,0,0,/bohdanmaksymchuk/ovarian-cancer-training,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15866,157677713,1178.0,,0,2,/mohammedsalf/classify-ovarian-cancer-subtypes,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15867,146386355,1109.0,0.1462566206945178,0,3,/yunsuxiaozi/welcome-to-this-competition-ubco,UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
15868,146427083,2.0,,0,1,/ironbar/semantle-2-tuples-search,AI Village Capture the Flag @ DEFCON31
15869,150106419,3.0,,0,14,/mrmldjr/3rd-place-25-points-solutions-ctf-defcon31,AI Village Capture the Flag @ DEFCON31
15870,150163778,4.0,,4,50,/patrih/ctf-bingus-travelling-solutions,AI Village Capture the Flag @ DEFCON31
15871,150212966,18.0,,1,3,/cf020031308/23-flags-w-o-the-big-4,AI Village Capture the Flag @ DEFCON31
15872,150022594,35.0,,1,13,/bowaka/defcon31-granny-square-attack-in-details,AI Village Capture the Flag @ DEFCON31
15873,148714090,55.0,,0,0,/pietromaldini1/pixelated,AI Village Capture the Flag @ DEFCON31
15874,146524171,61.0,,0,15,/kononenko/ctf-submission,AI Village Capture the Flag @ DEFCON31
15875,150192472,64.0,,0,7,/raiderrzj/defcon31-ai-ctf-22-flags,AI Village Capture the Flag @ DEFCON31
15876,149280043,80.0,,0,1,/thariqnugrohotomo/ctf-defcon31-pixelated-ocr-image-generator,AI Village Capture the Flag @ DEFCON31
15877,150075520,94.0,,0,5,/josepart/granny-1-ai-village-ctf-2023,AI Village Capture the Flag @ DEFCON31
15878,150074637,129.0,,0,2,/proselotis/ctf-20-solutions,AI Village Capture the Flag @ DEFCON31
15879,150188225,136.0,,1,8,/nikhil1e9/defcon31-ctf-all-llm-solutions,AI Village Capture the Flag @ DEFCON31
15880,150059079,166.0,18.0,0,7,/mohammad2012191/18-flags-some-unsuccessful-trials,AI Village Capture the Flag @ DEFCON31
15881,150129228,168.0,,2,9,/lucasboesen/semantle-using-datamuse-api,AI Village Capture the Flag @ DEFCON31
15882,150124901,192.0,18.0,0,10,/furduisorinoctavian/18-flags-ai-ctf-write-ups,AI Village Capture the Flag @ DEFCON31
15883,150076201,202.0,,0,3,/tc0000/inversion-attack-sample-code,AI Village Capture the Flag @ DEFCON31
15884,151727070,275.0,,0,0,/michalbigaj/cluster-3-without-guessing-order-of-letters,AI Village Capture the Flag @ DEFCON31
15885,147977119,314.0,,0,6,/texopher/for-granny-various-images-about-timber-wolf,AI Village Capture the Flag @ DEFCON31
15886,150210748,316.0,,3,9,/evanarlian/defcon31-solve-cluster-3-without-eyeballing,AI Village Capture the Flag @ DEFCON31
15887,149444107,374.0,,0,8,/jazivxt/no-hints-just-fooling-around,AI Village Capture the Flag @ DEFCON31
15888,150718720,391.0,,0,3,/phanisrikanth/defcon31-llm-challenges-prompt-evolution,AI Village Capture the Flag @ DEFCON31
15889,150096395,399.0,,2,17,/rushali2406/11-flags-ctf-solutions,AI Village Capture the Flag @ DEFCON31
15890,148373310,433.0,10.0,0,1,/theerawitplukmontol/defcon31-ctf-attempt,AI Village Capture the Flag @ DEFCON31
15891,151078228,565.0,,0,0,/impradhumn/ctf-2023-beginners-approach-to-the-competition,AI Village Capture the Flag @ DEFCON31
15892,147996493,1124.0,1.0,0,12,/imessam/ai-village-capture-the-flag-defcon31,AI Village Capture the Flag @ DEFCON31
15893,146505231,1254.0,0.0,1,6,/mr0106/ai-ctf-defcon31,AI Village Capture the Flag @ DEFCON31
15894,146505231,1254.0,0.0,1,6,/mr0106/ai-ctf-defcon31,AI Village Capture the Flag @ DEFCON31
15895,150055795,1342.0,,0,5,/pnartopuz/ai-village-capture-the-flag-defcon31-cyber-chall,AI Village Capture the Flag @ DEFCON31
15896,148370614,7.0,0.8739294395738374,0,6,/sarunpm/easy-binary-classification-smoking-xgboost-optuna,Binary Prediction of Smoker Status using Bio-Signals
15897,148370614,7.0,0.8739294395738374,0,6,/sarunpm/easy-binary-classification-smoking-xgboost-optuna,Binary Prediction of Smoker Status using Bio-Signals
15898,150172309,8.0,0.8810906397860226,30,132,/arunklenin/ps3e24-eda-feature-engineering-ensemble,Binary Prediction of Smoker Status using Bio-Signals
15899,150219137,42.0,0.8807423789312255,0,6,/yongsukprasertsuk/top-lb-smoking-ensemble,Binary Prediction of Smoker Status using Bio-Signals
15900,148256863,81.0,0.8785850560129854,4,42,/alexryzhkov/smoking-lama-lightautoml-baseline,Binary Prediction of Smoker Status using Bio-Signals
15901,151882045,30.0,,8,39,/iqmansingh/smoker-status-xgb-lgbm-cat-dart-ensembling,Binary Prediction of Smoker Status using Bio-Signals
15902,150437332,89.0,0.8180985658348614,5,10,/rm1000/s03e24-decision-tree-classifier,Binary Prediction of Smoker Status using Bio-Signals
15903,155692552,35.0,,0,6,/daniellebagaforomeer/smoker-status-prediction-voting-and-stacking-clf,Binary Prediction of Smoker Status using Bio-Signals
15904,150525627,82.0,0.8810584976335137,1,8,/mahmudds/binary-pred-eda-feature-engineering-ensemble,Binary Prediction of Smoker Status using Bio-Signals
15905,148320102,49.0,0.8739848662676872,6,37,/eishkaran/smoking-starter-stacked-meta-models,Binary Prediction of Smoker Status using Bio-Signals
15906,147927975,60.0,0.8430374297985758,0,3,/ianchute/box-cox-logistic-regression,Binary Prediction of Smoker Status using Bio-Signals
15907,148119707,63.0,,4,16,/maxmarriottclarke/ps3-24-predicting-smokers-xgb-lgbm,Binary Prediction of Smoker Status using Bio-Signals
15908,150160734,109.0,,27,82,/ashishkumarak/binary-classification-smoker-or-not-eda-xgboost,Binary Prediction of Smoker Status using Bio-Signals
15909,150592096,133.0,,0,0,/jacker01/smoker-predictions,Binary Prediction of Smoker Status using Bio-Signals
15910,150582444,138.0,,0,0,/spiritokko/smoking-prediction-with-xgboost,Binary Prediction of Smoker Status using Bio-Signals
15911,148791986,157.0,0.8677611138854822,0,3,/abhishekrp1517/ps-s3-e24-from-baseline-to-ensemble,Binary Prediction of Smoker Status using Bio-Signals
15912,150222300,141.0,0.8384872374515518,0,7,/rishabhdang/smoking-prediction,Binary Prediction of Smoker Status using Bio-Signals
15913,148373305,146.0,0.7868634173522093,0,12,/angelojmaia/decisiontree-randomforest-xgboost,Binary Prediction of Smoker Status using Bio-Signals
15914,148299645,272.0,,0,6,/armanzhalgasbayev/ps-s3-e24-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
15915,149942052,171.0,0.8670820815539818,0,0,/strawhatdragon/ps3e24-catboost-v2,Binary Prediction of Smoker Status using Bio-Signals
15916,147900406,180.0,0.8630868246444128,0,8,/guanlintao/voting-stacking-binary-prediction-probability,Binary Prediction of Smoker Status using Bio-Signals
15917,149611034,183.0,,9,16,/amulyas/ps3e24-dsc1-eda-feature-engineering-modeling,Binary Prediction of Smoker Status using Bio-Signals
15918,148838819,185.0,0.8586141465580975,1,13,/abdullaharean/simple-neural-network-test,Binary Prediction of Smoker Status using Bio-Signals
15919,148838819,185.0,0.8586141465580975,1,13,/abdullaharean/simple-neural-network-test,Binary Prediction of Smoker Status using Bio-Signals
15920,149393795,173.0,0.8802895973612721,16,59,/paddykb/pg-s3e24-brute-force-and-ignorance,Binary Prediction of Smoker Status using Bio-Signals
15921,148687814,160.0,,0,2,/nakashi120/stacking-classifier-binary-prediction-of-smoker,Binary Prediction of Smoker Status using Bio-Signals
15922,151687966,166.0,,0,0,/smmike/ps3e24-eda-feature-engineering-ensemble,Binary Prediction of Smoker Status using Bio-Signals
15923,150418632,217.0,0.8800595524164612,8,39,/zhukovoleksiy/ps-s3e24-smoker-status-predictions,Binary Prediction of Smoker Status using Bio-Signals
15924,148910442,223.0,0.8152980656169667,0,0,/rss1011/voting-classifier-using-xgboost-and-lgbm,Binary Prediction of Smoker Status using Bio-Signals
15925,150752771,206.0,,0,2,/echowuzangye/optuna-borutashap-xgboost-lgbm-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
15926,149265143,252.0,,0,6,/shadeer/smoker-status,Binary Prediction of Smoker Status using Bio-Signals
15927,148372383,241.0,0.7764881057774932,0,13,/sunilthite/binaryprediction-of-smoker-status-using-biosignals,Binary Prediction of Smoker Status using Bio-Signals
15928,147851516,254.0,0.8719118826231465,9,21,/kdmitrie/pgs324-the-tutorial-on-using-autogluon,Binary Prediction of Smoker Status using Bio-Signals
15929,150569164,259.0,,0,5,/atsassin/xgboost-some-feature-engineering,Binary Prediction of Smoker Status using Bio-Signals
15930,149666920,313.0,0.8778378503386218,5,28,/cybersimar08/ps-s3e24-eda-optuna-cat-xgb-lgbm,Binary Prediction of Smoker Status using Bio-Signals
15931,147929472,307.0,0.8777460943400183,0,4,/yaoheyi/binary-prediction-of-smoker-status-using-bio-signa,Binary Prediction of Smoker Status using Bio-Signals
15932,150439704,320.0,0.8774380879628993,0,5,/gulnihall/smoker-status-eda-lgbm-xgbm-catboost-votingc,Binary Prediction of Smoker Status using Bio-Signals
15933,150439704,320.0,0.8774380879628993,0,5,/gulnihall/smoker-status-eda-lgbm-xgbm-catboost-votingc,Binary Prediction of Smoker Status using Bio-Signals
15934,148523833,328.0,,1,11,/sytuannguyen/smoker-status-prediction-using-bio-signals,Binary Prediction of Smoker Status using Bio-Signals
15935,148606637,292.0,,0,4,/fathyalin/starter-notebook-optuna-pycaret,Binary Prediction of Smoker Status using Bio-Signals
15936,149556817,326.0,0.8768675692727526,9,31,/francescoliveras/ps-s3-e24-eda-model-en-es,Binary Prediction of Smoker Status using Bio-Signals
15937,148247965,314.0,0.8733439383766821,0,4,/lonnieqin/smoker-status-prediction-with-lgbm-and-optuna,Binary Prediction of Smoker Status using Bio-Signals
15938,147797724,425.0,,8,22,/anzarwani2/getting-started,Binary Prediction of Smoker Status using Bio-Signals
15939,149894396,332.0,0.8758404748293883,0,7,/kanishk026/simple-ensemble-xgb-lgbm-hist,Binary Prediction of Smoker Status using Bio-Signals
15940,147877920,358.0,,0,5,/adeniyibabalola/mad-genius-decoding-smoker-status-through-eda,Binary Prediction of Smoker Status using Bio-Signals
15941,150012053,335.0,0.8756425630033166,0,7,/xxxxyyyy80008/smoker-status-prediction-lightgbm-baseline-no-fe,Binary Prediction of Smoker Status using Bio-Signals
15942,147985604,333.0,,0,4,/mainscientist/ps3e24-catboost-xgboost-bayes-opt,Binary Prediction of Smoker Status using Bio-Signals
15943,150352532,386.0,0.8734781440589954,0,8,/dima806/s3e24-catboost-optuna-skf-topmisclass-pseudolabels,Binary Prediction of Smoker Status using Bio-Signals
15944,149061941,340.0,,0,4,/bertanpank/s3e24-no-model-some-useful-stuff,Binary Prediction of Smoker Status using Bio-Signals
15945,150533987,355.0,,1,11,/rcratos/smoker-status-xgboost-lgbm-hist-ensemble-optuna,Binary Prediction of Smoker Status using Bio-Signals
15946,149576632,359.0,0.8750782008272043,2,10,/stepankarpov/binary-prediction-of-smoker-status-using-bio-signa,Binary Prediction of Smoker Status using Bio-Signals
15947,150448510,464.0,0.8744767730941094,28,64,/akioonodera/ps-3-24-lgbm-bin,Binary Prediction of Smoker Status using Bio-Signals
15948,147883814,385.0,0.8718602681801002,0,8,/m000sey/eda-w-model-baseline,Binary Prediction of Smoker Status using Bio-Signals
15949,149177034,427.0,,2,9,/ziadwael/smoker-prediction-xgbc-acc-87-4,Binary Prediction of Smoker Status using Bio-Signals
15950,149107632,428.0,,6,14,/ridwanakmal/fast-stacking-baseline-rf-xgb-lgbm-just-2-min,Binary Prediction of Smoker Status using Bio-Signals
15951,153620613,418.0,0.8730038033977092,0,2,/danielpopov/binary-classification-smoker-or-not-xgboost,Binary Prediction of Smoker Status using Bio-Signals
15952,148442062,930.0,,0,1,/andrprovensi/ps-s3-e24-smoking,Binary Prediction of Smoker Status using Bio-Signals
15953,148276333,411.0,0.8749167809137405,0,3,/dataminingee/ps-s3-ep24-smoking,Binary Prediction of Smoker Status using Bio-Signals
15954,150544734,387.0,,0,5,/joseelisei/smoker-prediction-using-bio-signals,Binary Prediction of Smoker Status using Bio-Signals
15955,150091451,421.0,0.8739916190105202,0,6,/syerramilli/ps3e24-xgboost-for-predicting-smoking-status,Binary Prediction of Smoker Status using Bio-Signals
15956,148171985,444.0,,0,8,/danielmbuchberger/ps-s-3-e-24-first-steps,Binary Prediction of Smoker Status using Bio-Signals
15957,162542292,438.0,0.8691362749575956,22,69,/kapturovalexander/kapturov-s-solution-of-ps-s3e24,Binary Prediction of Smoker Status using Bio-Signals
15958,148428407,453.0,0.8645699211966205,0,6,/docxian/ps-s3-e24-smoker-status-nn-autogluon,Binary Prediction of Smoker Status using Bio-Signals
15959,147761899,445.0,,3,11,/gauravduttakiit/pss3e24-lazypredict,Binary Prediction of Smoker Status using Bio-Signals
15960,150522869,389.0,0.8627036844048949,0,13,/klyushnik/smoker-death,Binary Prediction of Smoker Status using Bio-Signals
15961,151891161,469.0,,7,26,/dumanmesut/smoker-status-0-1-eda-lgbm-xgb,Binary Prediction of Smoker Status using Bio-Signals
15962,147872442,459.0,0.8743868464338651,0,14,/matthewjansen/smoker-status-prediction-via-bio-signals,Binary Prediction of Smoker Status using Bio-Signals
15963,150415306,437.0,0.8733029340961207,13,15,/thomasmeiner/ps3e24-bluecast-eda-automl-tracking,Binary Prediction of Smoker Status using Bio-Signals
15964,148572772,491.0,,3,21,/iqbalsyahakbar/ps3e24-predicting-smokers-for-starters,Binary Prediction of Smoker Status using Bio-Signals
15965,148263672,466.0,,10,38,/lucabasa/binary-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
15966,151899976,558.0,,2,17,/yldzburhan/smoker-status-prediction-lgbm-xgb,Binary Prediction of Smoker Status using Bio-Signals
15967,149657262,492.0,0.8698942217841044,0,7,/ayhampar/voting-3-classifiers-add-original-dataset,Binary Prediction of Smoker Status using Bio-Signals
15968,151444885,526.0,,1,0,/enriquegiottonini/smokin1,Binary Prediction of Smoker Status using Bio-Signals
15969,152285544,546.0,0.8696027472054936,1,25,/huseyinbaytar/ps3e24-binary-classification-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
15970,148799149,514.0,0.8738846907957452,0,0,/sabienn/smoker-status-comp-notebook,Binary Prediction of Smoker Status using Bio-Signals
15971,150623880,433.0,0.8676862510361734,0,3,/thiagostat/appyling-feat-eng-xgboost-optuna,Binary Prediction of Smoker Status using Bio-Signals
15972,150553862,489.0,,0,0,/dunyexplorer/smoki,Binary Prediction of Smoker Status using Bio-Signals
15973,148520873,553.0,0.8639557603651667,5,18,/mukul74/estimation-of-smoking-probability-s3e24,Binary Prediction of Smoker Status using Bio-Signals
15974,148520873,553.0,0.8639557603651667,5,18,/mukul74/estimation-of-smoking-probability-s3e24,Binary Prediction of Smoker Status using Bio-Signals
15975,148433726,478.0,0.871665852422893,0,4,/syedsubahani/smoker-status-binary-prediction-model,Binary Prediction of Smoker Status using Bio-Signals
15976,159445378,852.0,,1,4,/arpitppatel/classification-template-ps3e24,Binary Prediction of Smoker Status using Bio-Signals
15977,147766581,564.0,,0,6,/yunsuxiaozi/pss3e24-best-eda-is-all-you-need,Binary Prediction of Smoker Status using Bio-Signals
15978,147776718,542.0,,1,7,/stpeteishii/ps3e24-histplot,Binary Prediction of Smoker Status using Bio-Signals
15979,150015744,554.0,0.8730438004129517,6,11,/hridaym25/simple-lgbm-classifier,Binary Prediction of Smoker Status using Bio-Signals
15980,148641933,515.0,0.8731155737130311,0,2,/fnushashank/smoker-prediction,Binary Prediction of Smoker Status using Bio-Signals
15981,148641933,515.0,0.8731155737130311,0,2,/fnushashank/smoker-prediction,Binary Prediction of Smoker Status using Bio-Signals
15982,150643329,607.0,,13,36,/enricomanosperti/binary-prediction-of-smoker-status-using-bio-signa,Binary Prediction of Smoker Status using Bio-Signals
15983,150537774,578.0,0.8718176016859182,0,5,/askboxnet/lightgbm-stratifiedkfold-binary-prediction,Binary Prediction of Smoker Status using Bio-Signals
15984,150600640,614.0,0.8699388757076152,21,41,/vishwasmishra1234/smokingpreds,Binary Prediction of Smoker Status using Bio-Signals
15985,147985707,556.0,0.8723276302543114,0,11,/mcpenguin/ps3e24-baseline,Binary Prediction of Smoker Status using Bio-Signals
15986,147945595,592.0,0.872586605846511,2,5,/viji1609/pgs-s3e24-tfdf-r1,Binary Prediction of Smoker Status using Bio-Signals
15987,150456893,609.0,0.8725473360497277,0,2,/radturkin/binary-prediction-of-smoker-status-final,Binary Prediction of Smoker Status using Bio-Signals
15988,163999031,636.0,,0,6,/jpedrou/prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
15989,147803638,599.0,0.8724114455693696,0,5,/mexwell/s03e24-eda-and-lightgbm,Binary Prediction of Smoker Status using Bio-Signals
15990,150311968,628.0,,6,29,/tamsquare/binary-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
15991,147831518,583.0,0.8697606484656684,0,5,/nickkrikota/s3e24-quick-eda-and-ensemble,Binary Prediction of Smoker Status using Bio-Signals
15992,150567120,658.0,0.8460994983005673,0,0,/aaradhyabadal/smoking-is-not-cool-kids-pg-s3e24,Binary Prediction of Smoker Status using Bio-Signals
15993,148786943,644.0,,0,6,/abdrah/gridsearch-ensemble-submission-starter,Binary Prediction of Smoker Status using Bio-Signals
15994,150272414,645.0,0.872171445410375,0,5,/misterjjunpatch/smoker-status-prediction-catboost-80-accuracy,Binary Prediction of Smoker Status using Bio-Signals
15995,151511156,681.0,,0,0,/andresmembrillo/smoker-status-xgboost,Binary Prediction of Smoker Status using Bio-Signals
15996,149466190,649.0,0.8719580135679994,0,8,/jankuper192/smoking-bio-signals,Binary Prediction of Smoker Status using Bio-Signals
15997,149069783,643.0,,2,3,/sharif8410/binaryclassification-tree-based-ensemble-models,Binary Prediction of Smoker Status using Bio-Signals
15998,148539627,666.0,0.8718602681801002,0,9,/adwaitkesharwani/a-simple-catboost-notebook-with-cross-validation,Binary Prediction of Smoker Status using Bio-Signals
15999,148314818,637.0,0.8662154358938409,0,7,/neupane9sujal/binary-prediction-of-smoker-status-catboost,Binary Prediction of Smoker Status using Bio-Signals
16000,148052811,624.0,,3,22,/patriciabrezeanu/catboost-hyperparameter-tuning,Binary Prediction of Smoker Status using Bio-Signals
16001,149207828,676.0,,0,1,/yashrana24/2-s3-24,Binary Prediction of Smoker Status using Bio-Signals
16002,149754498,709.0,0.8706399685046653,2,7,/barbagrande007/bbg007-s3e24-smoking,Binary Prediction of Smoker Status using Bio-Signals
16003,148186572,708.0,0.8711000583942871,0,3,/synchrocyclotron/simple-catboost-0-87,Binary Prediction of Smoker Status using Bio-Signals
16004,149225964,665.0,0.8709958448272995,1,5,/bkowshik/automl-with-h2o-predict-smoking-status,Binary Prediction of Smoker Status using Bio-Signals
16005,148858499,679.0,,0,10,/keishibata/ps3-s3e24-baseline-for-beginners,Binary Prediction of Smoker Status using Bio-Signals
16006,150268547,695.0,0.8709114739354064,1,3,/riteshbhalerao/binary-classifier-autogluon,Binary Prediction of Smoker Status using Bio-Signals
16007,148111650,735.0,,0,13,/mawro73/easy-notebook-86-auc-score-with-catboots,Binary Prediction of Smoker Status using Bio-Signals
16008,148637900,775.0,,0,6,/aniskhan25/playground-series-s03e24,Binary Prediction of Smoker Status using Bio-Signals
16009,147995263,698.0,,0,12,/ashirzaki/binary-prediction,Binary Prediction of Smoker Status using Bio-Signals
16010,150472284,743.0,0.8660014078226663,0,0,/natchaphonkamhaeng/pg-competition-binary-prediction-of-smoke-detect,Binary Prediction of Smoker Status using Bio-Signals
16011,150347868,767.0,0.8706139693155365,0,2,/jonwhiting/smoker-status-using-bio-signals,Binary Prediction of Smoker Status using Bio-Signals
16012,153298678,777.0,,0,6,/swarnasridhar045/fork-of-notebookb4aa8124fe,Binary Prediction of Smoker Status using Bio-Signals
16013,148369765,705.0,,0,6,/nartaa/smoking-classifier,Binary Prediction of Smoker Status using Bio-Signals
16014,149791563,747.0,0.8705385915413564,1,11,/pramodiasuka/smokepred-with-lgbm,Binary Prediction of Smoker Status using Bio-Signals
16015,150053969,778.0,0.8705293048261289,2,5,/danishelahi/binary-prediction-of-smoker,Binary Prediction of Smoker Status using Bio-Signals
16016,148122589,773.0,,0,1,/mukund23/pss3e24-eda-xgboost,Binary Prediction of Smoker Status using Bio-Signals
16017,148511402,720.0,,2,12,/khansahil128/easy-notebook-86-auc-score-with-catboots,Binary Prediction of Smoker Status using Bio-Signals
16018,149560263,847.0,,2,11,/magantiit/eda-smoker-status-predictions,Binary Prediction of Smoker Status using Bio-Signals
16019,150301283,760.0,,0,5,/soleil31/smokers,Binary Prediction of Smoker Status using Bio-Signals
16020,150476978,783.0,,0,7,/sb0702/eda-5-models-performance-comparison,Binary Prediction of Smoker Status using Bio-Signals
16021,150398431,800.0,0.8699768356077957,1,1,/daniliur/catboost,Binary Prediction of Smoker Status using Bio-Signals
16022,147988376,929.0,0.8698430590295418,0,2,/setyoab/simple-smoker-prediction-using-xgboost,Binary Prediction of Smoker Status using Bio-Signals
16023,149236900,927.0,,0,1,/ananth360/smoker-prediction-eda-pipelines-xgboost,Binary Prediction of Smoker Status using Bio-Signals
16024,161206490,928.0,,0,5,/psydelix/smoker-status-eda-baseline-prediction,Binary Prediction of Smoker Status using Bio-Signals
16025,147774199,770.0,,9,22,/mpwolke/smoking-effect-on-oral-health,Binary Prediction of Smoker Status using Bio-Signals
16026,149552772,827.0,,1,12,/jirkaborovec/smoker-classif-eda-xgboost-gpu,Binary Prediction of Smoker Status using Bio-Signals
16027,149451577,836.0,,1,4,/valentinbelyaev/s3e24-initial-eda-part-1,Binary Prediction of Smoker Status using Bio-Signals
16028,150309503,772.0,0.869387047886929,0,5,/imessam/binary-prediction-of-smoker-status-using-bio-signa,Binary Prediction of Smoker Status using Bio-Signals
16029,148782128,963.0,0.8693219234413314,0,10,/lonewalker29/votingclassifier-xgb-lgbm-catboost-gridsearch,Binary Prediction of Smoker Status using Bio-Signals
16030,150190973,820.0,0.869183950677063,0,1,/egorbrazh/notebookbfba303ee5,Binary Prediction of Smoker Status using Bio-Signals
16031,150541884,838.0,,2,5,/raaggeesingh/smoking-status-prediction-using-xgbclassifier,Binary Prediction of Smoker Status using Bio-Signals
16032,148252569,866.0,0.7894993900398714,4,16,/lordpatil/very-simple-lightgbm,Binary Prediction of Smoker Status using Bio-Signals
16033,149694938,812.0,,3,13,/rakgyunim/real-simple-baseline,Binary Prediction of Smoker Status using Bio-Signals
16034,150113889,997.0,0.868351199720748,2,5,/swatibajaj54/binary-prediction-smoker-status-xgboost-beginner,Binary Prediction of Smoker Status using Bio-Signals
16035,149432749,998.0,,0,4,/muhannadmansour/ps3e24-xgboost-recursive-feature-elimination,Binary Prediction of Smoker Status using Bio-Signals
16036,150491828,848.0,0.8681339149756051,0,6,/rushikeshdhaigude/xgboost-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16037,148095990,829.0,0.8670141566397845,2,17,/ucas0v0zhuoqunli/eda-automl-baseline1,Binary Prediction of Smoker Status using Bio-Signals
16038,150325102,946.0,0.8660339474610408,8,8,/edilsoncastro/smoker-status-using-bio-signals,Binary Prediction of Smoker Status using Bio-Signals
16039,148100449,861.0,0.8678532041335638,0,3,/christph/r-h2o-automl,Binary Prediction of Smoker Status using Bio-Signals
16040,150541015,857.0,0.8677869504667568,0,0,/nursyahrina/smoking-prediction-tf-df-with-eda-and-fe,Binary Prediction of Smoker Status using Bio-Signals
16041,149090456,902.0,,0,2,/selfmade95/classify,Binary Prediction of Smoker Status using Bio-Signals
16042,150506431,922.0,0.8672661717124487,0,21,/anopsy/eda-fe-xgb-smokers,Binary Prediction of Smoker Status using Bio-Signals
16043,149265099,991.0,0.8675845849922346,6,27,/nazimcherpanov/prediction-smoker-status-using-votting,Binary Prediction of Smoker Status using Bio-Signals
16044,150334865,954.0,,0,3,/keitashimizu21/en-ja-eda-and-feature-creation-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16045,148043357,1017.0,,0,5,/theusman/simple-and-accurate-smoke-preds,Binary Prediction of Smoker Status using Bio-Signals
16046,149453379,988.0,,0,7,/mvoulo/smoker-status-prediction,Binary Prediction of Smoker Status using Bio-Signals
16047,147809721,950.0,0.8578995527922659,0,16,/itsnobita/pss34-eda-modelling,Binary Prediction of Smoker Status using Bio-Signals
16048,147809721,950.0,0.8042515133370962,0,16,/itsnobita/pss34-eda-modelling,Binary Prediction of Smoker Status using Bio-Signals
16049,147809721,950.0,0.8578230503137609,0,16,/itsnobita/pss34-eda-modelling,Binary Prediction of Smoker Status using Bio-Signals
16050,147809721,950.0,0.8260381698449878,0,16,/itsnobita/pss34-eda-modelling,Binary Prediction of Smoker Status using Bio-Signals
16051,147809721,950.0,0.866529350356328,0,16,/itsnobita/pss34-eda-modelling,Binary Prediction of Smoker Status using Bio-Signals
16052,149215607,1002.0,0.8662793227129929,6,10,/vishsin01/its-smoking-hot-with-catboost-xbboost-lgbm,Binary Prediction of Smoker Status using Bio-Signals
16053,148486273,1037.0,,0,17,/alkanerturan/smokingstatus,Binary Prediction of Smoker Status using Bio-Signals
16054,149605566,1024.0,0.8658927406072283,0,1,/cicinguyen/smoker-status-xgboost,Binary Prediction of Smoker Status using Bio-Signals
16055,152351344,1047.0,,0,1,/sergiolopez13/proyecto-2-smoker-status-sals,Binary Prediction of Smoker Status using Bio-Signals
16056,150530623,1026.0,,1,6,/riyadmehdi/ps3e24-eda-models-predictions,Binary Prediction of Smoker Status using Bio-Signals
16057,151008798,1052.0,,6,16,/memocan/comprehensive-eda-feature-crafting-pycaret,Binary Prediction of Smoker Status using Bio-Signals
16058,149915907,1018.0,0.8652352538164063,0,3,/syeshwanth/smoking-classification-eda-outlier-removal-pca,Binary Prediction of Smoker Status using Bio-Signals
16059,150686674,1004.0,,0,0,/abdurrahmansyafiqi/smoker-status-prediction-catboost-w-auc-0-86490,Binary Prediction of Smoker Status using Bio-Signals
16060,147808989,1030.0,,0,5,/abramova/ps3-e24-quick-and-simple-run-of-multiple-models,Binary Prediction of Smoker Status using Bio-Signals
16061,150286408,1058.0,,2,8,/eshraqsaeed/ps3e24-eda,Binary Prediction of Smoker Status using Bio-Signals
16062,150499351,1104.0,0.8632936528011551,0,6,/suraj520/ps-s3-e24-soft-voting-k-fold-cv-optuna,Binary Prediction of Smoker Status using Bio-Signals
16063,149975484,1111.0,0.7798945596470903,0,0,/carljvh/smoking-classifier-using-random-trees,Binary Prediction of Smoker Status using Bio-Signals
16064,150067772,1118.0,,0,2,/hollowcain/smoki-random-forest-above-0-86151,Binary Prediction of Smoker Status using Bio-Signals
16065,150426825,1143.0,0.8608059829933865,20,38,/hikmatullahmohammadi/smoking-status-feature-engineering-tf-keras,Binary Prediction of Smoker Status using Bio-Signals
16066,148716742,1125.0,0.8595770470341412,1,7,/grassymonkey/pg-s3-e24-eda-rf-clf,Binary Prediction of Smoker Status using Bio-Signals
16067,150571776,1132.0,,0,3,/waltuu/binary-prediction-of-smoker-status-fast-ai,Binary Prediction of Smoker Status using Bio-Signals
16068,148111572,1141.0,,0,8,/levgolovnin/smoki,Binary Prediction of Smoker Status using Bio-Signals
16069,148379614,1147.0,,0,6,/harshitajakiya/beginnercatboost-xgboostapproach,Binary Prediction of Smoker Status using Bio-Signals
16070,148778644,1176.0,0.8608257669489779,0,5,/brukselka/prediction-of-smoker-status-starter,Binary Prediction of Smoker Status using Bio-Signals
16071,150585584,1163.0,0.8605570890881458,0,0,/stanislavsamsonenko/samsonenko,Binary Prediction of Smoker Status using Bio-Signals
16072,149156038,1169.0,0.8581939452784821,1,7,/ryanml2/mum-said-smoking-was-bad,Binary Prediction of Smoker Status using Bio-Signals
16073,147931632,1152.0,,0,2,/mrmarvels30/smoki-re,Binary Prediction of Smoker Status using Bio-Signals
16074,150342524,1195.0,0.8606553810191104,0,0,/juanfaz/smoker,Binary Prediction of Smoker Status using Bio-Signals
16075,148926019,1171.0,0.8546814981892711,0,14,/saurabhru/binary-prediction-of-smoker-status-with-nn-model,Binary Prediction of Smoker Status using Bio-Signals
16076,150450504,1188.0,0.8605582318600099,0,3,/p7476762/regression-classification-model-s-compare,Binary Prediction of Smoker Status using Bio-Signals
16077,148510782,1179.0,0.8605568000075162,0,5,/gordonbchen/smoking-prediction-kaggle-comp,Binary Prediction of Smoker Status using Bio-Signals
16078,147822261,1175.0,0.8603343660136575,0,4,/qwerty29544/smoki,Binary Prediction of Smoker Status using Bio-Signals
16079,150541795,1184.0,0.8602145104744753,0,0,/proxod3/hw1-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16080,150499760,1183.0,,0,0,/zakyabasith/smoker-status-identifier-using-mlp,Binary Prediction of Smoker Status using Bio-Signals
16081,149652374,1181.0,0.7728867663946659,1,14,/harshagrawal12/binary-prediction-of-smoker-status-using-bio-signa,Binary Prediction of Smoker Status using Bio-Signals
16082,150329941,1182.0,,0,1,/luishiramhernandez/notebook5b3fa91d4d,Binary Prediction of Smoker Status using Bio-Signals
16083,149080319,1165.0,0.8594744053430773,0,6,/franklinshih0617/out-of-bag-random-forest-model,Binary Prediction of Smoker Status using Bio-Signals
16084,147845997,1210.0,,0,4,/rakeshku1993/eda-and-base-line-model-roc-0-85,Binary Prediction of Smoker Status using Bio-Signals
16085,150647671,1226.0,,2,8,/anmolarora15/smoking-prediction-xgb-ada-boost,Binary Prediction of Smoker Status using Bio-Signals
16086,150571995,1230.0,,0,0,/mikhailbykov/bykov-yurchenkov-smoki,Binary Prediction of Smoker Status using Bio-Signals
16087,150064296,1217.0,0.8587092315008271,14,20,/chestadhingra/eda-fe-cv-ensemble,Binary Prediction of Smoker Status using Bio-Signals
16088,148354983,1223.0,0.8483451353511643,0,6,/dipayancodes/binary-classifications-prediction,Binary Prediction of Smoker Status using Bio-Signals
16089,150351291,1261.0,0.8338802091426085,0,2,/piratemeow/notebookcac5ba6931,Binary Prediction of Smoker Status using Bio-Signals
16090,147774239,1237.0,0.8573621699692923,4,7,/chiranjeevisrinivas/pg-series-s3e24,Binary Prediction of Smoker Status using Bio-Signals
16091,150236217,1287.0,0.8566362252718623,0,1,/rautaishwarya/prediction-using-hybrid-nn-xgboost-model,Binary Prediction of Smoker Status using Bio-Signals
16092,149975434,1272.0,,2,10,/yashkalkani/binary-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16093,150346011,1239.0,0.8564520402588139,0,3,/vinitkp/binaryprediction-smokerstatus,Binary Prediction of Smoker Status using Bio-Signals
16094,149853824,1279.0,,9,11,/abhijit89kumar/smoke-smoke-smoke-that-cigarette,Binary Prediction of Smoker Status using Bio-Signals
16095,148099800,1252.0,0.8558810924646075,0,12,/sibangibhowmick/eda-prediction-smoking,Binary Prediction of Smoker Status using Bio-Signals
16096,150231525,1271.0,,0,2,/skullking2596/binary-prediction-of-smoker-status-using-bio-signa,Binary Prediction of Smoker Status using Bio-Signals
16097,148263493,1278.0,0.8532569088463732,0,10,/lasm1984/p3e24-profilereport-pca-fnn-and-kerastuner,Binary Prediction of Smoker Status using Bio-Signals
16098,147788494,1288.0,0.8548857562385407,0,11,/prajwaldongre/smoker-status-adv-eda-rdmforest-roc-0-85,Binary Prediction of Smoker Status using Bio-Signals
16099,152066889,1269.0,,0,4,/michaeltezak/eda-viz-pipelines-stacking,Binary Prediction of Smoker Status using Bio-Signals
16100,150397841,1296.0,0.8539269977458938,10,29,/hemanthpingali/smoker-status-prediction-bio-signals,Binary Prediction of Smoker Status using Bio-Signals
16101,148986839,1298.0,0.8536756647228403,1,6,/tejeshsai555/binary-prediction-with-randomforestregressor,Binary Prediction of Smoker Status using Bio-Signals
16102,155228811,1294.0,,2,4,/yanlukianchik/prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16103,150471668,1275.0,0.8355500020958345,0,2,/jesusenriqueescobedo/lostios-binarypred-smokerstat,Binary Prediction of Smoker Status using Bio-Signals
16104,150471668,1275.0,0.8355500020958345,0,2,/jesusenriqueescobedo/lostios-binarypred-smokerstat,Binary Prediction of Smoker Status using Bio-Signals
16105,148739873,1303.0,,0,4,/ahirao/playground-s3-24-eda-and-baseline-simple-lightgbm,Binary Prediction of Smoker Status using Bio-Signals
16106,147799892,1311.0,0.8510108878605647,1,4,/pohzixiang/ps3e24-prediction-with-xgboost,Binary Prediction of Smoker Status using Bio-Signals
16107,151031308,1313.0,,0,0,/jageshkar/smoker-prediction-v3,Binary Prediction of Smoker Status using Bio-Signals
16108,148861485,1322.0,,0,1,/vinodkumargurjar/prediction-smoke-status-vinod,Binary Prediction of Smoker Status using Bio-Signals
16109,148860452,1324.0,0.8491115106847815,0,2,/mahendra77/smoking-prediction,Binary Prediction of Smoker Status using Bio-Signals
16110,148207913,1330.0,0.8478273648421584,0,7,/coinshot/binary-prediction-of-smoker-status-model,Binary Prediction of Smoker Status using Bio-Signals
16111,150454144,1340.0,0.846539795200828,0,4,/danyamyakota/smoking-prediction-using-randomforest,Binary Prediction of Smoker Status using Bio-Signals
16112,150479238,1329.0,,0,6,/remoanil/smoking-prediction-with-explanation,Binary Prediction of Smoker Status using Bio-Signals
16113,149340398,1350.0,0.8452122737131035,0,5,/aguinaldomulonde/binary-prediction-of-smoker-logistic-regression,Binary Prediction of Smoker Status using Bio-Signals
16114,147764034,1348.0,,0,8,/edmondkirsch/simple-and-quick-implemention-pb-0-84,Binary Prediction of Smoker Status using Bio-Signals
16115,150563420,1392.0,0.8375537689971142,0,0,/kevstrider/smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16116,148825626,1399.0,0.8374620220322802,0,0,/wintersbae/playground-s3e24-smoker-prediction,Binary Prediction of Smoker Status using Bio-Signals
16117,147826850,1372.0,,3,9,/rizal1015/smoking-02,Binary Prediction of Smoker Status using Bio-Signals
16118,148140212,1397.0,,0,7,/santiagoormando/simple-deep-learning-model-tutorial,Binary Prediction of Smoker Status using Bio-Signals
16119,147878811,1406.0,0.8355306472443027,0,4,/tracyporter/play-3-24-jax-linear-reression,Binary Prediction of Smoker Status using Bio-Signals
16120,148718741,1411.0,,0,5,/joachimandre/smoker-prediction-auc-0-83,Binary Prediction of Smoker Status using Bio-Signals
16121,151247807,1414.0,0.8303376570159509,1,10,/radhakrishnanb/smoker-signal,Binary Prediction of Smoker Status using Bio-Signals
16122,150386645,1415.0,0.8323839955568307,0,0,/demonickelodeon/smoker-status-using-binary-classification,Binary Prediction of Smoker Status using Bio-Signals
16123,150515009,1423.0,,0,1,/itsmegood/simple-prediction-using-auto-keras,Binary Prediction of Smoker Status using Bio-Signals
16124,150375764,1453.0,,0,5,/gouthamb002/predictsmoker-logit-with-graph,Binary Prediction of Smoker Status using Bio-Signals
16125,149346928,1466.0,,0,1,/hopesb/binary-prediction-of-smoker-status-using-bio-signa,Binary Prediction of Smoker Status using Bio-Signals
16126,147784067,1469.0,,0,1,/manaknarang/baseline-model-xgboost-hyperparameter-tuning,Binary Prediction of Smoker Status using Bio-Signals
16127,151387131,1470.0,,0,2,/lc3287/smoker-status-using-bio-signal-data-preprocessin,Binary Prediction of Smoker Status using Bio-Signals
16128,150667392,1487.0,,3,9,/tatianakushniruk/smoker-status-pred-eda-xgboost-optuna,Binary Prediction of Smoker Status using Bio-Signals
16129,149807755,1480.0,0.785384218871617,0,0,/yeehawww/binary-prediction-of-smoker,Binary Prediction of Smoker Status using Bio-Signals
16130,149750039,1497.0,0.7897416757425939,4,12,/rahulcris07/catboost-auc-0-87-for-smoking-classification,Binary Prediction of Smoker Status using Bio-Signals
16131,150467458,1508.0,0.7895429237759423,10,16,/yeonseokcho/smoking-status-prediction-using-biosignals,Binary Prediction of Smoker Status using Bio-Signals
16132,150193550,1553.0,,1,5,/ayoubchnaida/prediction-of-smoker-status-using,Binary Prediction of Smoker Status using Bio-Signals
16133,149008400,1533.0,,1,7,/vladislavonufrienko/ps3e24-lgbmclassifier,Binary Prediction of Smoker Status using Bio-Signals
16134,148869315,1516.0,0.4998030276859746,0,2,/abhiramreddygeesidi/s3e24,Binary Prediction of Smoker Status using Bio-Signals
16135,147956683,1542.0,0.7842045621259568,0,10,/harshsoni2001/smoker-status-using-bio-signals-with-xgboost,Binary Prediction of Smoker Status using Bio-Signals
16136,149555900,1526.0,,0,6,/yakinoki/kolmogorov-smirnov,Binary Prediction of Smoker Status using Bio-Signals
16137,156349320,1524.0,,0,0,/srsses/binary-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16138,147791770,1571.0,0.7855116311591339,1,6,/joebeachcapital/pss3e24-eda-starter-model-submission,Binary Prediction of Smoker Status using Bio-Signals
16139,149609982,1583.0,,0,5,/anushkrishna/automl,Binary Prediction of Smoker Status using Bio-Signals
16140,148659818,1573.0,0.7837536776476353,0,3,/amitvikramraj/solution-binary-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16141,150593930,1701.0,0.7742832787814095,0,3,/pluspin/ps-s3-e24,Binary Prediction of Smoker Status using Bio-Signals
16142,147910775,1660.0,0.7807637347627405,4,26,/jocelyndumlao/smoker-status-prediction-with-roc-auc,Binary Prediction of Smoker Status using Bio-Signals
16143,149003086,1658.0,0.7802791633572957,0,2,/imtommi/smoker-prediction,Binary Prediction of Smoker Status using Bio-Signals
16144,150351005,1669.0,0.7760448729020877,0,2,/debopamdas/sempai-notice-me,Binary Prediction of Smoker Status using Bio-Signals
16145,152457077,1707.0,0.8767227489110694,0,1,/galrozental/smoker-status-binary-prediction-xgboost,Binary Prediction of Smoker Status using Bio-Signals
16146,150582511,1704.0,0.7781809167758549,2,8,/piyushjoshi01/ps-s3-ep24-eda-lgb-catboost,Binary Prediction of Smoker Status using Bio-Signals
16147,148707749,1696.0,0.7768964592681779,0,5,/rainrein/project3-smoke-prediction,Binary Prediction of Smoker Status using Bio-Signals
16148,150581607,1710.0,0.5502368925422256,0,3,/zonwie/s13e24-eda-feature-importance-mlpclassifier,Binary Prediction of Smoker Status using Bio-Signals
16149,149209106,1724.0,,0,1,/amirmoosa/binary-prediction-of-smoking-randomforestclassifie,Binary Prediction of Smoker Status using Bio-Signals
16150,150539795,1721.0,,0,8,/sajjadfc13/classification-using-random-forrest,Binary Prediction of Smoker Status using Bio-Signals
16151,150446648,1729.0,,1,8,/scienceenthusiast/smoker-status-prediction-randomforestclassifier,Binary Prediction of Smoker Status using Bio-Signals
16152,150301835,1748.0,,0,3,/soroushsrd/smoking-prediction-competition-svc,Binary Prediction of Smoker Status using Bio-Signals
16153,152599256,1715.0,,0,0,/v23joshi/notbook,Binary Prediction of Smoker Status using Bio-Signals
16154,150461108,1740.0,0.772851999932066,0,3,/josefersonbarreto1/smoker-binary-lgbm-classifier,Binary Prediction of Smoker Status using Bio-Signals
16155,156421522,1789.0,,0,7,/bhavyaprakash02/binary-classification-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16156,150511773,1794.0,0.7524822359953082,0,2,/satishpb/predict-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16157,149521785,1796.0,,0,5,/asheniranga/eda-prediction-submission,Binary Prediction of Smoker Status using Bio-Signals
16158,150344352,1811.0,0.7369334471347411,0,0,/vigneshshanmug/smoking-v1,Binary Prediction of Smoker Status using Bio-Signals
16159,150189033,1814.0,,0,4,/eduardomarinho44/binary-prediction-of-smoker-status,Binary Prediction of Smoker Status using Bio-Signals
16160,149137815,1830.0,0.7078084381913092,0,6,/shashwatpsit/binary-prediction,Binary Prediction of Smoker Status using Bio-Signals
16161,150472604,1838.0,0.6656460464249037,4,16,/tuhinm2002/binary-pred-smoker-eda,Binary Prediction of Smoker Status using Bio-Signals
16162,150543370,1845.0,,0,13,/sunilkumaradapa/binary-predicitons-of-smoke-status,Binary Prediction of Smoker Status using Bio-Signals
16163,150400191,1852.0,0.5,0,2,/nazninhussain/notebook3fb2998d3b,Binary Prediction of Smoker Status using Bio-Signals
16164,150208523,1854.0,,0,2,/soyabulislamlincoln/no-more-smoking-smoking-kills,Binary Prediction of Smoker Status using Bio-Signals
16165,149543555,1902.0,,0,2,/bustedplayer/smoking,Binary Prediction of Smoker Status using Bio-Signals
16166,151124514,1903.0,,8,16,/khsamaha/smoker-status-age-and-hemoglobin-level-py,Binary Prediction of Smoker Status using Bio-Signals
16167,157663358,163.0,0.8286918531159145,7,50,/cpmpml/ai-generated-text-detection-cluster,LLM - Detect AI Generated Text
16168,161684146,1.0,,0,2,/ubamba98/private-score-0-984-single-llm,LLM - Detect AI Generated Text
16169,153423383,296.0,0.7195412960664668,0,3,/bestpredict/llmd-deberta-base-ft-v1,LLM - Detect AI Generated Text
16170,160227316,73.0,,0,4,/boristown/llm-daigt-analyse-edge-cases,LLM - Detect AI Generated Text
16171,159917678,2.0,0.967298482550189,0,14,/wowfattie/daigt-2nd-place,LLM - Detect AI Generated Text
16172,164320261,1597.0,,0,2,/wcqyfly/fork-of-fork-of-fork-of-llm-daigt-analyse-e-db6333,LLM - Detect AI Generated Text
16173,158976725,300.0,0.8547879247537951,0,1,/yitounian/word-embedding,LLM - Detect AI Generated Text
16174,159777177,1873.0,,13,50,/rhoguy/eda-for-llm-detection-dataset-relation,LLM - Detect AI Generated Text
16175,160075916,449.0,0.953085498040703,7,50,/yekenot/llm-detect-by-regression-fm-ftrl,LLM - Detect AI Generated Text
16176,152182602,121.0,0.9401645867089554,3,41,/lizhecheng/balanced-weights-longer-training-higher-score,LLM - Detect AI Generated Text
16177,158415557,95.0,0.9583891747394307,2,14,/cuboorandell/llm-public-score-0-961,LLM - Detect AI Generated Text
16178,150927615,183.0,0.8722578458073338,1,10,/pamilovedl/ai-generated-text-detection-quick-baseline-0,LLM - Detect AI Generated Text
16179,151885582,18.0,,0,3,/junglebeastds/llm-make-5-prompt-train-dataset-v4,LLM - Detect AI Generated Text
16180,155849705,181.0,,5,4,/sorkun/roc-auc-sensitivity-experiments,LLM - Detect AI Generated Text
16181,157506532,336.0,0.910240416106457,8,101,/aerdem4/daigt-superfast-unsupervised-baseline,LLM - Detect AI Generated Text
16182,160120469,27.0,,2,8,/mingkaizhu/public-0-966-private-0-923-solution,LLM - Detect AI Generated Text
16183,150193857,339.0,0.8954061735098424,24,118,/x75a40890/ai-generated-text-detection-quick-baseline,LLM - Detect AI Generated Text
16184,156974645,442.0,,0,4,/yuhaya9/vectorize-with-sentence-transformers-lb-0-77,LLM - Detect AI Generated Text
16185,159300785,283.0,0.966038010939888,0,0,/wasimmadha/llm-daigtext,LLM - Detect AI Generated Text
16186,155718643,35.0,,14,24,/etiennekaiser/eda-gemini-pro-original-llm-daigt-dataset,LLM - Detect AI Generated Text
16187,161141699,327.0,,0,5,/ootake/efficiency-lb-5th-place-solution,LLM - Detect AI Generated Text
16188,160125730,107.0,0.9658753346893278,0,0,/reiendo73/daigt-ensemble-two-stage-prediction,LLM - Detect AI Generated Text
16189,154462237,326.0,0.9602990944714492,0,7,/shhrkre/llm-daigt-cv-0-9983-lb-0-960-67a7be,LLM - Detect AI Generated Text
16190,150099363,384.0,0.8612315920869675,3,23,/xiaocao123/ai-generated-text-detection-quick-baselin-sgd,LLM - Detect AI Generated Text
16191,150247754,2522.0,,0,0,/sorokin/persuade,LLM - Detect AI Generated Text
16192,150349122,1987.0,0.8964517185506946,2,23,/guochangzhang/ai-generated-text-detection-quick-baselin-f6d640,LLM - Detect AI Generated Text
16193,149967407,1756.0,0.714523829018283,9,53,/narsil/find-typos-0-714-lb-in-14-lines-of-code,LLM - Detect AI Generated Text
16194,150233533,1938.0,0.6031839656519691,0,10,/lonnieqin/ai-generated-text-detector-with-kerasnlp,LLM - Detect AI Generated Text
16195,156069435,142.0,0.9611083459739602,0,10,/zskagcomp/llm-daigtext-0-961,LLM - Detect AI Generated Text
16196,159649219,514.0,0.963316146389952,0,4,/piotrkoz/0-963-levenshtein-distance-daigt,LLM - Detect AI Generated Text
16197,166751394,205.0,,0,0,/celtoy/late-submission,LLM - Detect AI Generated Text
16198,154699763,767.0,0.6570089762815872,0,3,/serjhenrique/daigt-stylometric-voting-clf,LLM - Detect AI Generated Text
16199,154064121,79.0,,0,0,/jdonnelly0804/return-overflowing-tokens,LLM - Detect AI Generated Text
16200,158943472,437.0,0.9429478588501626,2,6,/danshatzz/spacy-embeddings-tfidf-ensemble,LLM - Detect AI Generated Text
16201,160896690,47.0,,0,3,/superfei/solution-of-4th-place-in-efficiency-lb,LLM - Detect AI Generated Text
16202,157825032,1205.0,,0,6,/snassimr/setfit-sample-notebook,LLM - Detect AI Generated Text
16203,151110752,199.0,,9,31,/nahman/0-908-don-t-try-this-at-home,LLM - Detect AI Generated Text
16204,162675638,539.0,,0,0,/yamsam/fix-words-train,LLM - Detect AI Generated Text
16205,160005143,173.0,0.9639555394674848,0,0,/raichucy/detect-ai-generated-text-raichucy,LLM - Detect AI Generated Text
16206,159473433,122.0,,2,11,/olegshpagin/0-963-optimizations-detect-human-or-ai-text,LLM - Detect AI Generated Text
16207,150351113,1989.0,0.896202676652762,4,29,/newtonbaba12345/using-confidence-to-determine-the-weights,LLM - Detect AI Generated Text
16208,160062925,513.0,,0,0,/zhijianjiang6666/exp4-llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16209,151947284,167.0,,15,109,/pamin2222/ai-or-not-ai-delving-into-essays-with-eda,LLM - Detect AI Generated Text
16210,156004798,357.0,0.8288135909722941,12,32,/pranshubahadur/detect-llm-generated-essays-using-retention,LLM - Detect AI Generated Text
16211,159004960,467.0,,0,6,/zhangyue199/meta-classifier,LLM - Detect AI Generated Text
16212,160113599,394.0,0.9553015579572748,0,2,/mchernyshev/llm-detect-private-0-928-public-code-tuning,LLM - Detect AI Generated Text
16213,153973927,345.0,0.9601572465267004,24,90,/batprem/llm-daigt-cv-0-9983-lb-0-960,LLM - Detect AI Generated Text
16214,151814981,450.0,,0,3,/humbleyll/llm-detect-ai-generated-text-bert-vit,LLM - Detect AI Generated Text
16215,151508477,463.0,0.929221646211834,34,80,/yongsukprasertsuk/ai-generated-text-mod-weight-add-more-data-0-929,LLM - Detect AI Generated Text
16216,159626181,654.0,0.9630376575769068,3,24,/user7979/detect-ai-text,LLM - Detect AI Generated Text
16217,158913163,441.0,0.9621571229933004,0,3,/lenferdetroud/bpe-tf-idf,LLM - Detect AI Generated Text
16218,153280501,408.0,0.8277247733305753,0,7,/malabhbakshi/starter-notebook,LLM - Detect AI Generated Text
16219,157769399,675.0,,0,4,/zhuior/llm-generated-text-detection,LLM - Detect AI Generated Text
16220,159956506,387.0,0.9631378489100332,0,0,/bohaoxu/llm-ensemble962,LLM - Detect AI Generated Text
16221,160019861,323.0,0.7082247029452661,0,0,/younglak/llm-daigtext-0-961,LLM - Detect AI Generated Text
16222,157764599,810.0,,0,7,/myominhtet/multinomialnb-single-model-0-916,LLM - Detect AI Generated Text
16223,150190329,896.0,,0,12,/hubert101/0-827-countvectorizer-for-begginers,LLM - Detect AI Generated Text
16224,157502553,418.0,,0,1,/konstantinboyko/separate-voting-for-different-models,LLM - Detect AI Generated Text
16225,159873540,152.0,,0,1,/nikotin55/daigt-152-place,LLM - Detect AI Generated Text
16226,149974620,367.0,0.8598689540455752,0,2,/iteachmachines/random-forest-and-xgboost-ensemble,LLM - Detect AI Generated Text
16227,152649717,867.0,,0,1,/lovemaid/1mnb-1sgd,LLM - Detect AI Generated Text
16228,151273226,236.0,0.9170884398593442,3,12,,LLM - Detect AI Generated Text
16229,161040526,316.0,0.9397966798244104,0,2,/gali1eo/3rd-place-efficiency-solution-v69,LLM - Detect AI Generated Text
16230,160019115,175.0,0.9626681347031176,3,55,/youxuanlim/detect-ai-generated-text-private-0-908,LLM - Detect AI Generated Text
16231,152041227,951.0,0.7974691453787017,0,1,/barinoffn/logreg-dummy,LLM - Detect AI Generated Text
16232,161557307,956.0,,0,0,/valuejack/llm-daigt-excluded-prompts,LLM - Detect AI Generated Text
16233,150264279,964.0,0.8780928238586089,0,0,/fuuaad/ai-generated-text-detection-quick-baselin-bc5607,LLM - Detect AI Generated Text
16234,159961993,751.0,,10,66,/mfmfmf3/clean-code-detect-ai-generated,LLM - Detect AI Generated Text
16235,149082654,984.0,0.5017161805771021,0,8,/minhtien1405/data-understanding,LLM - Detect AI Generated Text
16236,154196420,1591.0,0.9606835203571552,10,98,/verracodeguacas/sentencepiece-constructions,LLM - Detect AI Generated Text
16237,149109922,986.0,0.648730981602142,1,22,/ianchute/one-magic-feature-no-model-tag-prp,LLM - Detect AI Generated Text
16238,160463694,991.0,,0,1,/kenjikonno/llm-distillbert-how-to-tune-up,LLM - Detect AI Generated Text
16239,151626791,992.0,0.9265809402328172,0,1,/donghunlim/newstart3-dnn-and-tfidf-and-sc-for-df,LLM - Detect AI Generated Text
16240,166044989,998.0,,0,0,/yangruiii/llama-logits-new,LLM - Detect AI Generated Text
16241,153509002,1009.0,0.9577914382735202,0,1,/amulil/llm-daigt-preprocessing-bypass-catboost-added,LLM - Detect AI Generated Text
16242,160153609,486.0,0.9636915945576354,0,0,/heartssix/popular-daigt-levenshtein-correction-but-late,LLM - Detect AI Generated Text
16243,151921740,1048.0,0.9329244162328634,0,5,/farisalahmdi/ai-text-generated-detection-baseline-0-933-lb,LLM - Detect AI Generated Text
16244,157795418,1055.0,,0,6,/rajkumardubey10/bert-llm,LLM - Detect AI Generated Text
16245,158096687,1057.0,0.7442688043690604,0,23,/pdx250697/llm-competition-distillbert,LLM - Detect AI Generated Text
16246,158096687,1057.0,0.621539269256846,0,23,/pdx250697/llm-competition-distillbert,LLM - Detect AI Generated Text
16247,158096687,1057.0,0.700662950609623,0,23,/pdx250697/llm-competition-distillbert,LLM - Detect AI Generated Text
16248,159164446,1061.0,,0,0,/liujingtao/7-se7en-prompts-8e34b0,LLM - Detect AI Generated Text
16249,158396641,1063.0,0.5748343072361843,0,1,/vinitkp/pytorch-llm-text,LLM - Detect AI Generated Text
16250,150525798,1092.0,,1,7,/kevinbnisch/nlp-analysis-of-llms-students-essays,LLM - Detect AI Generated Text
16251,157906785,4110.0,0.5553991637076109,0,7,/serhiikharchuk/lightgbm-model-feature-engineering-tf-idf-vectoriz,LLM - Detect AI Generated Text
16252,159201345,1117.0,,0,3,/bromotdi/detect-fake-text,LLM - Detect AI Generated Text
16253,153577317,272.0,0.9587276347088632,0,0,/kevinvonkampl/llm-deneme2,LLM - Detect AI Generated Text
16254,166049428,1147.0,,0,5,/youssefismail20/daigt,LLM - Detect AI Generated Text
16255,153502740,2951.0,0.9551343928477034,0,4,/csmimrankhan/llm-daigt-sub-8ae3af,LLM - Detect AI Generated Text
16256,149040141,593.0,,0,3,/shadie520/0-805-detectai-simple-baseline,LLM - Detect AI Generated Text
16257,152112484,1165.0,0.73181419571138,0,2,/janderchu/roberta-det,LLM - Detect AI Generated Text
16258,154006097,2712.0,0.6915250700980223,2,10,/sasidharanm10/llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16259,159645789,8.0,0.9031894959262708,0,2,/abdullahmeda/perplexity-features,LLM - Detect AI Generated Text
16260,159328797,1231.0,0.781032559669505,0,0,/pandas007/llm-daigt-analyse-edge-cases,LLM - Detect AI Generated Text
16261,157229565,370.0,0.9560984202089152,1,13,/suryanshsharma1/approachable-solution,LLM - Detect AI Generated Text
16262,153959381,1734.0,0.908700198802588,0,11,/grafael/skorch-bnn-bpe,LLM - Detect AI Generated Text
16263,160653407,112.0,,0,2,/thomasgamet/token-game-ensemble-playbook-extension,LLM - Detect AI Generated Text
16264,158814935,40.0,0.9035821813125566,0,2,/xyzdivergence/efficiency-lb-1st-place-solution,LLM - Detect AI Generated Text
16265,152055675,491.0,,0,1,/phucpx/0-937-aidetector-remove-special-character-in-llm,LLM - Detect AI Generated Text
16266,158411162,1200.0,,0,2,/ahmedmaghrabi/daigt-cluster,LLM - Detect AI Generated Text
16267,158974001,1598.0,,0,2,/rajatgupta1901/essaywriting,LLM - Detect AI Generated Text
16268,159018285,1772.0,0.962126060088944,0,0,/pparalyzed/jiangzc,LLM - Detect AI Generated Text
16269,159018285,1772.0,0.9620818897162756,0,0,/pparalyzed/jiangzc,LLM - Detect AI Generated Text
16270,154826000,1561.0,,1,12,/alexmoura2023/alex-public-0-959-balanced-data-by-prompt-name,LLM - Detect AI Generated Text
16271,160119125,676.0,0.9424104526493604,7,53,/ichigoe/ensemble-transformercnn-roberta,LLM - Detect AI Generated Text
16272,148850430,763.0,,1,9,/yavuzhanbaykara/detect-ai-generated-text-external-datas,LLM - Detect AI Generated Text
16273,153386954,185.0,,0,1,/sjoonpark/notebook4f57f14dab,LLM - Detect AI Generated Text
16274,159473540,146.0,0.9612203878948758,0,0,/rechawine/detect-ai-generated-text-146th-solution,LLM - Detect AI Generated Text
16275,157297434,1312.0,,0,1,/wu468ef/notebookf0d55a9692,LLM - Detect AI Generated Text
16276,159821137,4288.0,0.8127151061238093,0,0,/nourelhwaryy/notebook5f575d2908,LLM - Detect AI Generated Text
16277,149915525,494.0,0.7741319264890083,2,14,/vonewman/starter-notebook-detectai-galsenai,LLM - Detect AI Generated Text
16278,157713641,1523.0,0.9611015229082636,0,0,/abdelkaderdebbaghi/premier,LLM - Detect AI Generated Text
16279,157713641,1523.0,0.9610961362774504,0,0,/abdelkaderdebbaghi/premier,LLM - Detect AI Generated Text
16280,154807985,1485.0,0.7486217407292493,0,7,/zakirkhanaleemi/detecting-fake-text-infer-nlp,LLM - Detect AI Generated Text
16281,156322261,1593.0,0.9572649848887048,0,11,/denisding/sentencepiece-constructions,LLM - Detect AI Generated Text
16282,149028386,2163.0,,0,14,/mozattt/daigt-script-example-to-generate-ai-essay,LLM - Detect AI Generated Text
16283,153988375,1353.0,0.93419943174636,0,0,/colin4ever/colin-s-adjustment-of-baseline,LLM - Detect AI Generated Text
16284,159814051,1550.0,0.955198852863102,0,2,/dileepjayamal/lstm-transformer-0-955,LLM - Detect AI Generated Text
16285,153989032,1694.0,0.5,0,1,/gagandeep44489/s-and-llm-analysis,LLM - Detect AI Generated Text
16286,155486042,1714.0,0.7827485606922466,0,0,/zainalinasir/deeplearningaitextdetection,LLM - Detect AI Generated Text
16287,155003857,1651.0,0.9607865845600486,0,5,/owaislone/detect-ai-text,LLM - Detect AI Generated Text
16288,151269776,1356.0,,0,0,/deepsh2207/notebook18112023,LLM - Detect AI Generated Text
16289,155692899,764.0,0.9586455783661414,0,1,/taiheekim/detect-ai-text,LLM - Detect AI Generated Text
16290,158489867,1347.0,,0,3,/oussamalariouch/catboost-llm,LLM - Detect AI Generated Text
16291,150392374,1402.0,0.8819884352627527,1,5,/andrusha95/ai-gtd-weight-lr-sgd-rf,LLM - Detect AI Generated Text
16292,163370707,1377.0,,0,5,/yaswanthgali/generate-synthetic-essays-with-mistral-7b-instruct,LLM - Detect AI Generated Text
16293,152283531,1429.0,0.930101283023638,0,2,/soranoki/notebookc709586748,LLM - Detect AI Generated Text
16294,156900988,466.0,,0,0,/symonmwenewungu/notebookb18e01f3f9,LLM - Detect AI Generated Text
16295,156844656,1652.0,0.7391691014237942,0,23,/riteshbhalerao/xlnet-cnn,LLM - Detect AI Generated Text
16296,151417485,1440.0,0.8985483748175729,3,4,/ilhansevval/exploring-ensemble-learning-with-voting-classifier,LLM - Detect AI Generated Text
16297,149473117,1808.0,0.7740179094701278,1,10,/defdet/deberta-xsmall-training-with-processed-ds,LLM - Detect AI Generated Text
16298,158534696,1843.0,0.901634016501764,0,4,/klausmikaelson2002/lstm-transformer-cnn-approach,LLM - Detect AI Generated Text
16299,158114336,1846.0,,0,1,/hli111111/your-local-llm-build-your-custom-daigt-data,LLM - Detect AI Generated Text
16300,156683425,1853.0,0.7538248669861298,0,3,/igalriklin/deberta-first-try,LLM - Detect AI Generated Text
16301,149599907,792.0,,1,36,/rsuhara/ai-generated-text-detection-quick-baseline,LLM - Detect AI Generated Text
16302,156172041,1499.0,0.7192342581101114,0,0,/maxtrox/p-tuning,LLM - Detect AI Generated Text
16303,154973028,1469.0,0.7747941229703175,0,2,/erikfolkesson/llm-detecting-ai-generated-text,LLM - Detect AI Generated Text
16304,154884826,2020.0,0.6345443915836408,0,2,/carrot1500/predicting-ai-generation-with-lm-score-features,LLM - Detect AI Generated Text
16305,154235193,2203.0,,0,0,/rakasinghssdfsf/notebook4687b0aee0,LLM - Detect AI Generated Text
16306,156921236,598.0,,4,20,/cheesegue/eda-llm-detect,LLM - Detect AI Generated Text
16307,155124340,648.0,0.7281692421944129,0,1,/shaikikozashvili/distilbert-base-notebook,LLM - Detect AI Generated Text
16308,154933842,639.0,0.9558831345307454,0,32,/finlay/llm-detect-0-to-1,LLM - Detect AI Generated Text
16309,154710980,615.0,,1,4,/stopwhispering/llm-student-n-gram-feature-importance,LLM - Detect AI Generated Text
16310,152113085,2173.0,0.9401520179037244,16,94,/siddhvr/llm-detect-ai-gt-sub,LLM - Detect AI Generated Text
16311,153160953,1691.0,0.8311975342158789,0,6,/pshikk/bi-lstm-approach,LLM - Detect AI Generated Text
16312,150653273,28.0,0.7659780038726285,0,4,/myncoder0908/inference-longformers-score-improve-0-735-0-823,LLM - Detect AI Generated Text
16313,157524108,1986.0,0.7960380971259812,0,4,/lookb4uplay/nj-ai-classification,LLM - Detect AI Generated Text
16314,151326925,2060.0,0.9112229375667942,0,7,/murugesann/detect-fake-text-kerasnlp-nm-inf,LLM - Detect AI Generated Text
16315,157853798,2008.0,0.8318582942623045,0,3,/sineer666/llm-text-detection-with-lstm,LLM - Detect AI Generated Text
16316,158961970,2007.0,,0,4,/namanjr333/naman21112074llm,LLM - Detect AI Generated Text
16317,158943473,2004.0,,0,2,/jyoti404/llm-detect-ai-generated,LLM - Detect AI Generated Text
16318,158047203,2013.0,0.9572107594718516,0,7,/v1o1oo/llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16319,159367748,2064.0,,6,28,/rishabh0517/llm-detect-0-801-using-bidirectional-nn,LLM - Detect AI Generated Text
16320,150784240,2680.0,,9,98,/carlmcbrideellis/llm-make-7-prompt-train-dataset-v4,LLM - Detect AI Generated Text
16321,149864605,2157.0,,0,0,/hozaifazaki/mistral-inference-perplexity-xgboost,LLM - Detect AI Generated Text
16322,157295336,2098.0,0.956114220992634,0,1,/sauravmishraa/llm-detect-ai-generated-notebook,LLM - Detect AI Generated Text
16323,155198000,2937.0,0.7598598685949368,0,1,/anthonynam/lora-fine-tuning-with-distilbert-7-prompts-v4,LLM - Detect AI Generated Text
16324,158850769,2130.0,,2,15,/bmart80/llm-detect-ai-generated-text-nn-baseline,LLM - Detect AI Generated Text
16325,157979298,2132.0,0.9560973428827524,0,2,/huyryu/notebook820f02cae2,LLM - Detect AI Generated Text
16326,159559537,2102.0,0.8039754771836684,0,1,/zhangxiaojie6/detectai-transformers-baseline,LLM - Detect AI Generated Text
16327,155071138,1962.0,0.9558806207696992,0,11,/nurfarahfauziah/finalproject-ml,LLM - Detect AI Generated Text
16328,158900482,2268.0,,0,2,/jeannkouagou/saved-deberta-embeddings-for-efficiency-submission,LLM - Detect AI Generated Text
16329,154011213,4181.0,0.9349524827340526,0,0,/medolotfy/0-960-llm-daigt-sub-mod-weights,LLM - Detect AI Generated Text
16330,156302310,699.0,0.5593612102251181,0,0,/jshtang/llm-competition-using-glove-with-voting-classifier,LLM - Detect AI Generated Text
16331,159288255,2165.0,0.5758489689270406,0,0,/yuxuezhang1128/bert-based-classifier,LLM - Detect AI Generated Text
16332,159073676,2162.0,0.9543141885292056,0,20,/priyankraval/ai-detection-text-llm,LLM - Detect AI Generated Text
16333,154786070,2230.0,0.94071527993243,0,0,/oortcloudk/sp-am-bw-001,LLM - Detect AI Generated Text
16334,154786070,2230.0,0.9407691462405628,0,0,/oortcloudk/sp-am-bw-001,LLM - Detect AI Generated Text
16335,151695200,4287.0,,0,0,/kareem87/train-qlora-mistral-for-sequence-classification,LLM - Detect AI Generated Text
16336,154120444,2210.0,0.8202206579446341,0,11,/joonyeongs/cnn-text-classification,LLM - Detect AI Generated Text
16337,155608041,1998.0,0.9380002384481908,12,34,/hsinhungwu/two-stages-prompt-prediction-custom-models,LLM - Detect AI Generated Text
16338,154656107,2205.0,,0,1,/junghyukchoi/llm-report,LLM - Detect AI Generated Text
16339,160087096,2223.0,,0,0,/firecracker1994/twin-encoders,LLM - Detect AI Generated Text
16340,151585345,2313.0,,0,0,/tonyyunyang99/llm-detect-ai-generated-text-quick-baseline,LLM - Detect AI Generated Text
16341,153024948,2317.0,0.8951515654267361,0,0,/yutarohori/ai-generated-text-detection-quick-baseline,LLM - Detect AI Generated Text
16342,158306879,2322.0,,0,0,/derrickmwiti/detect-ai-content-with-tensorflow,LLM - Detect AI Generated Text
16343,156710811,2325.0,0.9341924291263028,0,6,/aphysict/train-your-own-tokenizer,LLM - Detect AI Generated Text
16344,159277495,2338.0,,0,5,/dky7376/train-daigt-bert-pipeline,LLM - Detect AI Generated Text
16345,158978747,2357.0,,0,0,/kasvisingh/essaywriting2,LLM - Detect AI Generated Text
16346,154200661,2331.0,,0,0,/johnsonl8/voting-with-larger-dataset,LLM - Detect AI Generated Text
16347,158974284,3821.0,0.9455844350788888,0,2,/ruhong/daigt-train-your-own-tokenizer,LLM - Detect AI Generated Text
16348,159379228,7.0,0.9422458013008354,0,1,/tailen/daigt-deberta,LLM - Detect AI Generated Text
16349,153428177,2475.0,0.5112995354569586,0,0,/burakyener/notebookf77ea9241a,LLM - Detect AI Generated Text
16350,155722658,1956.0,0.7369185670700176,0,24,/paradoxplusparadise/ai-text-detection-bert-model,LLM - Detect AI Generated Text
16351,156824841,2555.0,,3,56,/phanisrikanth/generate-synthetic-essays-with-mistral-7b-instruct,LLM - Detect AI Generated Text
16352,154210499,2558.0,,0,0,/simengxu/pure-regression-with-large-dataset,LLM - Detect AI Generated Text
16353,151212207,2560.0,0.911494782868503,5,22,/imnandini/llm-essay-detection,LLM - Detect AI Generated Text
16354,154410468,2280.0,,0,0,/ducnh279/mistral-7b-dolly,LLM - Detect AI Generated Text
16355,151621183,2613.0,0.524356548993921,1,4,/fekihmea/text-generated-svm,LLM - Detect AI Generated Text
16356,151386330,2602.0,,0,2,/mullerf/use-typo-number-to-predict,LLM - Detect AI Generated Text
16357,152234996,2638.0,0.9401785919490696,0,6,/bhanupratapbiswas/detect-ai-gt-sub,LLM - Detect AI Generated Text
16358,165842527,2665.0,,0,1,/tarekyahia/generative-question-answer-system-with-haystack,LLM - Detect AI Generated Text
16359,149315731,2386.0,,0,7,/prithviraj7387/ai-generated-essay-prediction-eda,LLM - Detect AI Generated Text
16360,151587211,2478.0,0.8873883530986773,0,0,/yoojiinn/notebook06c0ce7d67,LLM - Detect AI Generated Text
16361,155885455,2299.0,,0,11,/treblemaker123/analysis-predicting-on-out-of-distribution-data,LLM - Detect AI Generated Text
16362,151854551,2436.0,0.728398533112697,0,0,/sakurakinomoto/notebook5873e96c8f,LLM - Detect AI Generated Text
16363,157046631,2536.0,0.7964516108180784,0,0,/jacoballessio/transformers-based-llm-detect,LLM - Detect AI Generated Text
16364,158243896,2524.0,0.9354471549970698,0,2,/yeyuuu/explained-bpe-tokenizer-tf-idf-vectorizer,LLM - Detect AI Generated Text
16365,153098196,2734.0,0.6903409090909091,0,3,/hirakuhasegawa/tf-idf,LLM - Detect AI Generated Text
16366,152300301,2461.0,0.9338460687650106,0,1,/c4nter/nm-llm-detect-ai-text-typo-correct-with-testdata,LLM - Detect AI Generated Text
16367,151690071,2590.0,,1,34,/jdragonxherrera/using-the-augmented-data,LLM - Detect AI Generated Text
16368,151787295,2422.0,0.9306478464968224,0,3,/tmleyncodes/llm-dectect-ai-generated-text,LLM - Detect AI Generated Text
16369,152992571,2510.0,,0,0,/ayakakoba/ayaka,LLM - Detect AI Generated Text
16370,150515746,2428.0,0.519497448891647,0,3,/al1337/0-838-ridgeclf-svd-9-countvec,LLM - Detect AI Generated Text
16371,151119596,3268.0,0.7669468792015721,0,0,/deltawi/bert-sequence-classification,LLM - Detect AI Generated Text
16372,151589772,2441.0,,0,2,/ilyalion/llm-2023-nb-eda,LLM - Detect AI Generated Text
16373,159192328,4252.0,,0,3,/molotfy/extract-important-features,LLM - Detect AI Generated Text
16374,149651046,2492.0,0.5290317854311029,0,8,/sunilthite/llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16375,149198317,2757.0,,4,11,/satyaprakashshukl/detect-ai-boost,LLM - Detect AI Generated Text
16376,159464539,2547.0,,0,26,/amitkumarupadhyay012/llm-vs-human-response,LLM - Detect AI Generated Text
16377,159346087,2526.0,0.9051631574562462,8,30,/umar47/detect-ai-eda-tensorflow-0-91,LLM - Detect AI Generated Text
16378,151817816,2054.0,,0,1,/milantokic/tfidf-and-typo-syllable-length-analysis,LLM - Detect AI Generated Text
16379,151184133,2784.0,0.911494782868503,0,0,,LLM - Detect AI Generated Text
16380,158944451,2677.0,,0,1,/garvsethi/work-is-going-on,LLM - Detect AI Generated Text
16381,149207274,2864.0,,0,7,/hridaym25/interesting-visualizations-and-analytics,LLM - Detect AI Generated Text
16382,149800527,2847.0,0.7219665368129533,0,2,/vujjinisravya/beginner-notebook,LLM - Detect AI Generated Text
16383,151349217,2465.0,0.8233326941198101,2,13,/luficergfree/ai-detector-with-tf-keras,LLM - Detect AI Generated Text
16384,151984289,2868.0,0.5,0,2,/hariharanalm/llm-generated-or-not,LLM - Detect AI Generated Text
16385,156159575,3063.0,,0,1,/b10705052/irtmfinal,LLM - Detect AI Generated Text
16386,156302038,3099.0,,0,0,/boketto/explained-llm-model,LLM - Detect AI Generated Text
16387,150980966,3077.0,0.8939977491065375,0,4,/mrgarlic/without-grammer-correction,LLM - Detect AI Generated Text
16388,159074164,2946.0,,0,0,/krishkhadria/datapreprocessingfortextclassification,LLM - Detect AI Generated Text
16389,154804148,2722.0,0.8911552240263844,0,0,/ericliu365/detect-llm-written-essay,LLM - Detect AI Generated Text
16390,152635586,2572.0,,0,1,/scr0ll0/exploratory-data-analysis,LLM - Detect AI Generated Text
16391,150938916,2825.0,0.7368262761287505,0,0,/muhammadtayyab212/getting-started-withxgboost,LLM - Detect AI Generated Text
16392,153979529,2900.0,,0,0,/nidhipriya123/chexk,LLM - Detect AI Generated Text
16393,152553266,2841.0,0.7597555475115202,3,4,/rachanabv14/llm-detect-ai-generated-text-for-beginners,LLM - Detect AI Generated Text
16394,152155263,2837.0,0.7469653517541742,0,1,/sjorslockhorst/ai-text-detection-fine-tuned-roberta,LLM - Detect AI Generated Text
16395,157193713,2819.0,,0,42,/alnourabdalrahman9/detect-llm-generated-text-using-distilbert-0-94,LLM - Detect AI Generated Text
16396,156473367,2459.0,0.6698846399145033,3,9,/akshatshaw7/simple-tf-idf-from-basics,LLM - Detect AI Generated Text
16397,158901622,6.0,0.7666091374495811,0,1,/davidecozzolino/coder-one,LLM - Detect AI Generated Text
16398,154317215,3241.0,0.871836790832098,0,0,/scottnewcomer/detect-ai-generated-tfidf-stylometry,LLM - Detect AI Generated Text
16399,159232417,2816.0,0.8184044655887659,1,13,/cybersimar08/llm-detect-ai-baseline,LLM - Detect AI Generated Text
16400,157905567,2673.0,,0,5,/mohanapriyan/tuning-llm,LLM - Detect AI Generated Text
16401,149011035,3275.0,,0,2,/roshansalunke/llm-ai-detect,LLM - Detect AI Generated Text
16402,150031663,465.0,,3,21,/markwijkhuizen/daigt-mistral-7b-tpu-bfloat16-train,LLM - Detect AI Generated Text
16403,152337843,3051.0,,0,2,/nyl0522/distill-bert,LLM - Detect AI Generated Text
16404,148862936,3128.0,0.8544778343733122,10,112,/hotchpotch/infer-llm-detect-ai-comp-mistral-7b,LLM - Detect AI Generated Text
16405,156650226,2822.0,0.8342088403948471,0,3,/indubarnwal/llm-text-transformers,LLM - Detect AI Generated Text
16406,156650226,2822.0,0.8537395068431759,0,3,/indubarnwal/llm-text-transformers,LLM - Detect AI Generated Text
16407,156297754,2981.0,0.8444718085289759,0,2,/kk3103/llm-ai-vs-human-essay,LLM - Detect AI Generated Text
16408,156729037,3256.0,0.8428037485204721,0,3,/saurav9786/detecting-llm-generated-text,LLM - Detect AI Generated Text
16409,156272149,3061.0,0.8191067026924534,16,24,/dafaaqilla/bert-llm-detection,LLM - Detect AI Generated Text
16410,152342949,3066.0,0.8427245650475172,0,3,/cristhianccalah/tf-rnn-llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16411,158913365,2899.0,0.7803861639719147,0,1,/shaileshkumar591/llm-detect,LLM - Detect AI Generated Text
16412,154725168,3478.0,,0,0,/robinsingh301/minorproject,LLM - Detect AI Generated Text
16413,158163658,2898.0,0.8139673182335299,0,1,/blohorn/ai-or-academia-unraveling-text-origins-with-disti,LLM - Detect AI Generated Text
16414,162617774,2934.0,,0,0,/hzhangsg/distilbert-detect-ai-generated-text,LLM - Detect AI Generated Text
16415,157344415,2967.0,0.8043577484170487,0,0,/ktoprakucar/pytorch-based-llm-model,LLM - Detect AI Generated Text
16416,150784498,3559.0,0.8355809948173428,0,4,/nanthiphatsangworn/multinomial-naive-baye,LLM - Detect AI Generated Text
16417,159282003,3624.0,,73,282,/awsaf49/detect-fake-text-kerasnlp-tf-torch-jax-train,LLM - Detect AI Generated Text
16418,148912062,3429.0,,2,9,/thomasrochefort/0-683-logisticregression-baseline-extradata,LLM - Detect AI Generated Text
16419,151929508,2823.0,,0,3,/vaibhavnakrani/comprehensive-evaluation-of-pos-tags,LLM - Detect AI Generated Text
16420,156585522,3604.0,,0,0,/solomonschwiger/notebookd5de7ba397,LLM - Detect AI Generated Text
16421,157988842,3056.0,,0,0,/ppujari/llm-detect-ai-gen-text-exploratory-data-analysis,LLM - Detect AI Generated Text
16422,154776697,3331.0,0.6353408947265602,0,1,/okadarowout/bert-gan-detect-ai-generated-text,LLM - Detect AI Generated Text
16423,149958280,3681.0,,2,5,/gowthamrajgoku/llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16424,153577382,3471.0,0.6845161656381793,0,2,/xpehutta/generate-text-gru-tensorflow-nn,LLM - Detect AI Generated Text
16425,160546410,3082.0,,0,0,/ankushrautcu/detecting-llm-generated-text-using-distilbert,LLM - Detect AI Generated Text
16426,149118337,3359.0,0.4145770130198458,0,4,/stpeteishii/ai-generated-text-countvectorizer-xgb,LLM - Detect AI Generated Text
16427,151660160,3522.0,0.7224157818227784,0,0,/yoolimhan/notebook7309ae766b,LLM - Detect AI Generated Text
16428,160024282,3441.0,,0,5,/bguberfain/naive-submission-train,LLM - Detect AI Generated Text
16429,159017202,3341.0,0.7673648817526804,0,1,/bisili/bert-based-classifier,LLM - Detect AI Generated Text
16430,149855823,3339.0,0.7925928080578252,0,2,/talmanr/deep-embedding-model-transfer-learning,LLM - Detect AI Generated Text
16431,158780095,3123.0,0.677597397467278,29,63,/suyashkapil/detecting-llm-generated-texts,LLM - Detect AI Generated Text
16432,152528595,3524.0,,0,0,/vineetjhaa03/detect-llm-generated-essays-using-retention,LLM - Detect AI Generated Text
16433,149897409,3650.0,0.7831290363820228,0,3,/susangrapes/detect-ai-generated,LLM - Detect AI Generated Text
16434,157768409,3315.0,,1,22,/shuvendumoharana/ai-generated-text-prediction,LLM - Detect AI Generated Text
16435,156916163,3465.0,0.7719268193884236,0,0,/majingms/mj-llm-detect-ai-comp-mistral-7b,LLM - Detect AI Generated Text
16436,157747188,3538.0,,0,1,/yugamjayant/d05-transfer-learning-model-02,LLM - Detect AI Generated Text
16437,149604043,3502.0,0.6170557968766159,2,9,/ilankhirin/gltr-paper-implementation-detecting-llm-gen-text,LLM - Detect AI Generated Text
16438,153776078,4007.0,,0,0,/ahmedmagdy16/llm-ai-generated-detect-with-embed-layer,LLM - Detect AI Generated Text
16439,160041523,3540.0,0.6986397320761656,0,0,/vitalymegabyte/notebook2945baefc9,LLM - Detect AI Generated Text
16440,153788768,3794.0,0.7581348898541731,1,0,/rishavsanson/llm-detect-ai-generated-text-bert,LLM - Detect AI Generated Text
16441,149619731,3724.0,0.7311780346123349,0,5,/tlisted/my-notebook-llm-detect-baseline,LLM - Detect AI Generated Text
16442,159588911,3973.0,0.5004734848484849,0,0,/dhattori/llmstudy,LLM - Detect AI Generated Text
16443,154931327,3801.0,0.7525748095287343,0,0,/rafaelbaez/ml-finalproject-rafaelbaez,LLM - Detect AI Generated Text
16444,159768520,3443.0,,0,0,/sansaaa/detect-ai-text-llm,LLM - Detect AI Generated Text
16445,157352113,3562.0,0.739353503751968,0,0,/mariusdumitrescu/llm-ai-generated-text,LLM - Detect AI Generated Text
16446,152793219,3732.0,0.7486210225118076,0,4,/mohdrafi/detect-ai-generated-text,LLM - Detect AI Generated Text
16447,157500379,3541.0,,0,1,/shrinidhi9/detect-ai-generated-text-train-torch-distilbert,LLM - Detect AI Generated Text
16448,153687157,3915.0,,0,0,/suandikanapitupulu/nlp-using-roberta-kelompok-07,LLM - Detect AI Generated Text
16449,159084293,3809.0,0.4908712767607818,0,2,/khushikhushikhushi/detect-ai-generated,LLM - Detect AI Generated Text
16450,152908185,3005.0,,0,1,/aljapotonik/datasets-eda,LLM - Detect AI Generated Text
16451,157711391,3957.0,0.2054421490215005,0,1,/quanminh11/notebook56ae1f78de,LLM - Detect AI Generated Text
16452,155094411,3925.0,0.4935279630778777,0,3,/shrutimechlearn/just-length,LLM - Detect AI Generated Text
16453,150805783,3989.0,,0,2,/susishengg/llm-7-prompt-train-dataset,LLM - Detect AI Generated Text
16454,153853576,3682.0,,0,21,/yassinabdulmahdi/simple-eda,LLM - Detect AI Generated Text
16455,158345590,3036.0,0.510984238000023,0,3,/pushpendramishra5027/train-your-own-custom-tokenizer,LLM - Detect AI Generated Text
16456,151675508,3573.0,0.4418897450040795,1,4,/jagdmir/essay-classification-kerasnlp-transformer-encoder,LLM - Detect AI Generated Text
16457,153430723,3347.0,0.6940799490927477,0,0,/chenxiguan/aigc-detection,LLM - Detect AI Generated Text
16458,156310200,3894.0,,0,2,/avdyveyg/notebookd5de7ba397,LLM - Detect AI Generated Text
16459,160046565,3862.0,0.5227892189816251,0,1,/maciejzajecki/dswts-xgboost,LLM - Detect AI Generated Text
16460,149724027,3470.0,0.6397141207294791,9,9,/rui314/anti-chatgpt,LLM - Detect AI Generated Text
16461,149213958,3608.0,,0,4,/guidosalimbeni/predicting-essay-generated-with-custom-features,LLM - Detect AI Generated Text
16462,151879247,3554.0,0.5497746233667735,3,40,/iqmansingh/llm-detect-ai-text-starter-notebook,LLM - Detect AI Generated Text
16463,152620462,4105.0,,0,0,/vincenthodgins/hodgins-llm,LLM - Detect AI Generated Text
16464,149456180,3511.0,0.6357351961020904,0,3,/noured/detect-ai-deberta-pytorch-train-infer,LLM - Detect AI Generated Text
16465,156020430,3630.0,0.5395721650521139,0,0,/nguyentuannguyen/llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16466,152688484,4160.0,0.5044486388343045,0,1,/mayakaripel/notebookbe71f3d92e,LLM - Detect AI Generated Text
16467,153510367,3728.0,0.4122289806483493,0,0,/jamalcao/detect-ai-generated-essays,LLM - Detect AI Generated Text
16468,153906089,3786.0,0.6023086381448156,0,0,/ekuras/llm-svm-model-with-average-sentence-length,LLM - Detect AI Generated Text
16469,157919712,3365.0,0.4181935969478632,0,1,/claudiojnior/llm-competition,LLM - Detect AI Generated Text
16470,158373374,3874.0,0.5791906551292217,0,4,/aaronogle/detecting-ai-generated-text-cnn-vs-xgboost,LLM - Detect AI Generated Text
16471,153884788,4335.0,0.5009001060088945,0,0,/ahmedmagdyhosney/llm-competition-using-random-forest,LLM - Detect AI Generated Text
16472,156681615,3810.0,0.5732057491869779,0,1,/rakeshsharma02/llm-detect-ai,LLM - Detect AI Generated Text
16473,154200554,4347.0,0.5454132479516438,0,0,/renitasequeira/notebook528d63d39c,LLM - Detect AI Generated Text
16474,152105498,3409.0,0.5552666525896048,0,3,/giabchnguyn/detect-ai-generated-text-with-scikit-learn,LLM - Detect AI Generated Text
16475,160679319,3958.0,0.4997146881212581,0,0,/arwani/pytorch-rnn,LLM - Detect AI Generated Text
16476,156652464,4000.0,,0,0,/shelitodelgado/c-digo-02,LLM - Detect AI Generated Text
16477,149521061,4329.0,,14,33,/jocelyndumlao/autollm-gpt2-ai-generated-text,LLM - Detect AI Generated Text
16478,153486535,4312.0,0.4990932504797691,0,0,/aditrichaudhari/nb-predict,LLM - Detect AI Generated Text
16479,152119394,4009.0,0.5,0,0,/hrithiman/notebookc547b33cac,LLM - Detect AI Generated Text
16480,152461899,3556.0,,2,8,/gabrielbuchhorn/latent-dirichlet-allocation-pandas,LLM - Detect AI Generated Text
16481,152461899,3556.0,,2,8,/gabrielbuchhorn/latent-dirichlet-allocation-pandas,LLM - Detect AI Generated Text
16482,152461899,3556.0,,2,8,/gabrielbuchhorn/latent-dirichlet-allocation-pandas,LLM - Detect AI Generated Text
16483,150261554,4148.0,,1,3,/dankabhi98/llm-machine-learning-model-nb,LLM - Detect AI Generated Text
16484,153923350,3710.0,0.5266807006354788,0,0,/fermingarcia/battle-of-the-algorithms,LLM - Detect AI Generated Text
16485,148933122,4104.0,0.4377799252479286,0,7,/saurabhru/llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16486,156055780,4035.0,0.5109889064133945,2,6,/arviinndn/llm-text-generation-evaluation-using-deberta-rf,LLM - Detect AI Generated Text
16487,157201331,4036.0,,0,3,/ankitmaddheshiya/llm-ai,LLM - Detect AI Generated Text
16488,155459534,4134.0,,0,0,/highjay/roberta-10epoch,LLM - Detect AI Generated Text
16489,149561668,4332.0,,0,2,/koheiedwardyamada/based-onai-or-not-ai-delving-into-essays-with-eda,LLM - Detect AI Generated Text
16490,152431150,4182.0,0.5001896094046265,0,1,/ravindra1010/naive-bayes,LLM - Detect AI Generated Text
16491,150524479,4218.0,,0,1,/ponderpiece/we-detecting-now,LLM - Detect AI Generated Text
16492,153177866,4227.0,0.5,0,0,/sayedshaun/voting-model,LLM - Detect AI Generated Text
16493,153222600,4122.0,0.5,0,1,/haseebwar07/detect-ai-generated-text-xgbclassifier,LLM - Detect AI Generated Text
16494,153813638,4237.0,0.5,0,1,/kazumaishii/lightgbm-firstsubmission,LLM - Detect AI Generated Text
16495,156244851,4258.0,0.5,0,1,/tauter/detect-llm-fake-text-scikit-learn-library,LLM - Detect AI Generated Text
16496,156674296,3373.0,,0,6,/koushiksahu/detect-ai-generated-text-dataset,LLM - Detect AI Generated Text
16497,157382978,4099.0,,0,0,/chintanvhparmar/fork-of-notebook1554722fbf,LLM - Detect AI Generated Text
16498,158252446,4272.0,0.5,0,0,/meetp2997/notebook09454a1782,LLM - Detect AI Generated Text
16499,158252446,4272.0,0.5,0,0,/meetp2997/notebook09454a1782,LLM - Detect AI Generated Text
16500,158490445,4275.0,0.5,0,4,/sankha1234/detect-ai-text-v1,LLM - Detect AI Generated Text
16501,165989303,4278.0,,0,2,/shaziyasultana/llm-daigt-final-sub1,LLM - Detect AI Generated Text
16502,150958806,4175.0,0.4999262031578584,0,0,/upesshreya/llm-or-student,LLM - Detect AI Generated Text
16503,153493268,4167.0,,0,0,/vinodpgowda/initial,LLM - Detect AI Generated Text
16504,158300773,4289.0,0.4994311717861205,0,7,/abdelrahmanahmed110/ai-text-detection-prediction,LLM - Detect AI Generated Text
16505,148791044,4318.0,0.4739874211397249,1,7,,LLM - Detect AI Generated Text
16506,157831533,4058.0,0.4737186282621436,0,2,/vivekyogi/llm-detect-ai-text,LLM - Detect AI Generated Text
16507,149899327,4343.0,0.465625395019593,0,3,/shuvojitdas/llm-detect-by-classification,LLM - Detect AI Generated Text
16508,157648057,4294.0,0.4512904930993668,0,1,/satishsathawane/llm-detect-ai-generated-text,LLM - Detect AI Generated Text
16509,154520247,4341.0,0.3982666540260396,0,0,/nguyenvietdat/ai-text-detection,LLM - Detect AI Generated Text
16510,152867309,4357.0,,1,3,/jenilgajjar/llm-detect-ai-generated-text-using-multinomial,LLM - Detect AI Generated Text
16511,161055950,4.0,0.876338005065918,0,1,/igorkrashenyi/fork-of-multiview-2-5-sennet-hoa-inference-v3,SenNet + HOA - Hacking the Human Vasculature in 3D
16512,161055950,4.0,0.876338005065918,0,1,/igorkrashenyi/fork-of-multiview-2-5-sennet-hoa-inference-v3,SenNet + HOA - Hacking the Human Vasculature in 3D
16513,151653560,16.0,0.5562136231031144,5,31,/hengck23/lb0-534-baseline-simple-unet-seresnext26d-32x4,SenNet + HOA - Hacking the Human Vasculature in 3D
16514,151438485,214.0,,5,22,/limitz/slicing-xz-and-zy,SenNet + HOA - Hacking the Human Vasculature in 3D
16515,155374131,270.0,,0,8,/markwatney/full-free-slice-rotations-animation,SenNet + HOA - Hacking the Human Vasculature in 3D
16516,156459250,84.0,,1,1,/yasinadyaman/unet3dinfer,SenNet + HOA - Hacking the Human Vasculature in 3D
16517,155746177,367.0,,0,6,/sonujha090/sennet-fastai-starter,SenNet + HOA - Hacking the Human Vasculature in 3D
16518,156994469,488.0,0.0477965287864208,0,0,/kyotaroh/sennet-hoa-attention-gated-unet-inference,SenNet + HOA - Hacking the Human Vasculature in 3D
16519,156710253,306.0,,0,7,,SenNet + HOA - Hacking the Human Vasculature in 3D
16520,157096336,284.0,0.812804102897644,7,14,,SenNet + HOA - Hacking the Human Vasculature in 3D
16521,157367962,653.0,,0,0,/ducchu12/training-6,SenNet + HOA - Hacking the Human Vasculature in 3D
16522,159840929,254.0,0.1634687483310699,0,0,/aeyeee/sennet-yolov8-inference,SenNet + HOA - Hacking the Human Vasculature in 3D
16523,156873739,919.0,0.7287259101867676,1,26,,SenNet + HOA - Hacking the Human Vasculature in 3D
16524,157193444,825.0,,2,28,,SenNet + HOA - Hacking the Human Vasculature in 3D
16525,154774137,15.0,,15,104,/junkoda/fast-surface-dice-computation,SenNet + HOA - Hacking the Human Vasculature in 3D
16526,156694315,51.0,,25,119,/yoyobar/2-5d-cutting-model-baseline-training,SenNet + HOA - Hacking the Human Vasculature in 3D
16527,157401872,183.0,,0,1,,SenNet + HOA - Hacking the Human Vasculature in 3D
16528,150451053,77.0,0.0,0,3,/harshitsheoran/notebooke824b39459,SenNet + HOA - Hacking the Human Vasculature in 3D
16529,157220285,9.0,0.8271968960762024,0,5,/tereka/simpleunet-xy-xz-yz-v2-nbp-b749ff,SenNet + HOA - Hacking the Human Vasculature in 3D
16530,159981917,98.0,,12,43,/jirkaborovec/sennet-hoa-rle-decode-encode-demo-submission,SenNet + HOA - Hacking the Human Vasculature in 3D
16531,157675034,805.0,0.0,0,9,/nimaiji/segnet-tensorflow-blood-vessel-segmentation,SenNet + HOA - Hacking the Human Vasculature in 3D
16532,161992281,1134.0,,0,0,/noahbittermann/segformer-submission3,SenNet + HOA - Hacking the Human Vasculature in 3D
16533,152069636,148.0,,5,32,/squidinator/sennet-hoa-in-memory-tiled-dataset-pytorch,SenNet + HOA - Hacking the Human Vasculature in 3D
16534,152597638,661.0,0.1230690375427222,2,6,/dieptam/blood-vessel-segmentation-submission-notebook,SenNet + HOA - Hacking the Human Vasculature in 3D
16535,151475646,759.0,,1,6,/zenglinlin/1-explore-dataset,SenNet + HOA - Hacking the Human Vasculature in 3D
16536,155449209,368.0,,0,2,/athrunzala/2d-method,SenNet + HOA - Hacking the Human Vasculature in 3D
16537,156224594,896.0,,0,4,,SenNet + HOA - Hacking the Human Vasculature in 3D
16538,154468970,961.0,,0,6,/langzhelu/sennet-submission-for-resnext-on-patched-images,SenNet + HOA - Hacking the Human Vasculature in 3D
16539,159073024,959.0,,0,1,/aaalexlit/convert-binary-to-coco-to-yolo,SenNet + HOA - Hacking the Human Vasculature in 3D
16540,160138952,926.0,,0,18,/awsaf49/sennet-hoa-kerascv-starter-notebook-train,SenNet + HOA - Hacking the Human Vasculature in 3D
16541,149945203,908.0,,0,3,/miltiadesgeneral/preparing-coco-dataset,SenNet + HOA - Hacking the Human Vasculature in 3D
16542,163113266,986.0,,0,0,/cyrielled/light-submission-preprocessed-in-dataloader,SenNet + HOA - Hacking the Human Vasculature in 3D
16543,151185270,1014.0,,0,5,/dhinkris/interactive-3d-viewer-tiff-to-nifti-images,SenNet + HOA - Hacking the Human Vasculature in 3D
16544,150197636,1019.0,,1,9,/pangyuteng/tiff-to-nifti-visualize-using-itksnap,SenNet + HOA - Hacking the Human Vasculature in 3D
16545,159398872,2.0,0.0256427247077226,0,3,/ojimaryoji/sennet-hoa-2nd-place-solution,SenNet + HOA - Hacking the Human Vasculature in 3D
16546,161848651,1034.0,0.0042275465093553,0,4,/jtakahashi64/simple-train-and-infer-implement-with-pytorch,SenNet + HOA - Hacking the Human Vasculature in 3D
16547,161848651,1034.0,0.0042275465093553,0,4,/jtakahashi64/simple-train-and-infer-implement-with-pytorch,SenNet + HOA - Hacking the Human Vasculature in 3D
16548,155170888,1056.0,,0,4,/pranshubahadur/so-hoa-eda-395-rows-w-all-0-masks,SenNet + HOA - Hacking the Human Vasculature in 3D
16549,162624818,1071.0,0.0,0,0,/hzhangsg/segmentation-models-pytorch-sennet-hoa-test,SenNet + HOA - Hacking the Human Vasculature in 3D
16550,157770136,1037.0,0.0,0,0,/b45370/inferencenb,SenNet + HOA - Hacking the Human Vasculature in 3D
16551,150353110,1086.0,,0,9,/stpeteishii/blood-vessel-mask-slide-show,SenNet + HOA - Hacking the Human Vasculature in 3D
16552,150604837,1088.0,0.0,10,20,/salmankhaliq22/tf-keras-unet-starter-sennet-hoa,SenNet + HOA - Hacking the Human Vasculature in 3D
16553,150854124,1093.0,0.0,0,11,/busharakmea/sennet-hoa-hacking-the-human-vasculature-in-3d,SenNet + HOA - Hacking the Human Vasculature in 3D
16554,150431428,1094.0,,0,17,/shreydan/first-look-monai-animations-rle,SenNet + HOA - Hacking the Human Vasculature in 3D
16555,152283110,1103.0,0.0,1,10,/suraj520/unet-end-to-end-train-infer,SenNet + HOA - Hacking the Human Vasculature in 3D
16556,163179907,1074.0,,11,18,/rohitdileep/unet-tensorflow,SenNet + HOA - Hacking the Human Vasculature in 3D
16557,153891568,1.0,,6,21,/electricweasle/mohs-hardness-solution,Regression with a Mohs Hardness Dataset
16558,159073595,3.0,,0,6,/fabienpv/3rd-place-solution-simple-r-classifier,Regression with a Mohs Hardness Dataset
16559,152776282,9.0,0.25,2,21,/adaubas/pss3e25-an-other-25-notebook,Regression with a Mohs Hardness Dataset
16560,151975390,13.0,,6,17,/paddykb/pg-s3e25-evaluate-the-lgbm-prefit-technique,Regression with a Mohs Hardness Dataset
16561,152118649,18.0,,0,2,/xiaochuanyang/minmax-transform-and-histgbr-model,Regression with a Mohs Hardness Dataset
16562,152320750,27.0,,0,9,/elanderos/s03e23-eda-and-baseline,Regression with a Mohs Hardness Dataset
16563,152719773,29.0,,17,41,/lasm1984/my-beauty-notebook,Regression with a Mohs Hardness Dataset
16564,159636361,36.0,,30,98,/larjeck/regression-with-a-mohs-hardness-dataset-optimal,Regression with a Mohs Hardness Dataset
16565,152131733,43.0,0.3620597999999999,10,37,/eishkaran/lgbm-basic-notebook,Regression with a Mohs Hardness Dataset
16566,152786520,60.0,,0,10,/cheesegue/eda-mohs-hardness,Regression with a Mohs Hardness Dataset
16567,152696796,64.0,0.5006302886266818,0,12,/satyaprakashshukl/eda-hardness-dataprep,Regression with a Mohs Hardness Dataset
16568,150768666,67.0,0.5198271122902693,2,4,/syedsubahani/predict-the-mohs-hardness-of-a-mineral,Regression with a Mohs Hardness Dataset
16569,150655187,71.0,,0,6,/mexwell/ps3e25-mohs-hardness-regression-starter,Regression with a Mohs Hardness Dataset
16570,159051255,79.0,,3,14,/lucasrathgeb/mohs-hardness-prediction,Regression with a Mohs Hardness Dataset
16571,153712326,133.0,0.25,1,2,/markuslill/s3e25-mohs-hardness-xgbclassifier,Regression with a Mohs Hardness Dataset
16572,151777150,201.0,,0,2,/vai15r32/mohs-hardness-prediction,Regression with a Mohs Hardness Dataset
16573,152626438,98.0,0.5457532999999999,0,5,/racecar09/quick-and-dirty-mohs-hadness-via-nn-s3e25,Regression with a Mohs Hardness Dataset
16574,153681281,102.0,,0,2,/andy120198/regression-with-a-mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16575,151544019,103.0,0.428178570848134,0,5,/guanlintao/blending-s3e25-prediction,Regression with a Mohs Hardness Dataset
16576,152073933,127.0,0.5519699750438338,0,10,/yunsuxiaozi/pss3e25-baseline-optuna-lgbm,Regression with a Mohs Hardness Dataset
16577,152732736,118.0,0.4516365999999996,27,67,/enricomanosperti/regression-with-a-mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16578,153885473,119.0,,1,4,/fanhuaiyuan/my-tabular-practice-notebook,Regression with a Mohs Hardness Dataset
16579,155411393,141.0,,13,61,/ddosad/mohs-hardness-eda-pycaret-automl,Regression with a Mohs Hardness Dataset
16580,153464641,154.0,,0,9,/yunusemregktrk/ps3e25-regression-with-nn,Regression with a Mohs Hardness Dataset
16581,150946421,156.0,0.6252684489871743,0,2,/ianchute/baseline-knn-model,Regression with a Mohs Hardness Dataset
16582,155413474,160.0,,5,30,/brpuneet898/notebook-s3-e25-for-beginners,Regression with a Mohs Hardness Dataset
16583,153554184,170.0,,0,6,/jominjae/mohs-hardness-regression,Regression with a Mohs Hardness Dataset
16584,153621631,183.0,0.25,0,1,/sonhoangvu/ps3e25-mohs-hardness-prediction-xgb,Regression with a Mohs Hardness Dataset
16585,150819864,190.0,,1,6,/bertanpank/ps3e25-pycaret-adversial-validation,Regression with a Mohs Hardness Dataset
16586,153176784,357.0,0.4431424000000001,8,38,/francescoliveras/ps-s3-e25-eda-model-en-es,Regression with a Mohs Hardness Dataset
16587,151648673,379.0,0.4312813999999996,10,34,/xpehutta/xgboost-optuna-outliers-omitted,Regression with a Mohs Hardness Dataset
16588,152886125,244.0,0.75,0,10,/tonyyunyang99/regression-with-a-mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16589,150890333,398.0,,0,8,/kitoryyeah/basicneuralnet-baseline-mohs-hardness-prediction,Regression with a Mohs Hardness Dataset
16590,152521958,257.0,0.3797949999999996,0,1,/fatmanurcetnturk/regression-with-a-mohs-hardness,Regression with a Mohs Hardness Dataset
16591,161828073,205.0,,0,3,/hallojong0319/ensemble-algorithm-super-learner-ctgan,Regression with a Mohs Hardness Dataset
16592,151785015,458.0,,0,4,/serhiikharchuk/my-version,Regression with a Mohs Hardness Dataset
16593,151695817,685.0,,3,12,/bedynoag/eda-for-beginners,Regression with a Mohs Hardness Dataset
16594,155137055,279.0,,4,35,/yutodennou/competition-lightgbm-and-nn,Regression with a Mohs Hardness Dataset
16595,152149331,414.0,,2,12,/keishibata/ps3-s3e25-eda-xgb,Regression with a Mohs Hardness Dataset
16596,153321258,301.0,0.3196613999999997,2,8,/yuvannabawa/lgbm-nn,Regression with a Mohs Hardness Dataset
16597,151658153,220.0,,0,3,/tonyyunyang/regression-with-a-mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16598,151989453,352.0,0.4181869999999996,6,16,/hridaym25/easy-optuna-lgbm,Regression with a Mohs Hardness Dataset
16599,153257093,217.0,0.3963736999999998,20,66,/imnandini/regression-with-mohs-hardnesss,Regression with a Mohs Hardness Dataset
16600,151154477,428.0,,0,6,/sovinasahni/mohs-hardness-baseline,Regression with a Mohs Hardness Dataset
16601,151317416,431.0,,22,71,/iqbalsyahakbar/ps3e25-mohs-hardness-regression-for-beginners,Regression with a Mohs Hardness Dataset
16602,151016045,216.0,,0,5,/anzarwani2/superficial-solution,Regression with a Mohs Hardness Dataset
16603,151702442,448.0,258.02145,0,3,/minhtien1405/data-understanding-and-dummy-model-with-pytorch,Regression with a Mohs Hardness Dataset
16604,151860925,263.0,,0,5,/armanzhalgasbayev/ps-s3-e25-mohs-hardness-regression-tf,Regression with a Mohs Hardness Dataset
16605,150823086,388.0,,1,11,/dreygaen/ps3e25-mohs-hardness-ensembling-method,Regression with a Mohs Hardness Dataset
16606,152779200,229.0,0.5006302886266818,0,10,/chiragthakur099/hardness-mohs,Regression with a Mohs Hardness Dataset
16607,151867511,342.0,,0,2,/pacesetter55/regression-with-xgboost,Regression with a Mohs Hardness Dataset
16608,152981561,378.0,0.4317350000000002,0,3,/thehustler2003/s3ep25-pytorch-nn,Regression with a Mohs Hardness Dataset
16609,151241570,413.0,,0,2,/aaradhyabadal/cv-0-6228-eda-best-feature-model-lgbm-tuned,Regression with a Mohs Hardness Dataset
16610,152224014,386.0,0.6081673799921372,2,6,/michaeltezak/eda-stacking-model,Regression with a Mohs Hardness Dataset
16611,151512232,351.0,0.3816503999999998,2,12,/coinshot/mohs-hardness-model,Regression with a Mohs Hardness Dataset
16612,152233956,406.0,0.3843652999999998,6,12,/danishelahi/predicting-the-hardness-of-materials,Regression with a Mohs Hardness Dataset
16613,152505426,533.0,,6,10,/ukdemirtas/playgroundse3ep25-eda-lgbm-nn,Regression with a Mohs Hardness Dataset
16614,152539429,442.0,0.4762519999999997,0,6,/ainjhamn526/ps-3-25-predict-hardness,Regression with a Mohs Hardness Dataset
16615,150890503,430.0,0.4898233000000003,12,27,/alexryzhkov/ps3e25-lightautoml-baseline,Regression with a Mohs Hardness Dataset
16616,152772085,471.0,0.6436116152339313,3,5,/hamzanabil/pycaret,Regression with a Mohs Hardness Dataset
16617,152690592,548.0,0.4153219999999997,0,0,/wintersbae/playground-s3e25-mohs-hardness-prediction,Regression with a Mohs Hardness Dataset
16618,152076782,506.0,0.4644313528560388,2,11,/wordcards/pgs3-25-quantile-regression-lightgbm,Regression with a Mohs Hardness Dataset
16619,151218331,312.0,0.7585472653000007,0,2,/gullude/3-25-basic-gradient-boosting,Regression with a Mohs Hardness Dataset
16620,151581691,435.0,0.4128305999999995,10,26,/gregoryklevans/mohs-hardness-eda-transformation-xgboost-ann,Regression with a Mohs Hardness Dataset
16621,153556178,540.0,,2,4,/chestadhingra/prediction-datadriftanalysis-deepnn,Regression with a Mohs Hardness Dataset
16622,151408175,487.0,,0,4,/aravindpcoder/regression-with-a-mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16623,153480771,480.0,0.4451246000000002,14,32,/debamritapaul/mohs-hardness-regression-with-neural-network,Regression with a Mohs Hardness Dataset
16624,151065289,325.0,0.4147425,7,30,/akioonodera/ps3-25-reg-tf-keras,Regression with a Mohs Hardness Dataset
16625,151738242,303.0,,2,3,/hamsawahed98/mohs-hardness,Regression with a Mohs Hardness Dataset
16626,151880328,362.0,,2,24,/iqmansingh/mohs-hardness-starter-notebook,Regression with a Mohs Hardness Dataset
16627,153181325,358.0,0.4400380104646793,0,0,/neupane9sujal/regression-for-mohs-hardness,Regression with a Mohs Hardness Dataset
16628,152784393,469.0,0.4513348538239823,2,5,/taichiuemura/ps3e25-classification-regression,Regression with a Mohs Hardness Dataset
16629,151015383,474.0,,0,13,/alicanpayasli/hardness-first-try-0-66-median-absolute-error,Regression with a Mohs Hardness Dataset
16630,151676335,483.0,,0,6,/xxxzayh/overfitting,Regression with a Mohs Hardness Dataset
16631,152306146,501.0,,0,9,/memocan/predicting-mineral-hardness-with-cool-ml-tricks,Regression with a Mohs Hardness Dataset
16632,151993610,496.0,,4,14,/devanshibavaria/mohs-hardness-nn-lgbm-cat-xgb,Regression with a Mohs Hardness Dataset
16633,153115163,536.0,0.6508672705476712,0,4,/meesh11/s3e25-example-approach,Regression with a Mohs Hardness Dataset
16634,150608079,493.0,,0,7,/gauravduttakiit/pss3e25-lazypredict,Regression with a Mohs Hardness Dataset
16635,152782055,747.0,0.4661119999999998,0,5,/fazilamirli/playground-series-notebook-s3e25,Regression with a Mohs Hardness Dataset
16636,153572971,794.0,,0,2,/kazumatokuda/cross-validated-keras-regression-for-mohs-hardne,Regression with a Mohs Hardness Dataset
16637,152399518,475.0,0.5013999999999994,2,5,/kjihwan/easy-code-with-pycaret,Regression with a Mohs Hardness Dataset
16638,152958066,778.0,0.5174404770841203,2,2,/oyebamijimicheal/mohs-hardness-eda-fe-optuna,Regression with a Mohs Hardness Dataset
16639,152100137,537.0,0.6587160000000001,0,16,/anopsy/eda-baseline-mohs-hardness,Regression with a Mohs Hardness Dataset
16640,152100137,537.0,0.6587160000000001,0,16,/anopsy/eda-baseline-mohs-hardness,Regression with a Mohs Hardness Dataset
16641,153441911,664.0,0.4822553370276776,23,49,/dumanmesut/mohs-hardness-prediction-cat-lgbm-xgb,Regression with a Mohs Hardness Dataset
16642,150786051,578.0,0.4836757536719913,0,6,/astitwaagarwal/playground-series-s3e25,Regression with a Mohs Hardness Dataset
16643,151743974,551.0,0.6449025120983221,0,4,/vishwasmishra1234/notebook0c0296f258,Regression with a Mohs Hardness Dataset
16644,151384059,718.0,0.6349999999999998,0,2,/eddieamimo/catboost-pipeline,Regression with a Mohs Hardness Dataset
16645,157351816,568.0,,1,9,/sid4ds/ps-s3e25-simple-baseline-cv-setup,Regression with a Mohs Hardness Dataset
16646,153027770,678.0,0.4980886824088575,4,7,/joseelisei/regression-mohs-hardness-bayesian-optimization,Regression with a Mohs Hardness Dataset
16647,153195784,650.0,0.4946156000000004,1,2,/kroha5/simple-nn-pytorch-version,Regression with a Mohs Hardness Dataset
16648,151120153,667.0,,0,6,/mukul74/lb-0-65-s3e25-baseline-xgb-regression,Regression with a Mohs Hardness Dataset
16649,151590461,584.0,0.4999867193005558,0,9,/keitashimizu21/explanatory-data-of-prediction-of-mohs-hardness,Regression with a Mohs Hardness Dataset
16650,151273780,646.0,0.5064668007387101,0,14,/syerramilli/ps3e25-lightgbm-optuna,Regression with a Mohs Hardness Dataset
16651,153571730,666.0,0.5193382282905787,2,16,/yldzburhan/s3e25-predicting-mohs-hardness-lgbm-xgb,Regression with a Mohs Hardness Dataset
16652,159086596,698.0,,0,8,/dima806/s3e25-hardness-external-data-autoviz-catboost-shap,Regression with a Mohs Hardness Dataset
16653,152100844,531.0,,0,3,/setyoab/ps3e25-mohs-hardness-lgbm,Regression with a Mohs Hardness Dataset
16654,153484696,656.0,0.5104476869010828,0,0,/natchaphonkamhaeng/pg-regression-with-a-mohs-hardness,Regression with a Mohs Hardness Dataset
16655,152289968,594.0,0.5185029999999999,0,17,/huseyinbaytar/s3e25-regression-with-mohs,Regression with a Mohs Hardness Dataset
16656,152145475,587.0,,0,8,/yashasvimisra/lgbm-regression-mohs-hardness-s3-e25,Regression with a Mohs Hardness Dataset
16657,151061010,595.0,0.5,0,6,/pramodiasuka/hardeness-prediction-lgbm,Regression with a Mohs Hardness Dataset
16658,150618028,1125.0,0.6470000000000002,0,5,/thomasmeiner/ps3e25-eda-and-baseline,Regression with a Mohs Hardness Dataset
16659,151030772,598.0,,2,8,/mbalos/mohs-hardness-exploratory-data-analysis,Regression with a Mohs Hardness Dataset
16660,151398529,600.0,0.5,0,3,/mohamedayoubchettouh/classification-problem,Regression with a Mohs Hardness Dataset
16661,151817333,647.0,0.5,8,11,/vishsin01/histgradientboost-regressor-optuna-beginner,Regression with a Mohs Hardness Dataset
16662,152001017,610.0,0.5427105999999999,0,3,/alex97andreev/ps-s3e25-faster-regression-tuning-with-sklearnex,Regression with a Mohs Hardness Dataset
16663,152210957,612.0,0.9202992515679558,2,8,/giabchnguyn/mohs-hardness,Regression with a Mohs Hardness Dataset
16664,166422629,623.0,0.5,0,4,/himanshuydv11/playground-s3e25-mohs-hardness,Regression with a Mohs Hardness Dataset
16665,152381814,759.0,0.6249019445686255,0,9,/amgedelshiekh/pg-s3e25-mohs-hardness-eda-ml-dl-blender,Regression with a Mohs Hardness Dataset
16666,152381814,759.0,0.5002060000000004,0,9,/amgedelshiekh/pg-s3e25-mohs-hardness-eda-ml-dl-blender,Regression with a Mohs Hardness Dataset
16667,151233643,660.0,0.500400687338808,0,10,/docxian/ps-s3-e25-a-hard-regression-problem,Regression with a Mohs Hardness Dataset
16668,151567032,639.0,0.5014071000000002,0,7,/sunny7712/s3-e25-eda-baseline,Regression with a Mohs Hardness Dataset
16669,153612647,669.0,0.5024483815171847,0,1,/lnzbati/mohs-hardness-predictions-with-machine-learning,Regression with a Mohs Hardness Dataset
16670,150842492,696.0,0.5036131479613077,2,8,/ryanml2/playground-series-3-hard-rocks,Regression with a Mohs Hardness Dataset
16671,153460860,662.0,,0,6,/kesavan21u/regression-lightgbm-beginners,Regression with a Mohs Hardness Dataset
16672,151970652,768.0,0.506943595624854,0,11,/umarzafar/mohs-hardness-prediction-hgbr-ada-rf-cat,Regression with a Mohs Hardness Dataset
16673,153414559,787.0,0.5268517120254037,7,13,/msarvesh/mohs-hardness-using-gradientboosting,Regression with a Mohs Hardness Dataset
16674,151003369,767.0,,0,1,/liviam/mohs-hardness-regression-competition,Regression with a Mohs Hardness Dataset
16675,151999503,731.0,0.5118256737691063,5,14,/saipraveenreddyallam/basic-model-gbdt-rf-xgb-lgbm,Regression with a Mohs Hardness Dataset
16676,153296102,728.0,0.5145915076351679,0,5,/imtommi/mohs-hardness-reg,Regression with a Mohs Hardness Dataset
16677,159444160,764.0,,0,3,/arpitppatel/regression-template-ps3e25,Regression with a Mohs Hardness Dataset
16678,153613529,868.0,,3,5,/abhirupghosh184098/mohs-hardness-fnn-predictor,Regression with a Mohs Hardness Dataset
16679,152149816,844.0,0.895999999999999,0,2,/darshan77879/pg-s3-e25-nn-eda,Regression with a Mohs Hardness Dataset
16680,150630664,851.0,,4,9,/ucas0v0zhuoqunli/eda-quick-automl-baseline,Regression with a Mohs Hardness Dataset
16681,151706637,942.0,,0,6,/zonwie/s13e25-1-eda-feature-importace-neural-network,Regression with a Mohs Hardness Dataset
16682,151389926,754.0,,4,4,/luistalavera/ps-s3-e25-mohs-hardness-eda,Regression with a Mohs Hardness Dataset
16683,150685408,836.0,0.5977286420603685,0,3,/stpeteishii/pgs-s3e25-lgbm1,Regression with a Mohs Hardness Dataset
16684,152109389,864.0,,0,7,/bill2bill/s03e25-eda,Regression with a Mohs Hardness Dataset
16685,151773701,934.0,0.5542990086198367,0,13,/tuhinm2002/mohs-hardness-eda,Regression with a Mohs Hardness Dataset
16686,156381822,904.0,,0,1,/xfolia/hardness-predict,Regression with a Mohs Hardness Dataset
16687,153464281,843.0,0.8588134886813208,0,0,/snehakurmi/feature-eng-model-designing,Regression with a Mohs Hardness Dataset
16688,164475200,910.0,,2,12,/yeonseokcho/predict-mohs-hardness,Regression with a Mohs Hardness Dataset
16689,151887957,875.0,0.5839118627804663,0,3,,Regression with a Mohs Hardness Dataset
16690,151352565,1020.0,0.5871677740863923,0,1,/alonewolf/mohs-hardness,Regression with a Mohs Hardness Dataset
16691,152393801,874.0,0.6347455291258646,3,14,/sujaykapadnis/ps-s3e21-feature-distribution,Regression with a Mohs Hardness Dataset
16692,152393801,874.0,0.5880390435594531,3,14,/sujaykapadnis/ps-s3e21-feature-distribution,Regression with a Mohs Hardness Dataset
16693,153226036,877.0,0.7119615780240611,0,4,/barbagrande007/bbg007-s3e25-mohshardness,Regression with a Mohs Hardness Dataset
16694,162291807,911.0,0.6628146109250705,22,77,/kapturovalexander/kapturov-s-solution-of-ps-s3e25,Regression with a Mohs Hardness Dataset
16695,153264198,969.0,0.5965921629623168,11,24,/hikmatullahmohammadi/mohs-hardness-prediction-eda,Regression with a Mohs Hardness Dataset
16696,151384057,923.0,0.6546450000000001,1,5,/uzairshafique/mohs-hardness-xgboost-regressor,Regression with a Mohs Hardness Dataset
16697,152456204,1146.0,,3,8,/pluspin/pgs-s3-e25-with-pipeline,Regression with a Mohs Hardness Dataset
16698,152416121,902.0,0.6265985013690298,1,3,/nicobarea/s3e25-cat-lgbm-rf-w-medae,Regression with a Mohs Hardness Dataset
16699,151948700,895.0,,0,1,/patrakeevvalentin/my-first-laptop-mohs-hardness,Regression with a Mohs Hardness Dataset
16700,151843752,940.0,,0,0,/mariusmartinaitis/regression-with-a-mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16701,153238847,1028.0,0.6112849999999996,0,5,/prathamghoshroy/regressionwithmohshardness-xgbregressor,Regression with a Mohs Hardness Dataset
16702,152146920,1084.0,0.6114272151599955,0,3,/iftekharalammitu/mohs-hardness-multiple-modeling-prediction,Regression with a Mohs Hardness Dataset
16703,152150281,965.0,0.6374541595398515,0,6,/sunilkumaradapa/better-accuracy-using-stacking,Regression with a Mohs Hardness Dataset
16704,152486700,1176.0,0.6362173354239209,2,16,/vanphung/mohs-hardness-regression,Regression with a Mohs Hardness Dataset
16705,151781122,1080.0,,0,3,/theusman/building-the-moh-regression-wonderland,Regression with a Mohs Hardness Dataset
16706,167048104,951.0,,4,10,/alexeyk12/experiment-with-generating-features,Regression with a Mohs Hardness Dataset
16707,151807227,967.0,,0,2,/vladys/notebookc4f8261cce,Regression with a Mohs Hardness Dataset
16708,151800992,1083.0,0.6205604752020566,0,4,/antoinebourgois2/notebook7bb2c112f5,Regression with a Mohs Hardness Dataset
16709,150788702,927.0,0.6215309398470548,0,9,/patriciabrezeanu/s3e25-lightgbm-optuna,Regression with a Mohs Hardness Dataset
16710,156896210,894.0,,0,0,/beastar3104/regression-with-a-mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16711,152935153,943.0,0.6230636,0,0,/herczeggyrgy/xgboost-mohs-hardness,Regression with a Mohs Hardness Dataset
16712,151174075,958.0,0.6331689999999996,0,2,/surajyadav91/xgboost-v1,Regression with a Mohs Hardness Dataset
16713,150954719,921.0,,0,5,/datanalystbiju/eda-model-drift-pca,Regression with a Mohs Hardness Dataset
16714,152902148,1099.0,,2,8,/abhijitdarekar001/featrureeng-xgboost-hyperparamoptimization,Regression with a Mohs Hardness Dataset
16715,150755391,1221.0,1.3529999999999998,2,23,/jocelyndumlao/autoreg-modeling-prediction-of-mohs-hardness,Regression with a Mohs Hardness Dataset
16716,154802499,929.0,,0,1,/avneets2103/hardness-predictor,Regression with a Mohs Hardness Dataset
16717,151119566,1036.0,0.6418707781093014,2,11,/tatianakushniruk/mohs-hardness-eda-stacked-regressions,Regression with a Mohs Hardness Dataset
16718,150733085,1102.0,,0,2,/mainscientist/ps3e25,Regression with a Mohs Hardness Dataset
16719,151982450,1185.0,,2,12,/magantiit/mohs-hardness-predictions,Regression with a Mohs Hardness Dataset
16720,152438409,1109.0,,0,1,/kundanrao/competition-regression-mohs-hardness,Regression with a Mohs Hardness Dataset
16721,153415457,1273.0,0.6362173354239209,0,0,/roronoazorox/notebook-s3-e25-for-beginners,Regression with a Mohs Hardness Dataset
16722,155092054,1262.0,,0,6,/prashikmeshram37/mohs-hardness-of-minerals,Regression with a Mohs Hardness Dataset
16723,151416221,1052.0,,0,1,/aaronalbrecht/hardness-contest,Regression with a Mohs Hardness Dataset
16724,153636233,1198.0,0.6410343459721597,0,3,/wpradovich/mohs-hardness-competition,Regression with a Mohs Hardness Dataset
16725,150758887,1075.0,0.6416909085307765,0,3,/mokshbaweja/baseline-beginner,Regression with a Mohs Hardness Dataset
16726,150981805,1050.0,,1,12,/hasibullahaman/mohs-hardness-lgbm-catboost-xgb,Regression with a Mohs Hardness Dataset
16727,150790838,1225.0,1.1743040000000002,3,12,/rukenmissonnier/for-beginners-feature-engineering-prediction,Regression with a Mohs Hardness Dataset
16728,153882105,996.0,,0,1,/dhineshbabbu/adb-mohs-hardness-prediction,Regression with a Mohs Hardness Dataset
16729,151396452,1248.0,0.6519999999999997,0,2,/juozaskadusauskas/eda-xgb-boost,Regression with a Mohs Hardness Dataset
16730,152995414,1278.0,0.6691736639610735,4,16,/suraj520/ps-s3-e25-median-stacking-with-lda-voting,Regression with a Mohs Hardness Dataset
16731,152995414,1278.0,0.6691736639610735,4,16,/suraj520/ps-s3-e25-median-stacking-with-lda-voting,Regression with a Mohs Hardness Dataset
16732,152060360,1213.0,0.8394126999999996,0,0,/joaquinmorillas/dnn-regression,Regression with a Mohs Hardness Dataset
16733,153428412,1332.0,,0,0,/swufeleo/hardness-tabnet,Regression with a Mohs Hardness Dataset
16734,152355439,1343.0,0.7079999999999993,6,16,/saurabhru/mohs-hardness-dataset,Regression with a Mohs Hardness Dataset
16735,153630525,1321.0,,3,15,/omega11/mohs-hardness,Regression with a Mohs Hardness Dataset
16736,150999654,1130.0,1.1782890000000004,0,4,/nicapotato/mohs-hardness-dataset-clustering,Regression with a Mohs Hardness Dataset
16737,154590035,1352.0,,0,0,/kabak09/mohs-hardness,Regression with a Mohs Hardness Dataset
16738,152699744,1375.0,0.7370000000000028,0,2,/yasiir/regression-on-mohs-hardness-data,Regression with a Mohs Hardness Dataset
16739,152775497,1395.0,,0,60,/abdoashraf90/mohs-hardness-prediction,Regression with a Mohs Hardness Dataset
16740,150630850,1404.0,0.7400380000000002,1,7,/pohzixiang/pse325-pca-xgboost-with-tuning,Regression with a Mohs Hardness Dataset
16741,157356808,1402.0,,0,0,/marianoweimer/predictive-analysis-of-mohs-hardness-in-minerals,Regression with a Mohs Hardness Dataset
16742,153291872,1421.0,0.7515431957457208,0,3,/jclohjc/mohs-hardness-prediction-using-regression-model,Regression with a Mohs Hardness Dataset
16743,153726254,1435.0,0.7741929394482718,0,4,/abhinandansamal/mohshardness-randomforestregressor,Regression with a Mohs Hardness Dataset
16744,152789144,1423.0,,2,7,/tarundirector/hardness-prediction-eda-optuna-lgmb,Regression with a Mohs Hardness Dataset
16745,150624342,1440.0,,1,9,/utkarshx27/mohs-hardness-dataset-analysis-model,Regression with a Mohs Hardness Dataset
16746,151373020,1460.0,0.8619193999999997,0,1,/tracyporter/play-3-25-jax-regression,Regression with a Mohs Hardness Dataset
16747,152194828,1461.0,0.888577226906027,1,8,/abaliyan/mohs-hardness-s3e25-version-1,Regression with a Mohs Hardness Dataset
16748,152689617,1471.0,0.8910301875061553,0,4,/spiritedcoder/mohs-hardness-dataset-regression,Regression with a Mohs Hardness Dataset
16749,152970613,1512.0,,0,0,/ttbrosltd/mohshardness-dataset,Regression with a Mohs Hardness Dataset
16750,153566513,1490.0,,0,0,/vinitkp/regression-mohs-hardness,Regression with a Mohs Hardness Dataset
16751,153630380,1491.0,,0,0,/anjanakittu/mohs-hardness-prediction-of-minerals,Regression with a Mohs Hardness Dataset
16752,151448312,1518.0,0.9879833962149592,0,3,/kohlijorawar/hardness-prediction,Regression with a Mohs Hardness Dataset
16753,151448312,1518.0,0.9879833962149592,0,3,/kohlijorawar/hardness-prediction,Regression with a Mohs Hardness Dataset
16754,151855420,1532.0,1.0071869988327649,0,1,/owenhochwald/regression-with-mohs-hardness-dataset-using-lr,Regression with a Mohs Hardness Dataset
16755,153231433,1575.0,,0,1,/nithishar/notebookb2ff82296f,Regression with a Mohs Hardness Dataset
16756,153547905,1600.0,,0,3,/vstacknocopyright/mohs-hardness-prediction-using-random-forest-regn,Regression with a Mohs Hardness Dataset
16757,153593954,1604.0,1.7254471920940562,0,6,/rahulcris07/mohs-hardness-pred-eda-all-reg-models-rsqr-0-39,Regression with a Mohs Hardness Dataset
16758,150978998,1606.0,,1,4,/raaggeesingh/mohs-hardness-playground-series-se3ep25,Regression with a Mohs Hardness Dataset
16759,159363209,1613.0,0.6505596000000002,3,17,/vishnupriyagarige/mohs-hardness-regression,Regression with a Mohs Hardness Dataset
16760,159363209,1613.0,0.5094411667014489,3,17,/vishnupriyagarige/mohs-hardness-regression,Regression with a Mohs Hardness Dataset
16761,159363209,1613.0,0.6461185832206624,3,17,/vishnupriyagarige/mohs-hardness-regression,Regression with a Mohs Hardness Dataset
16762,153634312,1628.0,4.926437546701522,0,5,/aniketarpathak/mohs-hardness-data-analysis-and-prediction,Regression with a Mohs Hardness Dataset
16763,162946483,4.0,,2,5,/kirderf/s3e26-autogluon-pseudolabel-distill-stacking,Multi-Class Prediction of Cirrhosis Outcomes
16764,154026833,55.0,0.4149561258876198,5,19,/juniorbertrand/for-beginners-by-a-beginner,Multi-Class Prediction of Cirrhosis Outcomes
16765,154242379,140.0,0.4285016469953077,1,13,/ianchute/cirrhosis-baseline-lgbm,Multi-Class Prediction of Cirrhosis Outcomes
16766,157687587,149.0,,37,84,/satyaprakashshukl/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16767,154419432,181.0,0.4099227634444335,0,21,/mehrankazeminia/1-s3e26-eda-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16768,153891361,23.0,0.398476602853937,5,31,/thehustler2003/s03e26-lgbm-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16769,156563216,193.0,0.3924630145783779,26,119,/ashishkumarak/ps3e26-liver-cirrhosis-eda-model,Multi-Class Prediction of Cirrhosis Outcomes
16770,157301411,57.0,0.3982817017331551,7,33,/iveeaten3223times/booststack-mlp-fusion-beginner,Multi-Class Prediction of Cirrhosis Outcomes
16771,155022155,203.0,,5,50,/ddosad/ps3e26-visual-eda-automl-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16772,154205486,81.0,0.3958571529016983,14,61,/mattop/ps-s3-e26-lgbm-xgb-preprocessing-fasteda,Multi-Class Prediction of Cirrhosis Outcomes
16773,155346872,99.0,,0,4,/minemine12345678/xgbcla-shap-20231217,Multi-Class Prediction of Cirrhosis Outcomes
16774,156758443,87.0,,0,3,/aymenbouyahia/xgboost-for-this-dataset,Multi-Class Prediction of Cirrhosis Outcomes
16775,154023328,220.0,0.5329305634405231,0,11,/docxian/ps-s3-e26-cirrhosis-multiclass-glm,Multi-Class Prediction of Cirrhosis Outcomes
16776,155670800,229.0,0.3984391958693958,0,11,/andrusha95/gb-lgbm-xgb-voteclassifier,Multi-Class Prediction of Cirrhosis Outcomes
16777,166543522,22.0,,3,15,/byteliberator/cirrhosis-eda-umap-tsne-pacmap-clustering,Multi-Class Prediction of Cirrhosis Outcomes
16778,154173460,88.0,0.4046114486034545,6,21,/ankitgaikar1995/boosting-ensemble-beginner,Multi-Class Prediction of Cirrhosis Outcomes
16779,154286229,148.0,0.4013094327794165,4,7,/arlle26/s3e26-gb-lgbm-xgb-optuna-vote,Multi-Class Prediction of Cirrhosis Outcomes
16780,157004829,263.0,0.4106333411039975,0,15,/lonnieqin/s3e26-with-flaml,Multi-Class Prediction of Cirrhosis Outcomes
16781,153740214,228.0,0.4124586160223402,0,21,/eishkaran/shortest-code,Multi-Class Prediction of Cirrhosis Outcomes
16782,156188583,227.0,,4,9,/squarehare/tuning-lgbm-with-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16783,154466929,128.0,,0,22,/brpuneet898/ps-3-ep-26-for-beginners,Multi-Class Prediction of Cirrhosis Outcomes
16784,154109381,131.0,,1,13,/cheesegue/eda-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16785,156192550,372.0,0.3977197526041178,0,1,/swufeleo/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16786,157353519,273.0,,3,14,/kershrita/catboost-optuna-in-cirrhosis-data,Multi-Class Prediction of Cirrhosis Outcomes
16787,157271580,364.0,0.3942237474860757,0,11,/itasps/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16788,155176046,197.0,0.3951005167378885,5,20,/max1mum/s03e26-blend,Multi-Class Prediction of Cirrhosis Outcomes
16789,154234702,77.0,,0,14,/shivamkc3/advance-blending-weights-0-39522,Multi-Class Prediction of Cirrhosis Outcomes
16790,154788209,399.0,0.4759883474565426,0,12,/samyakb/getting-above-benchmark-using-random-forest,Multi-Class Prediction of Cirrhosis Outcomes
16791,154180641,7.0,,15,32,/danielpopov/ps3e26-eda-xgb-lgbm-cat-submission,Multi-Class Prediction of Cirrhosis Outcomes
16792,156855794,50.0,,0,8,/sunny7712/s3e26-baseline-eda-log-reg-xgboost,Multi-Class Prediction of Cirrhosis Outcomes
16793,154924671,413.0,0.4919134723849756,2,16,/anthonytherrien/simple-neural-network-benchmark,Multi-Class Prediction of Cirrhosis Outcomes
16794,154924671,413.0,0.4919134723849756,2,16,/anthonytherrien/simple-neural-network-benchmark,Multi-Class Prediction of Cirrhosis Outcomes
16795,155514996,72.0,,0,2,/ronfswanson/cirrhosisversion8-lb-0-4128,Multi-Class Prediction of Cirrhosis Outcomes
16796,155384659,335.0,0.4046348091992292,0,8,/kjihwan/ps3e26-eda-ensemble-tabnet,Multi-Class Prediction of Cirrhosis Outcomes
16797,155512412,116.0,,2,16,/devsubhash/multi-class-prediction-eda-s3e26,Multi-Class Prediction of Cirrhosis Outcomes
16798,157354157,349.0,0.4652583505979204,1,5,/priyamsaha17/prediction-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16799,156099804,354.0,0.4086776886215138,0,3,/alenic/xgboost-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16800,154803170,356.0,,3,13,/tcashion/ps3e26-adversarial-learning,Multi-Class Prediction of Cirrhosis Outcomes
16801,156735106,355.0,0.3962597992239746,14,42,/mostafamohammednouh/ps3e26-multi-class-prediction-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16802,156659910,321.0,,2,14,/hridaym25/short-baseline-xgb-lgbm-with-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16803,157358079,19.0,,10,30,/jonathankao/dec-2023-tabular-ensemble-xgboost-lgbm-v3-3,Multi-Class Prediction of Cirrhosis Outcomes
16804,155060749,734.0,0.420275528125823,6,22,/lasm1984/multiclass-everywhere,Multi-Class Prediction of Cirrhosis Outcomes
16805,153764815,40.0,0.4118401879634257,1,10,/uzairshafique/cirrhosis-xgboost-lightgbm-catboost-votingclasifir,Multi-Class Prediction of Cirrhosis Outcomes
16806,157313440,39.0,0.3980613047141791,16,29,/luficergfree/it-s-me-luficer-g,Multi-Class Prediction of Cirrhosis Outcomes
16807,156856252,189.0,0.3967382158227083,0,7,/julyju/classifier-inpired-by-others-lgbm-mainly,Multi-Class Prediction of Cirrhosis Outcomes
16808,156856252,189.0,0.3967382158227083,0,7,/julyju/classifier-inpired-by-others-lgbm-mainly,Multi-Class Prediction of Cirrhosis Outcomes
16809,156822378,314.0,0.4040371021326912,2,16,/aaryansingh729/easy-to-understand-beginner-xgb-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16810,158101830,38.0,,0,3,/abhinavkrjha/xgboost-lgbm-optuna-ranked-38th-on-leaderboard,Multi-Class Prediction of Cirrhosis Outcomes
16811,155184413,272.0,,0,5,/llorenzok/uphill-to-heaven,Multi-Class Prediction of Cirrhosis Outcomes
16812,156810804,162.0,0.4042943383258355,4,17,/neupane9sujal/prediction-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16813,154015515,82.0,,0,1,/westedcrean/s3e26-eda-initial-submission-multi-class-pr,Multi-Class Prediction of Cirrhosis Outcomes
16814,156598742,187.0,0.3988111048040639,0,6,/kanishk026/simple-ensemble,Multi-Class Prediction of Cirrhosis Outcomes
16815,157029697,426.0,,4,20,/djanyigit/ps3e26-prediction-of-cirrhosis-deep-learning,Multi-Class Prediction of Cirrhosis Outcomes
16816,156819575,30.0,0.3981603578808774,8,37,/cityuming/prediction-of-cirrhosis-outcomes-beginner-level,Multi-Class Prediction of Cirrhosis Outcomes
16817,156819575,30.0,0.3981603578808774,8,37,/cityuming/prediction-of-cirrhosis-outcomes-beginner-level,Multi-Class Prediction of Cirrhosis Outcomes
16818,156819575,30.0,0.3981603578808774,8,37,/cityuming/prediction-of-cirrhosis-outcomes-beginner-level,Multi-Class Prediction of Cirrhosis Outcomes
16819,157198296,31.0,0.4037084832265407,0,8,/vassyesboy/classification-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16820,154647736,318.0,,0,3,/talnikarvishwam/easy-multi-class-prediction-with-voting-classifier,Multi-Class Prediction of Cirrhosis Outcomes
16821,154735071,362.0,,0,9,/seifeddine0/cirrhosis-patient-survival-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16822,155791709,236.0,0.5510574979660646,1,8,/pshikk/easy-random-forest-approach,Multi-Class Prediction of Cirrhosis Outcomes
16823,157253210,113.0,0.4056982366417164,6,25,/mouadberqia/cirrhosis-outcomes-optuna-hyper-params,Multi-Class Prediction of Cirrhosis Outcomes
16824,154054325,400.0,0.4017468065026603,2,10,/oran11/cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16825,153660850,520.0,,5,17,/thomasmeiner/ps3e26-easy-and-rich-eda-to-get-you-started,Multi-Class Prediction of Cirrhosis Outcomes
16826,157355429,393.0,0.4123019389430116,3,12,/barbagrande007/bbg007-s3e6-cirrhoses,Multi-Class Prediction of Cirrhosis Outcomes
16827,154451790,430.0,,0,9,/dolphine11/ps3e26-simple-eda-and-modeling,Multi-Class Prediction of Cirrhosis Outcomes
16828,153827579,487.0,0.4003510133479607,0,11,/sigmoidss/pss3e26-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16829,156594725,378.0,,13,27,/m000sey/multi-class-w-boosts-eda-dim-reduction,Multi-Class Prediction of Cirrhosis Outcomes
16830,156250830,553.0,0.4118107900137647,0,3,/djmishra11/lightgbm-eda-hypertuning-repeatedskf,Multi-Class Prediction of Cirrhosis Outcomes
16831,156578631,481.0,,0,4,/pattaraponjindaboot/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16832,154968343,320.0,,0,1,/wonsukj/s3e26-simple-eda-lgb-modeling,Multi-Class Prediction of Cirrhosis Outcomes
16833,156823127,450.0,0.4032346548739373,0,1,/harshtailor/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16834,153657518,392.0,0.5283620163917941,1,13,/yunsuxiaozi/pss3e26-baseline-nn-for-beginners,Multi-Class Prediction of Cirrhosis Outcomes
16835,156720000,139.0,0.4048906149650812,0,6,/hmikraminfo/prediction-of-cirrhosis-using-multiclass,Multi-Class Prediction of Cirrhosis Outcomes
16836,159051236,579.0,,0,10,/lucasrathgeb/xgboost-cirrhosis-classification,Multi-Class Prediction of Cirrhosis Outcomes
16837,154449642,522.0,0.4053044612601201,2,13,/syerramilli/ps3e26-eda-lightgbm-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16838,153913528,451.0,0.4086608114909769,1,16,/yldzburhan/ps-s3e26-cirrhosis-prediction-lgbm-xgb-cat,Multi-Class Prediction of Cirrhosis Outcomes
16839,155140860,418.0,0.4072976573502008,4,24,/huseyinbaytar/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16840,155496804,1556.0,,0,1,/selvakumaranr/cirrhosis-predictor,Multi-Class Prediction of Cirrhosis Outcomes
16841,156913825,550.0,,2,15,/ryzhokhina/cirrohosis-classification,Multi-Class Prediction of Cirrhosis Outcomes
16842,153776946,278.0,0.4067610202516328,4,19,/dumanmesut/ps3e26-cirrhosis-outcomes-eda-lgbm-xgb-cat,Multi-Class Prediction of Cirrhosis Outcomes
16843,156378060,730.0,0.419776297153891,3,19,/sergeydeev/multi-class-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16844,154361241,452.0,0.408440768535521,0,8,/srushanthbaride2010/s3e26-score-0-40844,Multi-Class Prediction of Cirrhosis Outcomes
16845,155378034,459.0,0.4072958653794871,0,10,/gauravduttakiit/pss3e26-flaml-log-loss,Multi-Class Prediction of Cirrhosis Outcomes
16846,157184036,442.0,,8,20,/yeonseokcho/cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16847,156282858,439.0,0.4078042495300301,0,0,/fatmanurcetnturk/multi-class-prediction-with-optuna-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16848,156282858,439.0,0.4078042495300301,0,0,/fatmanurcetnturk/multi-class-prediction-with-optuna-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16849,155370241,716.0,,0,3,/atifsuhail/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16850,167047635,699.0,,8,16,/alexeyk12/eda-catboost,Multi-Class Prediction of Cirrhosis Outcomes
16851,153652820,637.0,0.4587755859707585,2,13,/taichiuemura/ps3e26-baseline-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16852,157259233,484.0,0.7429578776580982,0,21,/mvoulo/feature-engineering-cirrhosis-outcome-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16853,155368567,878.0,0.4361392491648047,0,1,/natchaphonkamhaeng/pg-multi-class-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16854,153726608,461.0,,0,8,/ksakaida/simply-eda-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16855,153839709,624.0,,0,1,/herczeggyrgy/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16856,153890438,467.0,,0,10,/abramova/ps3-e26-baseline,Multi-Class Prediction of Cirrhosis Outcomes
16857,156089710,565.0,0.4091501451744559,7,22,/hikmatullahmohammadi/multi-class-cirrhosis-eda-mi-score-feature-eng,Multi-Class Prediction of Cirrhosis Outcomes
16858,156005949,528.0,0.4093934334745961,2,4,/auliaqotrunnada/auliaa-qotrunnadaa,Multi-Class Prediction of Cirrhosis Outcomes
16859,155219050,652.0,,0,6,/habilamar/s3e26-kaggle-playground,Multi-Class Prediction of Cirrhosis Outcomes
16860,153672028,560.0,,0,11,/amihua/multi-class-baseline,Multi-Class Prediction of Cirrhosis Outcomes
16861,157374174,615.0,,0,4,/anzarwani2/s3e26-multiclass-prediction-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16862,154027937,562.0,,2,25,/anopsy/cirrhosis-dataset-quick-eda-randomsearch-cv-xgb,Multi-Class Prediction of Cirrhosis Outcomes
16863,154877083,551.0,0.4239725174728646,0,4,/digitsingh/feature-mastery-and-eda-with-lgbm,Multi-Class Prediction of Cirrhosis Outcomes
16864,154054194,691.0,,3,13,/randmax/ps3e26-cirrhosis-classification-for-beginners,Multi-Class Prediction of Cirrhosis Outcomes
16865,153831389,566.0,0.4105771127471022,0,3,/rizkykiky/s3e26-5-12-2023-lgbm-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16866,157122199,557.0,0.4123139050401523,0,5,/kahfinadhika/cirrhosis-xgb,Multi-Class Prediction of Cirrhosis Outcomes
16867,153953503,767.0,,0,7,/beijiayang/catboost-with-grid-search-for-multi-class-pred,Multi-Class Prediction of Cirrhosis Outcomes
16868,154426581,772.0,0.4458259039632083,0,6,/surajyadav91/playground-s3e26-xgboost-v1,Multi-Class Prediction of Cirrhosis Outcomes
16869,153753185,655.0,,4,18,/simonezappatini/cirrhosis-pycaret-baseline-for-beginners,Multi-Class Prediction of Cirrhosis Outcomes
16870,165552884,654.0,,3,7,/imtommi/baseline-xgb,Multi-Class Prediction of Cirrhosis Outcomes
16871,153771919,668.0,,0,12,/ukdemirtas/se3ep26-xgboost,Multi-Class Prediction of Cirrhosis Outcomes
16872,155856238,694.0,0.4113042307531132,0,4,/sharmaaryan123/liver-cirrhosis-predictions-eda-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16873,157148819,650.0,0.4129913469530172,0,12,/xietaowang/s3e26-catboost-baseline,Multi-Class Prediction of Cirrhosis Outcomes
16874,154785930,440.0,,7,46,/imnandini/multi-class-prediction-of-cirrhosis-beginner-level,Multi-Class Prediction of Cirrhosis Outcomes
16875,157289541,709.0,0.4154715890063959,0,16,/getanmolgupta01/cirrhosis-pred-xgboost-lbgm-catboost,Multi-Class Prediction of Cirrhosis Outcomes
16876,154117172,835.0,0.4120752289391535,1,9,/adwaitkesharwani/baseline-beginner,Multi-Class Prediction of Cirrhosis Outcomes
16877,154394182,630.0,0.4147651525618467,2,8,/suraj520/ps-s3-e26-lazy-predict-voting-ensemble,Multi-Class Prediction of Cirrhosis Outcomes
16878,160905256,614.0,0.4227453073212192,1,13,/toshimelonhead/tps-3-26-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16879,156503615,669.0,0.9229802808464004,2,10,/mariusborel/cirrhosis-what-comes-next,Multi-Class Prediction of Cirrhosis Outcomes
16880,154232252,738.0,0.4135820766687569,0,5,/susanketsarkar/cirrhosis-classification-ensemble-baseline,Multi-Class Prediction of Cirrhosis Outcomes
16881,156683202,683.0,,0,4,/sanjushusanth/eda-feature-engineering-model-building,Multi-Class Prediction of Cirrhosis Outcomes
16882,153712498,759.0,0.4137966025047649,0,14,/mexwell/cirrhosis-patient-survival-eda-and-ensemble,Multi-Class Prediction of Cirrhosis Outcomes
16883,157229745,490.0,0.4142603701874974,0,1,/hopesb/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16884,155298689,853.0,0.4146623487251928,0,1,/litsea/eda-cirrhosis-predict-for-beginners,Multi-Class Prediction of Cirrhosis Outcomes
16885,155080287,964.0,0.4389353642707703,0,9,/enricomanosperti/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16886,155822810,761.0,0.4149561258876198,1,3,/danadyaksa/m-rafy-danadyaksaa,Multi-Class Prediction of Cirrhosis Outcomes
16887,156518832,816.0,0.4531444586887458,1,9,/shrinivaspatil/multiclass-prediction-of-cirrohosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16888,156860249,589.0,,0,10,/conradkleykamp/s3e26-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16889,155776942,741.0,,0,8,/miroslavtyurin/ps3e26-eda-clinical-trials-been-inconsistent,Multi-Class Prediction of Cirrhosis Outcomes
16890,156634462,780.0,0.4414934916664944,0,5,/zman950/feature-engineering-with-pipelines,Multi-Class Prediction of Cirrhosis Outcomes
16891,154708279,705.0,0.4854563233109265,2,5,/alexandrelemercier/mutli-class-prediction-of-cirrhosis-outcome,Multi-Class Prediction of Cirrhosis Outcomes
16892,154907400,832.0,,0,4,/prathamghoshroy/cirrhosispred-eda-catboost-randomfor,Multi-Class Prediction of Cirrhosis Outcomes
16893,155763920,721.0,0.4187058597790327,8,14,/chiragthakur099/se3-ep26-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16894,153949488,736.0,,0,10,/vengadeshwaran58/cirrhosis-outcomes-multiclass-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16895,155827837,870.0,0.4188614797323624,0,4,/arnogils/playground-series-s03e26-daily-buildout,Multi-Class Prediction of Cirrhosis Outcomes
16896,160880867,712.0,,0,7,/fabienpv/informative-custom-logloss-function,Multi-Class Prediction of Cirrhosis Outcomes
16897,153874364,785.0,0.4192157875059007,0,7,/ucas0v0zhuoqunli/ps3e26-quick-automl-baseline,Multi-Class Prediction of Cirrhosis Outcomes
16898,153788078,968.0,,0,8,/keitashimizu21/eda-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16899,157960082,555.0,,3,1,/bradhammond/cirrhosis-liver-rfc-xgb-neural-net,Multi-Class Prediction of Cirrhosis Outcomes
16900,155044126,762.0,0.420150937053407,0,2,/dipayancodes/cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16901,155512885,820.0,,11,39,/iqbalsyahakbar/ps3e26-cirrhosis-classification-for-beginners,Multi-Class Prediction of Cirrhosis Outcomes
16902,155733398,824.0,0.4207085720586573,1,14,/royx1221/testing-data-chirosis,Multi-Class Prediction of Cirrhosis Outcomes
16903,153991098,859.0,,0,2,/vinodkumargurjar/multi-class-prediction-of-cirrhosis-outcomes-vinod,Multi-Class Prediction of Cirrhosis Outcomes
16904,156252438,777.0,0.531462657403751,0,8,/chloepomeroy/catboost,Multi-Class Prediction of Cirrhosis Outcomes
16905,156045642,924.0,0.4233378307722727,5,25,/mattduerr/s3e26-complete-eda-3-baseline-models,Multi-Class Prediction of Cirrhosis Outcomes
16906,155149917,923.0,,0,8,/hakim11/multiclass-classification,Multi-Class Prediction of Cirrhosis Outcomes
16907,155171287,854.0,0.4309477382444165,0,2,/amitvkulkarni/ps-s3-e26-lgbm-xbg-ensemble,Multi-Class Prediction of Cirrhosis Outcomes
16908,155979856,763.0,0.4224849052301925,4,9,/ridwanmahenra/cirrhosis-outcomes-with-xgboost,Multi-Class Prediction of Cirrhosis Outcomes
16909,156337803,675.0,0.4229967715053162,5,14,/paradoxplusparadise/multi-class-prediction-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16910,157039252,789.0,0.4232152110457067,4,19,/danyamyakota/ps3e26-eda-and-predictive-modelling,Multi-Class Prediction of Cirrhosis Outcomes
16911,156190038,975.0,0.4257367419850114,0,7,/ilya2raev/playground-series-s3e26-xgb-lgbm,Multi-Class Prediction of Cirrhosis Outcomes
16912,154949383,961.0,,0,4,/aaditambadkar/here-goes-nothing,Multi-Class Prediction of Cirrhosis Outcomes
16913,156966286,776.0,,0,2,/zhangmaomi/optuna-rs-xgboost-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16914,155963741,933.0,0.4892886071627834,0,10,/talhabarkaatahmad/multi-class-prediction-of-cirrhosis-nn,Multi-Class Prediction of Cirrhosis Outcomes
16915,153952694,987.0,,2,13,/sunilthite/cirrhosis-outcomes-eda-univariate-analysis,Multi-Class Prediction of Cirrhosis Outcomes
16916,154267907,806.0,,1,14,/utkarshx27/cirrhosis-outcome-prediction-exploration-model,Multi-Class Prediction of Cirrhosis Outcomes
16917,155022891,839.0,,0,1,/potongpasir/cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16918,154704790,865.0,0.4280599149816068,0,3,/nemanjagojkovic/lightgmb-optimized-using-bayessearch,Multi-Class Prediction of Cirrhosis Outcomes
16919,156100484,958.0,0.4569580019638389,0,4,/thomaswrightanderson/ps3e26-multiclass-cirrhosis-outcome-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16920,157247480,899.0,,11,23,/mohammadbizhani/s3e26-xgb-cat-mlp-models,Multi-Class Prediction of Cirrhosis Outcomes
16921,157286091,845.0,,4,7,/abhirupghosh184098/cirrhosis-predictor-eda-ensemble-nn,Multi-Class Prediction of Cirrhosis Outcomes
16922,156334996,984.0,0.429173959937222,0,1,/amishkakru/cirrhoses,Multi-Class Prediction of Cirrhosis Outcomes
16923,157140223,934.0,0.4300515341664981,1,5,/aniketmazumdar/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16924,156976775,1028.0,0.4322864964953134,0,2,/sandeepbora/notebook5031b8809c,Multi-Class Prediction of Cirrhosis Outcomes
16925,158114197,1073.0,,0,0,/speedwagon1299/cirrhosisxgboost,Multi-Class Prediction of Cirrhosis Outcomes
16926,155457692,962.0,0.4463468473749131,2,10,/umar47/cirrhosis-outcome-eda-modelling,Multi-Class Prediction of Cirrhosis Outcomes
16927,154739066,1011.0,,0,6,/thaonguyentrang/lightgbm-for-multi-classification,Multi-Class Prediction of Cirrhosis Outcomes
16928,156697174,1009.0,,2,12,/ishratunnisa/cirrhosis-eda,Multi-Class Prediction of Cirrhosis Outcomes
16929,156744543,991.0,,0,14,/muhannadmansour/treatment-survival-analysis-prediction-models,Multi-Class Prediction of Cirrhosis Outcomes
16930,154472219,1021.0,0.4408864991097104,0,11,/cv13j0/prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16931,157165684,1052.0,0.4413026425466007,0,11,/dhineshbabbu/adb-multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16932,156394015,952.0,,3,13,/legendsoul/label-based-plotly-eda,Multi-Class Prediction of Cirrhosis Outcomes
16933,157155882,1025.0,,0,0,/alexandreazouri/mcp-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16934,155456623,995.0,,0,1,/commentsm/cirrhosis-classification,Multi-Class Prediction of Cirrhosis Outcomes
16935,156007721,1032.0,0.4449258831759903,2,6,/rapunzell/andakaaoktoraprasetyoo,Multi-Class Prediction of Cirrhosis Outcomes
16936,155144598,1020.0,,0,1,/yeohhanyi/cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16937,154023525,1066.0,0.4565645082858108,0,12,/msarvesh/multi-class-classification,Multi-Class Prediction of Cirrhosis Outcomes
16938,154261425,1411.0,,0,12,/stpeteishii/ps-s3e26-lgbm-w-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16939,155190460,1145.0,,0,1,/adityasoedira/cirrhosis-patient-survival-pred,Multi-Class Prediction of Cirrhosis Outcomes
16940,155028926,1081.0,0.4485829852490751,0,2,/coinshot/multi-class-prediction-of-cirrhosi-model,Multi-Class Prediction of Cirrhosis Outcomes
16941,154075634,1086.0,0.5178202277457244,0,15,/debamritapaul/multi-class-prediction-of-cirrhosis-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16942,156849635,1148.0,,3,24,/maryamayman20/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16943,155529645,1141.0,0.5077581923386364,0,0,/recursive69/multiclass-classification-xgboost,Multi-Class Prediction of Cirrhosis Outcomes
16944,157127817,1127.0,0.4521748448005835,0,7,/lseongho/multiclass-cirrhosis-prediction-using-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16945,157127817,1127.0,0.4521748448005835,0,7,/lseongho/multiclass-cirrhosis-prediction-using-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
16946,166422490,1175.0,,6,10,/singhnavjot2062001/random-forest-cirrhosis-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16947,155103352,1100.0,,1,6,/yangbosung/eda-can-the-type-of-drug-help-to-predict-status,Multi-Class Prediction of Cirrhosis Outcomes
16948,153822478,1180.0,0.4583156265042246,0,9,/maxenceleguery/multi-class-predictor,Multi-Class Prediction of Cirrhosis Outcomes
16949,157666562,1001.0,,0,0,/jageshkar/multi-class-prediction-of-cirrhosis-outcomes-v2,Multi-Class Prediction of Cirrhosis Outcomes
16950,155066528,1223.0,,0,1,/quinngerber123/final,Multi-Class Prediction of Cirrhosis Outcomes
16951,156984746,1159.0,,4,25,/faresabbasai2022/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16952,155160732,1354.0,,1,14,/kirtanmatalia26/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16953,155307114,1134.0,0.465819251305236,4,11,/janmejaymohanty/cirrhosis-outcome-prediction-with-randomforest,Multi-Class Prediction of Cirrhosis Outcomes
16954,155383826,1135.0,0.465819251305236,0,1,/ilhmdwi/iiilham-dwitarama-prayitno,Multi-Class Prediction of Cirrhosis Outcomes
16955,157325008,1160.0,0.480950832253484,0,2,/maxagrafa/prediction-of-cirrhosis-with-nn,Multi-Class Prediction of Cirrhosis Outcomes
16956,154474416,1182.0,,0,56,/prthmgoyl/multiclass,Multi-Class Prediction of Cirrhosis Outcomes
16957,153866056,1161.0,,8,15,/vidhikishorwaghela/prediction-of-cirrhosis-multiclass-approach,Multi-Class Prediction of Cirrhosis Outcomes
16958,158263992,1198.0,0.4894345667337892,0,3,/yeemeitsang/cirrhosis-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16959,157338453,1183.0,0.4731969097288883,2,11,/josmyrose/multiclass-prediction1-2,Multi-Class Prediction of Cirrhosis Outcomes
16960,153666091,1204.0,,2,15,/kazumatokuda/baseline-eda-automl-comparemodel,Multi-Class Prediction of Cirrhosis Outcomes
16961,154158397,1189.0,,0,11,/prashikmeshram37/prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16962,157835433,1261.0,0.4278264345608289,0,20,/amulyat29/multi-class-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16963,153706957,1186.0,,3,13,/rahulcris07/cirrhosis-pred-acc81-4-auc-class-0-88-0-84-0-89,Multi-Class Prediction of Cirrhosis Outcomes
16964,154896529,1144.0,,0,8,/luistalavera/ps-s3-e26-ft-transformer,Multi-Class Prediction of Cirrhosis Outcomes
16965,155935447,1233.0,2.1340402024027934,4,8,/hakanrek/neural-network-with-keras-tuner,Multi-Class Prediction of Cirrhosis Outcomes
16966,155700521,1328.0,,0,8,/anannoasif/multiclass,Multi-Class Prediction of Cirrhosis Outcomes
16967,156125701,1219.0,,0,9,/chaozhuang/ps3e26-multi-class-lr-rf-xgb-svm-nn,Multi-Class Prediction of Cirrhosis Outcomes
16968,157287504,1246.0,,0,29,/endofnight17j03/final,Multi-Class Prediction of Cirrhosis Outcomes
16969,153808460,1302.0,0.4869621888389228,0,4,/nicolemichelle/ps-s326-multiclass-cirrhosis-predictor-92,Multi-Class Prediction of Cirrhosis Outcomes
16970,155036306,1207.0,0.4884127510065646,0,2,/abyssskb/cirrhosis-outcomes-nn,Multi-Class Prediction of Cirrhosis Outcomes
16971,156183558,1346.0,,0,7,/harharharhar/liver-competition,Multi-Class Prediction of Cirrhosis Outcomes
16972,156897138,1256.0,,0,0,/krishdidwania/notebookedf799c6b6,Multi-Class Prediction of Cirrhosis Outcomes
16973,156013031,1247.0,,0,3,/milinchakraborty/s3e26,Multi-Class Prediction of Cirrhosis Outcomes
16974,157332433,1324.0,,0,4,/vinithaek/multiclass-liver-cirrhosis-outcome,Multi-Class Prediction of Cirrhosis Outcomes
16975,157312718,1336.0,,0,5,/jayalakshmiet/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16976,154972052,1361.0,0.5229097292928409,0,0,/carljvh/fastai-for-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16977,155192216,1295.0,,0,7,/nhatthinhbui/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16978,153928164,1388.0,,6,20,/richeyjay/cirrhossis-multi-class,Multi-Class Prediction of Cirrhosis Outcomes
16979,154189454,1364.0,0.525266058542631,0,5,/prajwaldongre/eda-prediction-logreg-mean-acc-79,Multi-Class Prediction of Cirrhosis Outcomes
16980,153658666,1394.0,0.5287364254350608,0,7,/pohzixiang/ps3e26-classification-using-nn,Multi-Class Prediction of Cirrhosis Outcomes
16981,155919396,1440.0,0.5293465584413748,0,6,/ruchikarani/rt-multi-class-p-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16982,155919396,1440.0,0.5293465584413748,0,6,/ruchikarani/rt-multi-class-p-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16983,156665495,1449.0,0.5340683707980994,0,3,/thomasantony666/multi-class-prediction,Multi-Class Prediction of Cirrhosis Outcomes
16984,155407565,1415.0,0.5608610976560288,0,1,/atharvmj082k/cirrohsis-baseline,Multi-Class Prediction of Cirrhosis Outcomes
16985,156425147,1462.0,0.5408895126447661,0,4,/vanillasky312/lgbm-optuna,Multi-Class Prediction of Cirrhosis Outcomes
16986,155683616,1431.0,0.5471110188610383,1,3,/fazagestananda/faza-gestananda,Multi-Class Prediction of Cirrhosis Outcomes
16987,156527543,1422.0,,0,1,/aryansingh0909/tps-s3e26,Multi-Class Prediction of Cirrhosis Outcomes
16988,153961516,1469.0,,0,8,/vinitkp/multiclass-cirrhosisoutcomes,Multi-Class Prediction of Cirrhosis Outcomes
16989,157022666,1500.0,,1,12,/yuvrajsinghspd09/comp1a,Multi-Class Prediction of Cirrhosis Outcomes
16990,157351804,1459.0,,4,10,/anmolarora15/cirrhosis-s3e26-xgb,Multi-Class Prediction of Cirrhosis Outcomes
16991,157209572,1444.0,,0,3,/oualihamza/cirrhosis-pred-complete-analysis-log-loss-0,Multi-Class Prediction of Cirrhosis Outcomes
16992,156930187,1471.0,0.582056216803489,0,6,/fabianaguirrechavez/prediction-of-cirrohis-outcomes-catboost,Multi-Class Prediction of Cirrhosis Outcomes
16993,154160261,1479.0,,0,5,/zoubheir/cirrhosis-model,Multi-Class Prediction of Cirrhosis Outcomes
16994,156715849,1473.0,,8,33,/mohamedzaghloula/easy-code-multi-class-prediction-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
16995,156868543,1476.0,0.5908562234601236,0,8,/ajaybabua/multi-class-prediction-of-cirrhosis-log-reg-dtc,Multi-Class Prediction of Cirrhosis Outcomes
16996,154432637,1492.0,0.6468033288730368,1,11,/loannfeidt1/day-5-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16997,154426309,1482.0,,0,1,/srivabhi22/notebook8423864ee4,Multi-Class Prediction of Cirrhosis Outcomes
16998,157233141,1503.0,,0,4,/prudhvi143413s/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
16999,157600585,1512.0,,0,7,/andrewbremner/predict-cirrhosis-s3e26-pytorch-flexible-model,Multi-Class Prediction of Cirrhosis Outcomes
17000,157205108,1515.0,22.971235533996808,0,17,/mirnamuhammad/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17001,154729294,1519.0,0.731321030790569,0,1,/rafiromolo/cirrhosis-pred-using-baggingclassification,Multi-Class Prediction of Cirrhosis Outcomes
17002,159357518,1521.0,0.4317524922382849,0,21,/vishnupriyagarige/prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17003,159357518,1521.0,0.423423952598206,0,21,/vishnupriyagarige/prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17004,159357518,1521.0,0.408413588603417,0,21,/vishnupriyagarige/prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17005,157274282,1531.0,,0,4,/shaziyasultana/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17006,165764317,1527.0,6.19473400895743,2,8,/chamodkalupahana/simple-dnn-model-cham-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
17007,156789058,1533.0,0.7805303400352771,0,5,/sagravela/cirrhosis-baseline,Multi-Class Prediction of Cirrhosis Outcomes
17008,153879470,1555.0,0.922173071859996,0,5,/tracyporter/play-3-26-rf-predict-proba,Multi-Class Prediction of Cirrhosis Outcomes
17009,154553705,1554.0,0.8064361294291695,0,3,/artemzysko/cirrhosis-prediction-pytorch-ensemble-models,Multi-Class Prediction of Cirrhosis Outcomes
17010,156572565,1561.0,1.069498549944366,0,13,/nazimcherpanov/prediction-of-cirrhosis-out-deep-learning,Multi-Class Prediction of Cirrhosis Outcomes
17011,158996655,1567.0,,0,1,/jayyanamandala/prediction-of-cirrhosis-outcomes-using-dl-nn,Multi-Class Prediction of Cirrhosis Outcomes
17012,155163994,1578.0,0.9751618182580482,0,8,/kalpanagarige/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17013,157332626,1586.0,,0,4,/reshmirbabu/cirrhosis-outcome,Multi-Class Prediction of Cirrhosis Outcomes
17014,153720093,1594.0,1.6232909883006716,0,6,/rishabh15virgo/s3e26-first-impression-eda-baseline-ensemble,Multi-Class Prediction of Cirrhosis Outcomes
17015,158295283,1602.0,0.4510533249158369,0,0,/usernameprateek/multi-class-prediction-of-cirrhosis,Multi-Class Prediction of Cirrhosis Outcomes
17016,157298017,1606.0,,0,13,/shaikhabdulrafay03/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17017,156444017,1629.0,,0,1,/mihiranpasindu/multi-class-prediction-of-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17018,154153926,1636.0,,0,6,/yassin92/simple-modeling-for-beginers-eny-tips-for-me,Multi-Class Prediction of Cirrhosis Outcomes
17019,154117951,1643.0,3.0883806520623844,6,42,/jocelyndumlao/predicting-cirrhosis-outcomes,Multi-Class Prediction of Cirrhosis Outcomes
17020,155124153,1641.0,4.4008892346717,1,2,/vladimirminaev/eda-xgb-vs-lightgbm,Multi-Class Prediction of Cirrhosis Outcomes
17021,161233999,25.0,162051.0,1,15,/yeoyunsianggeremie/santa-2023-25th-place-moves-distribution,Santa 2023 - The Polytope Permutation Puzzle
17022,161739185,27.0,,0,1,/elvenmonk/santa-puzzles,Santa 2023 - The Polytope Permutation Puzzle
17023,155876184,31.0,,6,76,/robikscube/santa-2023-polytope-permutation-first-look,Santa 2023 - The Polytope Permutation Puzzle
17024,155596131,47.0,1220590.0,4,33,/bio4eta/operation-check,Santa 2023 - The Polytope Permutation Puzzle
17025,156234632,58.0,,5,31,/asiknow/visualize-wreath-21-21-21,Santa 2023 - The Polytope Permutation Puzzle
17026,161301596,60.0,,3,6,/jumpeinagasawa/easy-to-understand-solution-for-globe3-33,Santa 2023 - The Polytope Permutation Puzzle
17027,158511426,69.0,,1,16,/solverworld/commuting-is-not-transitive,Santa 2023 - The Polytope Permutation Puzzle
17028,161832838,77.0,,1,8,/asalhi/enstofindbestsolutionswithcancelpairs,Santa 2023 - The Polytope Permutation Puzzle
17029,156163185,85.0,1181704.0,0,16,/jbomitchell/santa-scorecard-2023,Santa 2023 - The Polytope Permutation Puzzle
17030,161305022,88.0,159862.0,0,17,/takumatoda/so23-wreath-solver,Santa 2023 - The Polytope Permutation Puzzle
17031,157022648,91.0,,7,74,/paulorzp/magic-cube-utilities,Santa 2023 - The Polytope Permutation Puzzle
17032,161334487,107.0,,0,10,/taanieluleksin/milp-implementation-of-permutation-puzzles,Santa 2023 - The Polytope Permutation Puzzle
17033,157905009,115.0,,0,11,/reeseb777/visualize-globe-in-2d,Santa 2023 - The Polytope Permutation Puzzle
17034,157236700,126.0,848875.0,5,65,/crodoc/greedy-improvement-of-valid-solutions,Santa 2023 - The Polytope Permutation Puzzle
17035,157358699,127.0,838176.0,5,44,/werus23/solve-puzzles-with-self-supervision,Santa 2023 - The Polytope Permutation Puzzle
17036,158736673,130.0,,6,58,/bprinz/visualizing-all-unique-solution-states,Santa 2023 - The Polytope Permutation Puzzle
17037,158492904,132.0,,0,14,/snopoff/group-theory-of-santa-puzzles,Santa 2023 - The Polytope Permutation Puzzle
17038,160308789,148.0,785441.0,23,63,/glazed/humble-hillclimber,Santa 2023 - The Polytope Permutation Puzzle
17039,160788658,159.0,780591.0,2,33,/jazivxt/santa-optimization-competition-2023-prep,Santa 2023 - The Polytope Permutation Puzzle
17040,157856082,160.0,,2,22,/vincentjb/solution-validator-fast-numpy-20-sec,Santa 2023 - The Polytope Permutation Puzzle
17041,160111873,165.0,,4,17,/lorresprz/santa23-permutation-identities-of-cube-puzzles,Santa 2023 - The Polytope Permutation Puzzle
17042,158023288,166.0,,0,9,/r00man/santa-2023-metrics-testing,Santa 2023 - The Polytope Permutation Puzzle
17043,158035872,167.0,833130.0,5,60,/cl12102783/cancel-pairs-for-all-puzzles,Santa 2023 - The Polytope Permutation Puzzle
17044,160236008,178.0,786355.0,0,29,/ruiyaoyang/optimization-problems,Santa 2023 - The Polytope Permutation Puzzle
17045,155828966,224.0,1181704.0,9,91,/whats2000/a-star-algorithm-polytope-permutation,Santa 2023 - The Polytope Permutation Puzzle
17046,156807967,226.0,,0,8,/stpeteishii/santa-2023-create-permutation-and-mapping,Santa 2023 - The Polytope Permutation Puzzle
17047,160092027,273.0,,0,16,/ubaydulloasatullaev/polytope-permutation-santa-2024-01-23-787819,Santa 2023 - The Polytope Permutation Puzzle
17048,161367911,295.0,,0,2,/ubaydullohasatullaev/using-rcube-solver,Santa 2023 - The Polytope Permutation Puzzle
17049,161809122,304.0,52480.0,0,1,/johntermaat/java-tool-for-finding-shortcuts,Santa 2023 - The Polytope Permutation Puzzle
17050,159018579,319.0,827041.0,0,0,/lenferdetroud/wayfinder,Santa 2023 - The Polytope Permutation Puzzle
17051,158131252,356.0,,0,2,/bcsong/santa-basic-info,Santa 2023 - The Polytope Permutation Puzzle
17052,159554487,365.0,827047.0,0,3,/olegshpagin/wayfinder-82d4b,Santa 2023 - The Polytope Permutation Puzzle
17053,158397009,368.0,,0,14,/sasidharanm10/interactive-puzzle-solver-data-driven-approach,Santa 2023 - The Polytope Permutation Puzzle
17054,161716339,381.0,,0,12,/ivanlydkin/permutation-model,Santa 2023 - The Polytope Permutation Puzzle
17055,159701223,464.0,1196337.0,0,13,/hechtjp/santa-2023-networkx-find-shortest-path,Santa 2023 - The Polytope Permutation Puzzle
17056,158042772,495.0,827954.0,2,64,/nikolenkosergei/optimize-any-solution-with-group-theory-approach,Santa 2023 - The Polytope Permutation Puzzle
17057,156472383,522.0,1116526.0,0,11,/seanbearden/santa-2023-kociemba-w-greedy-1-116-526,Santa 2023 - The Polytope Permutation Puzzle
17058,156700055,523.0,1204168.0,9,35,/clehmann10/beginner-s-a-star-algorithm-tutorial,Santa 2023 - The Polytope Permutation Puzzle
17059,156016099,524.0,,2,10,/laythaljorani/santa-23-evolutionary-computing-approach-1,Santa 2023 - The Polytope Permutation Puzzle
17060,156507720,557.0,,0,13,/satyaprakashshukl/eda-santa-2023-the-polytope-permutation-puzzle,Santa 2023 - The Polytope Permutation Puzzle
17061,155663158,576.0,1220590.0,0,8,/yunsuxiaozi/santa-2023-welcome-to-this-puzzle-game,Santa 2023 - The Polytope Permutation Puzzle
17062,160053668,599.0,,0,0,/emanuelruzak/rubikai2,Santa 2023 - The Polytope Permutation Puzzle
17063,155775629,614.0,,15,25,/squarehare/q-learning-reinforcement-learning,Santa 2023 - The Polytope Permutation Puzzle
17064,159603151,632.0,,0,8,/vinitkp/santa-2023,Santa 2023 - The Polytope Permutation Puzzle
17065,156477299,669.0,1193986.0,2,14,/middlehigh/permutation-with-kociemba,Santa 2023 - The Polytope Permutation Puzzle
17066,155660601,752.0,,1,62,/zaburo/iterative-replacement-of-k-successive-moves,Santa 2023 - The Polytope Permutation Puzzle
17067,155731808,759.0,,1,16,/zhambalov/brute-force,Santa 2023 - The Polytope Permutation Puzzle
17068,159219255,785.0,,0,6,/mariabistro/permutationpuzzle-interactive-playground,Santa 2023 - The Polytope Permutation Puzzle
17069,156510973,805.0,1181704.0,0,7,/pahirathannithilan/the-polytope-permutation-puzzle,Santa 2023 - The Polytope Permutation Puzzle
17070,155861128,828.0,,0,2,/zakirkhanaleemi/santa-2023-greedy-baseline-improvement,Santa 2023 - The Polytope Permutation Puzzle
17071,159270532,865.0,,0,1,/mydalaharsha/bfsfor35wreaths,Santa 2023 - The Polytope Permutation Puzzle
17072,158563257,1035.0,,3,30,/madhur321/solving-christmas-ornament-puzzles,Santa 2023 - The Polytope Permutation Puzzle
17073,157359021,1053.0,,4,17,/dan3dewey/santa-2023-pondering-permutations,Santa 2023 - The Polytope Permutation Puzzle
17074,158233408,3.0,,8,37,/iqbalsyahakbar/ps4e1-bank-churn-for-starters,Binary Classification with a Bank Churn Dataset
17075,158493739,14.0,,0,3,/natalialimanska/bank-mljar,Binary Classification with a Bank Churn Dataset
17076,160473712,11.0,0.8932078587986793,31,74,/aspillai/bank-churn-dataset-classification-lightgbm,Binary Classification with a Bank Churn Dataset
17077,160195835,27.0,0.8943804266704147,12,67,/chinmayadatt/notebook-analysing-bank-churn-dataset-0-89438,Binary Classification with a Bank Churn Dataset
17078,157558821,12.0,,0,9,/tdoh86/pg-202401-baseline,Binary Classification with a Bank Churn Dataset
17079,161164021,17.0,,0,2,/viliuspstininkas/eda-cross-associational-analysis,Binary Classification with a Bank Churn Dataset
17080,161144950,71.0,,0,4,/veirding/s4e01-bank-customer-churn-prediction,Binary Classification with a Bank Churn Dataset
17081,159053315,101.0,,2,8,/yonatankpl/surname-classification-with-bert,Binary Classification with a Bank Churn Dataset
17082,160511228,40.0,,2,14,/ardaorcun/xgbregressor-with-optuna,Binary Classification with a Bank Churn Dataset
17083,160528618,198.0,,0,15,/mfmfmf3/clean-code-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17084,162497299,28.0,,0,6,/starcs2001/playground-series-s4e1-first-draft,Binary Classification with a Bank Churn Dataset
17085,164808343,39.0,,14,53,/ddosad/ps4e1-eda-neural-networks-bank-churn,Binary Classification with a Bank Churn Dataset
17086,161190644,45.0,0.8965623416293176,0,2,/girishchowdary22/bank-churn-binary-classification-0-89656,Binary Classification with a Bank Churn Dataset
17087,160790744,46.0,0.8854285176603108,1,13,/waltervirany/pgs4e1-beginner-eda-simple-models,Binary Classification with a Bank Churn Dataset
17088,161207463,47.0,0.8963341641195381,12,45,/ashishkumarak/playground-s4e1-bank-churn-prediction-ensemble,Binary Classification with a Bank Churn Dataset
17089,161129601,50.0,,0,3,/ubaydulloasatullaev/bank-churn-binary-classification-autogluon,Binary Classification with a Bank Churn Dataset
17090,161859476,57.0,,0,0,/cnezhmar/eda-binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17091,157626032,64.0,0.747456071931964,0,2,/hidemasatonda/240103-lighgbm-ver0-1,Binary Classification with a Bank Churn Dataset
17092,157718027,70.0,0.8867761160678934,6,28,/oscarm524/ps-s4-ep1-eda-modeling-submission,Binary Classification with a Bank Churn Dataset
17093,160771936,79.0,0.8961235434846302,1,17,/rockiecao/pss4e1-binaryclassificationbankchurn-ensemble,Binary Classification with a Bank Churn Dataset
17094,158427993,85.0,0.892293150566967,0,21,/kdmitrie/pgs41-easy-use-of-h2o-automl,Binary Classification with a Bank Churn Dataset
17095,161400727,90.0,,15,54,/apalladi/top-2-5-solution-catboost-optuna,Binary Classification with a Bank Churn Dataset
17096,159545100,94.0,,7,34,/najeebz/deep-learning-binary-classification-model-pruning,Binary Classification with a Bank Churn Dataset
17097,159280643,98.0,0.8916860464540804,37,114,/arunklenin/ps4e1-advanced-feature-engineering-ensemble,Binary Classification with a Bank Churn Dataset
17098,160464140,24.0,0.8903525776808199,1,5,/maehashitatsuya/no-idea-no-code,Binary Classification with a Bank Churn Dataset
17099,157704722,112.0,0.8849832918930047,4,17,/javohirtoshqorgonov/bank-churn-prediction-eda-analysis,Binary Classification with a Bank Churn Dataset
17100,160952683,122.0,,2,21,/cheesegue/eda-bank-for-japanese,Binary Classification with a Bank Churn Dataset
17101,159154198,116.0,0.8893379660057329,0,13,/rafiwidyansyah/stacked-model-optuna,Binary Classification with a Bank Churn Dataset
17102,158107291,96.0,,0,7,/lonnieqin/bank-customer-churn-prediction-with-lgbm,Binary Classification with a Bank Churn Dataset
17103,157611853,118.0,,2,42,/mohamedzaghloula/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17104,164104062,197.0,0.8945471489317898,0,5,/mikhailnaumov/bank-churn-catboost,Binary Classification with a Bank Churn Dataset
17105,160285045,125.0,,0,4,/bharathtoutireddy/binary-classification-using-xgboost-and-neural-net,Binary Classification with a Bank Churn Dataset
17106,162123514,129.0,,1,8,/abhyudaya12/bank-churn-catboost-result-0-89626,Binary Classification with a Bank Churn Dataset
17107,159364219,130.0,,6,34,/yatharthgautam123789/bank-churn-1,Binary Classification with a Bank Churn Dataset
17108,160425896,131.0,0.8252913092603298,0,7,/nikolayshchipitsin/catboost-woe-auc-825,Binary Classification with a Bank Churn Dataset
17109,159799079,136.0,0.8857480305120917,0,9,/energyshuma/simple-lightgbm-within-30-sec,Binary Classification with a Bank Churn Dataset
17110,157637887,202.0,0.888617478382402,0,5,/shadechen/eda-and-lgb-prediction-for-bank-churn,Binary Classification with a Bank Churn Dataset
17111,157877684,138.0,,8,29,/stechparme/first-eda-view-and-try-submit,Binary Classification with a Bank Churn Dataset
17112,161101262,217.0,0.8936910316662181,3,20,/vishnupriyagarige/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17113,158467099,199.0,0.8853346954036869,13,42,/smitraval24/easy-to-understand-catboost-lightgbm-xgboost,Binary Classification with a Bank Churn Dataset
17114,157614095,196.0,,1,3,/motensor/pgs4e1-baseline-simple-lightgbm-v1,Binary Classification with a Bank Churn Dataset
17115,161217188,208.0,0.890207897401533,48,115,/muhammadibrahimqasmi/decoding-customer-dynamics-cat-89-4,Binary Classification with a Bank Churn Dataset
17116,159523951,179.0,,3,14,/lasm1984/automatize-your-life,Binary Classification with a Bank Churn Dataset
17117,159935439,255.0,,0,1,/samlakhmani/interview-prep-for-faang,Binary Classification with a Bank Churn Dataset
17118,161112499,139.0,0.8911424329003215,3,21,/wonsukj/simple-eda-ensemble-lgbm-xgb-cat,Binary Classification with a Bank Churn Dataset
17119,161574540,155.0,0.8933562880089637,0,0,/ofirflaysher/pgs4-1-xgb-lgbm-catboost-tuning-ensemble,Binary Classification with a Bank Churn Dataset
17120,161156000,220.0,,1,9,/dannyklinger/bank-churn-lgbm-my-first-ever-notebook,Binary Classification with a Bank Churn Dataset
17121,159830194,218.0,,0,3,/c1trus/binary-classification,Binary Classification with a Bank Churn Dataset
17122,160014770,214.0,0.8867173456974644,0,0,/neilanshchauhan/ps-s4-e1-stacking-classifier-simple-0-88671,Binary Classification with a Bank Churn Dataset
17123,160390415,150.0,,2,8,/dipds109/bank-churn-s4e1-catboost-0-896,Binary Classification with a Bank Churn Dataset
17124,161188080,240.0,0.8954660700711083,0,2,/chunhsientsai/ps4e1-feature-engineering-single-xgb-240th,Binary Classification with a Bank Churn Dataset
17125,157435354,227.0,,0,13,/akshatshaw7/simplest-notebook-for-beginners,Binary Classification with a Bank Churn Dataset
17126,160580157,228.0,,0,0,/vishnusaitejan/bank-churn-prediciton-using-catboost,Binary Classification with a Bank Churn Dataset
17127,158209984,251.0,0.8867486362799518,6,10,/aaryansingh729/easy-to-understand-ensemble,Binary Classification with a Bank Churn Dataset
17128,166540494,242.0,,0,7,/byteliberator/bank-churn-i-data-drift-adversarial-validation,Binary Classification with a Bank Churn Dataset
17129,160752732,232.0,,3,20,/lashfire/0-8945-cool-feature,Binary Classification with a Bank Churn Dataset
17130,161027149,307.0,,0,7,/alekcandrr/catboost-0-89,Binary Classification with a Bank Churn Dataset
17131,159283538,256.0,,1,1,/saayan/customer-churn-save-the-heartbroke-bank,Binary Classification with a Bank Churn Dataset
17132,158104172,342.0,,1,1,/kuboiyusuke/notebook0a49d8ce94,Binary Classification with a Bank Churn Dataset
17133,159945387,306.0,0.8932474514692841,2,10,/santusrk/just-catboost-stratifiedkfold-score-0-893,Binary Classification with a Bank Churn Dataset
17134,158714121,281.0,0.8835792306253266,0,12,/lordpatil/simple-light-gbm-base-line,Binary Classification with a Bank Churn Dataset
17135,160416131,264.0,0.8927374483810556,0,21,/xietaowang/s4e01-simple-baseline-eda,Binary Classification with a Bank Churn Dataset
17136,160828552,290.0,,0,1,/anzarwani2/bank-churn-kaggle-playground-s4-ep1,Binary Classification with a Bank Churn Dataset
17137,160513572,311.0,0.890148842458784,0,8,/dghosh05/cat-boost-classifier-bankchurn,Binary Classification with a Bank Churn Dataset
17138,160656389,272.0,0.8898558566963084,0,10,/muhannadmansour/eda-pca-classification-models,Binary Classification with a Bank Churn Dataset
17139,159912495,287.0,,0,14,/jordirosell/understanding-customerid-surname,Binary Classification with a Bank Churn Dataset
17140,160849046,289.0,,0,0,/ronfswanson/fork-of-notebook6924363b35,Binary Classification with a Bank Churn Dataset
17141,157924374,258.0,0.8867761160678934,0,6,/uzairshafique/eda-ensemble-modeling-customer-churn,Binary Classification with a Bank Churn Dataset
17142,157939469,325.0,0.8896112049237446,1,9,/noepinefrin/bank-churn-scaled-encoded-xgb-w-best-tuned,Binary Classification with a Bank Churn Dataset
17143,160714580,315.0,0.708270185085837,0,5,/markusdarkus/logistic-regression-0-72,Binary Classification with a Bank Churn Dataset
17144,160290566,265.0,0.8851678927196998,0,21,/aryangupta30/bank-churn-88-5-accuracy,Binary Classification with a Bank Churn Dataset
17145,157570472,318.0,,0,11,/ksakaida/simply-eda-and-lightgbm-for-japanese,Binary Classification with a Bank Churn Dataset
17146,159229349,305.0,,6,28,/harshitstark/binary-classification-with-a-bank-churn-1-1,Binary Classification with a Bank Churn Dataset
17147,158825000,789.0,0.882559991556863,1,12,/hassaneskikri/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17148,161151268,380.0,0.8934313841696625,0,17,/vinodkumargurjar/binary-classification-with-a-bank-churn-dataset-vk,Binary Classification with a Bank Churn Dataset
17149,158104258,381.0,,5,5,/userbitco/s4ep1-bankchurn-dataset,Binary Classification with a Bank Churn Dataset
17150,158832183,317.0,0.7475232804903156,0,10,/samyakb/using-xgboost-lightgbm,Binary Classification with a Bank Churn Dataset
17151,160657412,345.0,,0,26,/cheesecke/bankchurnclassification,Binary Classification with a Bank Churn Dataset
17152,161224870,310.0,0.8932869760899863,0,13,/zeyadsayedadbullah/playgrounds4e01-bank-churn-eda-catboot-0-89331,Binary Classification with a Bank Churn Dataset
17153,157726371,376.0,0.8851768258160049,0,7,/abramova/s4e1-eda-shap-and-baseline,Binary Classification with a Bank Churn Dataset
17154,159328059,360.0,,2,12,/devsubhash/churn-prediction-eda-lightautoml,Binary Classification with a Bank Churn Dataset
17155,158853565,322.0,0.8922010852351013,0,8,/kokush1bo/ps4e1-catboost,Binary Classification with a Bank Churn Dataset
17156,163442165,328.0,,0,11,/khushimittal27/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17157,160281759,320.0,0.8932123686513153,0,6,/kennanemera/ps4e1-catboost-model-stratifiedkfold,Binary Classification with a Bank Churn Dataset
17158,157452808,387.0,0.7435118748317312,0,5,/sriharshaeedala/bank-churn,Binary Classification with a Bank Churn Dataset
17159,157438500,364.0,0.8147616385129784,0,5,/anthonytherrien/linear-regressions-benchmark,Binary Classification with a Bank Churn Dataset
17160,160562743,271.0,0.8917251751480768,44,103,/abdmental01/bank-churn-lightgbm-and-catboost-0-8945,Binary Classification with a Bank Churn Dataset
17161,158481158,329.0,0.890795922796272,0,4,/timllll/voting-clf-optuna,Binary Classification with a Bank Churn Dataset
17162,158065071,389.0,0.8861449470349049,0,0,/arlle26/s4e1-eda-xgb-optuna-lb0-886,Binary Classification with a Bank Churn Dataset
17163,159931173,333.0,,0,5,/eryaww/adversarial-validation-implementation-ps-s4-e1,Binary Classification with a Bank Churn Dataset
17164,157413633,366.0,,0,2,/bertanpank/ps4e1-churn-classification,Binary Classification with a Bank Churn Dataset
17165,158143760,409.0,0.8911859291607939,1,11,/yunsuxiaozi/pss4e1-baseline-lightautoml,Binary Classification with a Bank Churn Dataset
17166,159753113,353.0,,0,4,/neupane9sujal/binary-classification-lgbm,Binary Classification with a Bank Churn Dataset
17167,157748536,411.0,,0,0,/sovinasahni/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17168,161189557,419.0,0.7550674411652915,4,18,/armanzhalgasbayev/ps-s4-e1-tensorflow-bc-of-bank-churn,Binary Classification with a Bank Churn Dataset
17169,160159660,458.0,0.8920160513635715,16,68,/iqmansingh/bank-churn-kfold-lgbm-cat-xgb-ensemble,Binary Classification with a Bank Churn Dataset
17170,160528274,350.0,,2,8,/adeelhamid/bank-churn-prediction-using-xgboost-with-encoding,Binary Classification with a Bank Churn Dataset
17171,158253827,420.0,,0,5,/anannoasif/bank-churn-using-stacked-prediction-model,Binary Classification with a Bank Churn Dataset
17172,158810588,492.0,0.8857432237144259,0,13,/talhabarkaatahmad/ps4e1-bank-churn-xgboost,Binary Classification with a Bank Churn Dataset
17173,157708554,431.0,,0,1,/ilya2raev/playground-series-s4e1-churn,Binary Classification with a Bank Churn Dataset
17174,159990488,516.0,,0,10,/ishph102016098/binary-classification-bank-churn-df-eda-lgbm-xgb,Binary Classification with a Bank Churn Dataset
17175,159438114,520.0,0.8842528009339911,2,8,/kevin114514/2024-1-binary-classification-xgboost,Binary Classification with a Bank Churn Dataset
17176,157696321,469.0,,21,34,/satyaprakashshukl/bank-customer-churn-classification,Binary Classification with a Bank Churn Dataset
17177,157851569,493.0,,0,1,/tylerjthomas9/tps-s4e1-julia-evotrees-jl-baseline,Binary Classification with a Bank Churn Dataset
17178,159928826,551.0,,0,0,/key0410/lightgbm-jp,Binary Classification with a Bank Churn Dataset
17179,160631050,429.0,,0,6,/fabienpv/surname-classification,Binary Classification with a Bank Churn Dataset
17180,159571622,523.0,0.8908707653164245,1,4,/vitchakorn/ps4e01-bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17181,161197269,473.0,0.8888281608808577,38,131,/mouadberqia/bank-churn-prediction-beginner-friendly-0-88959,Binary Classification with a Bank Churn Dataset
17182,159925605,455.0,0.8866855045294015,0,10,/jirayuwat12/bank-churn-dataset-autogluon,Binary Classification with a Bank Churn Dataset
17183,157393146,528.0,,0,10,/yorkyong/bank-churn-eda-insights-through-data,Binary Classification with a Bank Churn Dataset
17184,159661624,460.0,0.8883028094464154,2,16,/thomasmeiner/ps4e1-easy-fast-modeling-submission,Binary Classification with a Bank Churn Dataset
17185,159023240,803.0,0.8911732595062003,3,16,/arjitdsce/binary-classification-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17186,159399763,802.0,0.4966871389643349,6,32,/anibansal/bank-churn-playground,Binary Classification with a Bank Churn Dataset
17187,167047636,524.0,,3,26,/alexeyk12/catboost-new-features,Binary Classification with a Bank Churn Dataset
17188,160883038,497.0,0.8902124876767813,2,7,/kanishk026/simple-lgbm-classifier,Binary Classification with a Bank Churn Dataset
17189,161543181,812.0,,0,0,/adityamuhammadreza/deep-learning,Binary Classification with a Bank Churn Dataset
17190,160513449,525.0,0.8910097046584737,0,8,/tinatally/binary-callsifiaction-eda-catboost,Binary Classification with a Bank Churn Dataset
17191,160274158,514.0,,0,2,/laxmikurapati/notebook3c4dffe562,Binary Classification with a Bank Churn Dataset
17192,157683337,604.0,0.8727704191775019,0,6,/andrusha95/ps4e1-bankchurn-gb-lgbm,Binary Classification with a Bank Churn Dataset
17193,157731064,505.0,0.8901423529726176,7,10,/valerybonneau/ps4e01-automl-test-with-bluecast-and-autogluon,Binary Classification with a Bank Churn Dataset
17194,162972925,614.0,,15,37,/divyam6969/bank-churns-basic-solution,Binary Classification with a Bank Churn Dataset
17195,158390229,480.0,0.8904846625417703,3,17,/iveeaten3223times/ensemble-wizardry-auc-mastery,Binary Classification with a Bank Churn Dataset
17196,159324176,574.0,0.8853454411019432,4,38,/rohangulati14/binary-classification,Binary Classification with a Bank Churn Dataset
17197,160143603,2178.0,0.8814477901350902,0,0,/adityakbhatia/bank-churn-for-beginners-eda-xgb,Binary Classification with a Bank Churn Dataset
17198,160561791,519.0,,0,12,/yashusinghal/proper-way-to-use-cross-validation-0-89082,Binary Classification with a Bank Churn Dataset
17199,161186494,538.0,0.8907896745779422,3,9,/kirilldolbilov/ps4e1-lama-model,Binary Classification with a Bank Churn Dataset
17200,157946420,553.0,0.8901631700564591,0,8,/ayhampar/catboostclassifier-0-89,Binary Classification with a Bank Churn Dataset
17201,158797302,626.0,,3,13,/tarukon5/bank-churn-prediction-eda,Binary Classification with a Bank Churn Dataset
17202,160486673,591.0,0.890214652900955,0,0,/mirkoferretti/notebookba75b60c9e,Binary Classification with a Bank Churn Dataset
17203,159829256,571.0,0.8898791112039339,47,75,/luficergfree/simplicity-is-the-key-to-success,Binary Classification with a Bank Churn Dataset
17204,159257321,615.0,,0,3,/mariusborel/i-almost-churn-out-of-the-competition,Binary Classification with a Bank Churn Dataset
17205,157591655,509.0,0.8853022356001459,0,7,/abhinavmangalore/s4e1-bank-churn-prediction-1st-approach,Binary Classification with a Bank Churn Dataset
17206,159436667,595.0,0.8797963489123892,0,6,/bantoutou/simple-non-linear-nn-with-pytorch,Binary Classification with a Bank Churn Dataset
17207,160301944,672.0,0.8896047092512234,3,22,/ogulcancck/bank-churn-classification-eda-model-deployment,Binary Classification with a Bank Churn Dataset
17208,159456761,661.0,,0,4,/tamalkoley/churn-dataset,Binary Classification with a Bank Churn Dataset
17209,157403561,564.0,0.5,2,3,/hridaym25/easy-pytorch-nn-optuna,Binary Classification with a Bank Churn Dataset
17210,159661927,587.0,,0,7,/mathewshuvarikov/bank-churn-dataset-with-nlp-hack,Binary Classification with a Bank Churn Dataset
17211,157371333,570.0,,0,6,/taichiuemura/ps4e1-first-view,Binary Classification with a Bank Churn Dataset
17212,159573024,698.0,,0,16,/saimondahal/bank-churn-prediction-for-beginners-0-89-score,Binary Classification with a Bank Churn Dataset
17213,160785545,660.0,0.8904230093300127,0,12,/hopesb/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17214,160006266,869.0,,0,0,/muhammadhadi13/eda-lgbm-xgboost-catboost-accuracy,Binary Classification with a Bank Churn Dataset
17215,160005355,621.0,0.8821065626831162,0,0,/mohamedtahaouf/bank-churn-binary-classification,Binary Classification with a Bank Churn Dataset
17216,160603967,782.0,,0,2,/zhichaocheng/bank-churn-classification-xgb-lgbm-ensemble,Binary Classification with a Bank Churn Dataset
17217,160036870,790.0,0.8900721316594871,8,25,/cybersimar08/bank-churn-oof-preds-xgb-cat-lgb,Binary Classification with a Bank Churn Dataset
17218,158688523,762.0,,0,10,/otcome/s4e1-eda-oof-xgboost-lgbm-catboost-ensemble,Binary Classification with a Bank Churn Dataset
17219,162767423,652.0,,0,1,/sanyamjain479/classification-sklearn,Binary Classification with a Bank Churn Dataset
17220,161209609,680.0,,1,13,/anubhavmaverick/bankchurn,Binary Classification with a Bank Churn Dataset
17221,159370987,674.0,0.883478306433413,3,16,/hieundai/bank-churn-xgboost-88-7,Binary Classification with a Bank Churn Dataset
17222,160873472,704.0,0.7481895756457565,2,9,/minhyeok10/simple-basic-code-with-lgbmclassifier-0-75,Binary Classification with a Bank Churn Dataset
17223,157951172,677.0,,0,6,/santosh1974/2024-ps-s4-e1-v1,Binary Classification with a Bank Churn Dataset
17224,160769533,856.0,0.8896296773791236,3,34,/yashpuri1912/bank-churn,Binary Classification with a Bank Churn Dataset
17225,160167329,833.0,,5,20,/dianaddx/churn-let-s-go-eda-lgbm,Binary Classification with a Bank Churn Dataset
17226,158948365,729.0,,1,22,/tanishqdublish/binary-classification-with-bank-churn,Binary Classification with a Bank Churn Dataset
17227,161238325,846.0,,0,5,/parthr164/ps4e1-bank-churn-classification-lgbmclassifier,Binary Classification with a Bank Churn Dataset
17228,158855575,605.0,,3,12,/thierryneusius/new-features-and-target-encoding-for-the-surname,Binary Classification with a Bank Churn Dataset
17229,158985555,642.0,0.8894546715886954,0,7,/oyebamijimicheal/eloquent-eda-lightgbm-optuna-0-88945,Binary Classification with a Bank Churn Dataset
17230,159757904,771.0,0.8894271484962704,2,15,/sakshamsikri8/notebookcc28113b63,Binary Classification with a Bank Churn Dataset
17231,158548937,793.0,0.8894228489796969,0,4,/shacodes/s4e01-simple-baseline-eda,Binary Classification with a Bank Churn Dataset
17232,159328168,837.0,0.8834640406992857,0,12,/nrng19/notebook1dcbf18fef,Binary Classification with a Bank Churn Dataset
17233,160687556,823.0,0.8843826958253488,1,9,/brassmonkey381/starter-playground-bank-churn-classification,Binary Classification with a Bank Churn Dataset
17234,159363544,819.0,0.8891709096811998,2,30,/piyush1234ggfuvi/bank-churn-lgbm-classifier,Binary Classification with a Bank Churn Dataset
17235,159841223,841.0,0.889104072304135,2,22,/bhavya4400/notebook8353e8aeed,Binary Classification with a Bank Churn Dataset
17236,158093045,898.0,,9,36,/cv13j0/bank-churn-gbdt-ideas,Binary Classification with a Bank Churn Dataset
17237,158145272,962.0,0.8826823700271605,2,21,/sergeydeev/binary-classification-with-a-bank,Binary Classification with a Bank Churn Dataset
17238,158277820,838.0,,0,0,/kkamal2003/binary-classification,Binary Classification with a Bank Churn Dataset
17239,157734819,904.0,,0,8,/timotheguy/first-eda-for-churn-dataset,Binary Classification with a Bank Churn Dataset
17240,164139287,894.0,,0,5,/stefansanchez26/bank-customer-churn-prediction,Binary Classification with a Bank Churn Dataset
17241,161115216,766.0,0.8889720740521515,0,3,/mbilalshaikh/attempt-to-achieve-90,Binary Classification with a Bank Churn Dataset
17242,161187240,732.0,0.8855254392806804,0,0,/gdataranger/bank-churn-xgboostclassifier,Binary Classification with a Bank Churn Dataset
17243,159865950,884.0,,0,8,/aarushijain24/v0003,Binary Classification with a Bank Churn Dataset
17244,159825755,737.0,0.8889292273589313,0,7,/ir1snvtien/part-1-getting-started-with-catboost-pipeline,Binary Classification with a Bank Churn Dataset
17245,160017933,673.0,,0,10,/yashsaini007/ps-s4-e1-eda-model,Binary Classification with a Bank Churn Dataset
17246,160242162,700.0,0.8772224788872083,1,8,/khushikhushikhushi/churn-prediction,Binary Classification with a Bank Churn Dataset
17247,159309684,840.0,0.8888828111390019,4,30,/rijuljain2003/bankchurn-rijul,Binary Classification with a Bank Churn Dataset
17248,159414854,814.0,0.8888650686734871,0,21,/aashimbansal/bankchurn-aashim,Binary Classification with a Bank Churn Dataset
17249,160146268,808.0,,0,20,/harleenkaurdeora/binary-classification-with-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17250,159999518,3237.0,0.8811211382298908,0,0,/andregalhardo/nn-with-cv-tensorflow,Binary Classification with a Bank Churn Dataset
17251,159216058,1006.0,0.8887481774998812,0,27,/jatinthakur706/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17252,160900994,854.0,0.8337922082614067,1,15,/barbagrande007/bbg007-s4e1-bankchurn,Binary Classification with a Bank Churn Dataset
17253,161197574,755.0,,0,0,/liorazaltcman/max-roc-auc-0-8896-bank-churn-predictions,Binary Classification with a Bank Churn Dataset
17254,159373265,964.0,,4,28,/abhinandansharma19/binary-classification-competition,Binary Classification with a Bank Churn Dataset
17255,158256184,963.0,0.8861402701506896,8,14,/pluspin/ps-s4-e01-hyperopt-xgboost,Binary Classification with a Bank Churn Dataset
17256,159429472,784.0,0.8860915216750076,0,1,/maazsaiyed/ps4e1-simple-xgboost,Binary Classification with a Bank Churn Dataset
17257,161093429,886.0,,4,13,/dbreyfogle/simple-neural-net-w-tensorflow-scikit-learn,Binary Classification with a Bank Churn Dataset
17258,159737811,912.0,0.8882624001769792,1,11,/cityuming/bank-churn-binary-classification-easy-to-read,Binary Classification with a Bank Churn Dataset
17259,159737811,912.0,0.8882624001769792,1,11,/cityuming/bank-churn-binary-classification-easy-to-read,Binary Classification with a Bank Churn Dataset
17260,159737811,912.0,0.8882624001769792,1,11,/cityuming/bank-churn-binary-classification-easy-to-read,Binary Classification with a Bank Churn Dataset
17261,161193889,831.0,0.8883595383197662,0,2,/denslinnunes/biclass-bank-churn,Binary Classification with a Bank Churn Dataset
17262,158330302,893.0,0.8874807604366279,0,5,/realshaktigupta/bank-churn-classification-simple-ensemble,Binary Classification with a Bank Churn Dataset
17263,158126019,1086.0,0.5919837338461904,0,4,/maramalhinai/original-vs-generated,Binary Classification with a Bank Churn Dataset
17264,158144908,896.0,,0,24,/goyalharshit03/ps4e1-advanced-feature-engineering-ensemble,Binary Classification with a Bank Churn Dataset
17265,159361314,1010.0,0.8881493631024024,0,5,/siddhantjain03/notebookc0c78a2859,Binary Classification with a Bank Churn Dataset
17266,159359436,977.0,0.8881149360380407,0,7,,Binary Classification with a Bank Churn Dataset
17267,159283763,989.0,0.8875660578963623,0,6,/aarushijuneja07/first-notebook,Binary Classification with a Bank Churn Dataset
17268,159695493,976.0,0.8879575799178057,0,25,/jasmeet0516/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17269,160994374,865.0,,1,6,/natasha23/binary-classification-bank-customer-churn-python,Binary Classification with a Bank Churn Dataset
17270,159143796,973.0,0.8870067928650048,6,38,/amulyat29/binary-classification-bank-churn-xgboost-lightgbm,Binary Classification with a Bank Churn Dataset
17271,157880622,1162.0,0.6600811662120107,0,5,/talnikarvishwam/xgb-hyperparameter-tunning,Binary Classification with a Bank Churn Dataset
17272,165874270,1068.0,,0,0,/jt4v4res/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17273,161227640,1048.0,0.8876742324960804,0,7,/anzhelinashevchuk/bank-churn-competition,Binary Classification with a Bank Churn Dataset
17274,157720191,1017.0,,0,6,/westedcrean/s4e1-eda-lightgbm-optimization,Binary Classification with a Bank Churn Dataset
17275,160405057,931.0,,6,23,/abdulmuid/binary-classification-with-88-accuracy,Binary Classification with a Bank Churn Dataset
17276,159218290,978.0,0.8873738725987046,0,16,/kaurneetlove/notebook3e2825a337,Binary Classification with a Bank Churn Dataset
17277,157579364,1027.0,0.8873390743530558,0,4,/habilamar/playground-s4e1,Binary Classification with a Bank Churn Dataset
17278,161645097,983.0,,3,34,/kriti264/bankchurn,Binary Classification with a Bank Churn Dataset
17279,161101319,1066.0,0.8868509090972079,2,15,/iamdal/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17280,160899803,1026.0,0.8871103029532172,3,21,/klyushnik/bank-churn-dataset-tensorflow,Binary Classification with a Bank Churn Dataset
17281,158731542,1034.0,,0,5,/osamaabobakr/xgboost-base-model-0-88-score,Binary Classification with a Bank Churn Dataset
17282,161928937,1077.0,,0,1,/lamiaaloukhmiri/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17283,158732316,991.0,,0,6,/carloscll/logist-regression-bank-churn-competition,Binary Classification with a Bank Churn Dataset
17284,157552914,1069.0,0.8871318376542134,0,11,/huseyinbaytar/ps4e01-bank-churn-prediction-lgbm-xgb,Binary Classification with a Bank Churn Dataset
17285,157537938,1054.0,0.8871163099037106,2,15,/dumanmesut/ps4e01-bank-churn-prediction-lgbm-xgb,Binary Classification with a Bank Churn Dataset
17286,160113683,1212.0,0.8871046919294299,0,8,/ahmetkoseoglu/ps4e01-bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17287,160113683,1212.0,0.8871046919294299,0,8,/ahmetkoseoglu/ps4e01-bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17288,157606446,1122.0,0.8862786279753891,0,12,/majidabdoos/ps4e1-simple-xgb-model,Binary Classification with a Bank Churn Dataset
17289,161198642,1002.0,0.88709546807445,0,0,/blohorn/classification-training,Binary Classification with a Bank Churn Dataset
17290,159305541,994.0,0.8870843883130355,0,3,/manindermaan/bank-churn-playground,Binary Classification with a Bank Churn Dataset
17291,160758080,961.0,,0,6,/ryancaldwell/exited-rolling-mean,Binary Classification with a Bank Churn Dataset
17292,159052032,1202.0,,0,9,/lucasrathgeb/binary-classification-of-bank-churn,Binary Classification with a Bank Churn Dataset
17293,157538431,1085.0,,0,12,/yldzburhan/ps4e01-bank-churn-prediction-lgbm-xgb,Binary Classification with a Bank Churn Dataset
17294,159051916,1149.0,,0,2,/tusharnarkhede/bank-churn,Binary Classification with a Bank Churn Dataset
17295,159191577,1123.0,0.8870067928650048,0,10,/abhiluvsingla/binary-classification-bank-churn-beginner-friendly,Binary Classification with a Bank Churn Dataset
17296,159191577,1123.0,0.8870067928650048,0,10,/abhiluvsingla/binary-classification-bank-churn-beginner-friendly,Binary Classification with a Bank Churn Dataset
17297,163260290,1124.0,,2,30,/akshaykhanna05/bank-churn-kaggle-competition,Binary Classification with a Bank Churn Dataset
17298,159363224,1125.0,,3,35,/udaysharma007/bankchurnbinaryclassification,Binary Classification with a Bank Churn Dataset
17299,158836335,1056.0,0.8870031924065217,0,3,/meicher/retention-classifier,Binary Classification with a Bank Churn Dataset
17300,157606425,1116.0,0.8869339794692206,2,8,/syerramilli/ps4e01-lightgbm-eda-optuna,Binary Classification with a Bank Churn Dataset
17301,159025482,1229.0,0.8861538553857911,2,9,/hongseoi/ps4e1-binary-classification-using-xgboost,Binary Classification with a Bank Churn Dataset
17302,159453002,997.0,0.8868735264102912,1,11,/imtommi/eda-catboost,Binary Classification with a Bank Churn Dataset
17303,158192815,1129.0,0.8143626928657968,0,6,/bobojamson/pg-s4e1-eda-baselines-and-sklearn-pipeline,Binary Classification with a Bank Churn Dataset
17304,157679927,1089.0,0.8850675995359739,0,10,/chaozhuang/ps4e01-tree-based-models-votingclassifier,Binary Classification with a Bank Churn Dataset
17305,160047382,1062.0,,1,5,/sid4ds/ps-s4e1-deduplication-linear-model,Binary Classification with a Bank Churn Dataset
17306,158403337,1076.0,0.8819547804685397,1,5,/docxian/ps-s4-e01-bank-churn-eda-correlation-glm-gbm,Binary Classification with a Bank Churn Dataset
17307,159168636,1033.0,0.8868475808383351,0,2,/iyasha/notebook5b3c7ed1e9,Binary Classification with a Bank Churn Dataset
17308,159168636,1033.0,0.8868475808383351,0,2,/iyasha/notebook5b3c7ed1e9,Binary Classification with a Bank Churn Dataset
17309,161189666,1137.0,,1,9,/kuryakin/ps-s4e1-eda-modeling-submission,Binary Classification with a Bank Churn Dataset
17310,158968046,1127.0,0.8855287366077792,0,2,/krystianpietrzak/ps04e1-catboost-optuna-pseudolabels,Binary Classification with a Bank Churn Dataset
17311,164357276,1200.0,,2,3,/amitvkulkarni/lime-for-explainability-in-python,Binary Classification with a Bank Churn Dataset
17312,158487262,1138.0,0.8854601917967946,0,1,/aparajitasingh15/bank-churn-0-8854-xgboost-adaboost-randomforest,Binary Classification with a Bank Churn Dataset
17313,165048097,1438.0,,0,1,/emirhancan/churn-data-analysis-xgboost-model,Binary Classification with a Bank Churn Dataset
17314,161918206,1231.0,,1,78,/bravo03/bank-churn-using-xgboost,Binary Classification with a Bank Churn Dataset
17315,159831817,1050.0,,0,3,/gauravduttakiit/pss4e1-flaml-roc-auc,Binary Classification with a Bank Churn Dataset
17316,158503809,1177.0,,1,9,/gabedossantos/optuna-xgboost-and-memes,Binary Classification with a Bank Churn Dataset
17317,157406661,1101.0,0.8859209391282487,2,39,/waalbannyantudre/ps4-ep1-bank-churn-eda-catboost-baseline,Binary Classification with a Bank Churn Dataset
17318,157809159,1175.0,,0,3,/vassyesboy/bank-churn-eda-classification,Binary Classification with a Bank Churn Dataset
17319,159292540,1252.0,0.8866335638946519,0,5,/arryuannkhanna123/simple-solution-xgb-hyper-parameter-tuning,Binary Classification with a Bank Churn Dataset
17320,159882887,956.0,0.8866268950041968,1,2,/nicobarea/s4e1-roc-auc-lgbm-xgb,Binary Classification with a Bank Churn Dataset
17321,161151812,1206.0,0.799871416615856,15,51,/getanmolgupta01/bank-churn-eda-catboost-lgbm-xgboost,Binary Classification with a Bank Churn Dataset
17322,160515451,1221.0,0.8860450126597563,0,0,/shuthdar/straightforward-solution-eda-with-dataprep,Binary Classification with a Bank Churn Dataset
17323,159618164,1108.0,,1,13,/maheshmani13/binaryclassification-logreg-adaboost-ann-automl,Binary Classification with a Bank Churn Dataset
17324,157839027,1196.0,,1,6,/hakim11/bank-churn-89-accuracy-with-ann,Binary Classification with a Bank Churn Dataset
17325,159887608,1173.0,0.8860100845006572,0,1,/fathyalin/voting-classifier-optuna-cross-validation,Binary Classification with a Bank Churn Dataset
17326,159358684,1362.0,0.8865313096364602,0,14,/shreyasharma28/bank-churn,Binary Classification with a Bank Churn Dataset
17327,158545325,1361.0,,0,3,/harshitarya003/xgb-bankchurn-simple-easy-to-understand-0-886,Binary Classification with a Bank Churn Dataset
17328,158952527,1250.0,0.8864910735849579,6,19,/jgabrielsb/ps4e1-eda-model-ensemble-step-by-step,Binary Classification with a Bank Churn Dataset
17329,159274183,1913.0,0.8864819982024927,1,15,/kartikye10/bank-churn-dataset-xgb-rf,Binary Classification with a Bank Churn Dataset
17330,159387322,1792.0,0.886481113553759,2,8,/ronitakhariya/eda-fine-tuning-score-0-886,Binary Classification with a Bank Churn Dataset
17331,162542326,1226.0,0.854395998962672,6,42,/kapturovalexander/kapturov-s-solution-of-ps-s4e1,Binary Classification with a Bank Churn Dataset
17332,159355024,1296.0,0.8864630617705049,0,2,/dakshsethi/binary-classification,Binary Classification with a Bank Churn Dataset
17333,159355024,1296.0,0.8864630617705049,0,2,/dakshsethi/binary-classification,Binary Classification with a Bank Churn Dataset
17334,159357698,1300.0,0.8864630617705049,0,10,/sankalp102/notebookee357b343f,Binary Classification with a Bank Churn Dataset
17335,159363408,1303.0,0.8864630617705049,0,10,/harshitrajpal2508/notebook4e461c53bf,Binary Classification with a Bank Churn Dataset
17336,159569436,1304.0,0.8864630617705049,0,4,/devansharora7/bank-churn-d,Binary Classification with a Bank Churn Dataset
17337,165759211,1172.0,,6,13,/marioandrs/edabinaryclassificationgato,Binary Classification with a Bank Churn Dataset
17338,159363243,1199.0,,0,8,/raaggeesingh/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17339,160956960,1440.0,0.8806273372048367,2,12,/arpitppatel/artificial-neural-network-template-ps4e1,Binary Classification with a Bank Churn Dataset
17340,159193854,1254.0,0.8863829732214972,0,10,/shwetakk/notebookd235b95251,Binary Classification with a Bank Churn Dataset
17341,161112082,1309.0,,0,1,/valentinbelyaev/88-6-s4e1-lgmb-xgb-cb,Binary Classification with a Bank Churn Dataset
17342,160097369,1057.0,0.8750348662955513,7,39,/samarjeetsinghgandhi/binary-classification-with-0-87-accuracy,Binary Classification with a Bank Churn Dataset
17343,158367064,1201.0,,0,2,/michaeloliver137/bank-churn-1,Binary Classification with a Bank Churn Dataset
17344,158121921,1334.0,,1,18,/mannacharya/88-6-xgboost-cv-bank-churn-classification,Binary Classification with a Bank Churn Dataset
17345,160564940,1315.0,,18,36,/devbilalkhan/bank-churn-deep-learning-0-88632,Binary Classification with a Bank Churn Dataset
17346,157716708,1158.0,0.8849030734305466,0,9,/mandritsamikhail/pgs-s4e1-data-insights-optuna-xgb-baseline,Binary Classification with a Bank Churn Dataset
17347,160309995,1641.0,,8,32,/usm811/bank-churn-eda-prediction-catboost-neural-network,Binary Classification with a Bank Churn Dataset
17348,158773863,1111.0,,2,16,/akelsayed/bank-churn-randomforestclassifier-ak-1-90,Binary Classification with a Bank Churn Dataset
17349,161213993,1332.0,0.8862922688876835,0,0,/une510/bank-churn-competition,Binary Classification with a Bank Churn Dataset
17350,161142940,1131.0,,0,3,/ivanvaccari/s04e01-88-eda-catboost-optimized,Binary Classification with a Bank Churn Dataset
17351,157456011,1227.0,,8,22,/mpwolke/bank-churn-pyspark,Binary Classification with a Bank Churn Dataset
17352,157742820,1571.0,0.882917049395816,0,0,/sharvithaa/bankchurndataset-xgboost,Binary Classification with a Bank Churn Dataset
17353,160716313,1366.0,0.8861845087737357,0,4,/rabiaaliasrabia/notebook2bbabb70f4,Binary Classification with a Bank Churn Dataset
17354,160620407,1317.0,0.886243019317264,0,0,/bogdanbozga/bcbcd,Binary Classification with a Bank Churn Dataset
17355,159965634,1218.0,0.886236999994061,1,4,/jinbao/bankcustomerchurnprediction-xgb,Binary Classification with a Bank Churn Dataset
17356,161116063,1415.0,0.8860548613365693,0,1,/niharpatel03/bank-churn-binary-classification-catboost,Binary Classification with a Bank Churn Dataset
17357,157413958,1464.0,0.8862218805429738,0,2,/recursive69/baseline-approach-with-lightgbm,Binary Classification with a Bank Churn Dataset
17358,160829790,1604.0,,0,8,/dkinvoker/playground-s04e01-beginner,Binary Classification with a Bank Churn Dataset
17359,160284386,953.0,0.8862145187807833,1,6,/rizwanahmedabbasi/bank-churn,Binary Classification with a Bank Churn Dataset
17360,159062892,1778.0,0.8861689191596851,0,19,/priyalsingla/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17361,159062892,1778.0,0.8861689191596851,0,19,/priyalsingla/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17362,160863280,1276.0,0.8860939962169203,0,4,/claudiojnior/bank-churn-with-xgbclassifier,Binary Classification with a Bank Churn Dataset
17363,157706477,1637.0,,0,1,/saswattulo/bank-churn-prediction-auc-0-89-simply-explained,Binary Classification with a Bank Churn Dataset
17364,157378418,1390.0,0.8861228246302044,0,2,/rishabh15virgo/first-impression-data-understanding-eda-baselinev1,Binary Classification with a Bank Churn Dataset
17365,158054304,1387.0,,0,4,/gauravru0211/random-search-xgboost-one-hot-encoding,Binary Classification with a Bank Churn Dataset
17366,159272451,1310.0,,4,9,/muratbakirr/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17367,158891507,1449.0,0.885862069776143,0,7,/omkarchoulwar/bank-churn-eda-modelling,Binary Classification with a Bank Churn Dataset
17368,160110261,1826.0,,0,9,/swarooprangle/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17369,160623196,1723.0,,4,9,/vcode1509/pycaret-auto-modelling-starter-lb-0-887,Binary Classification with a Bank Churn Dataset
17370,157778040,1658.0,0.8860558758987536,2,15,/houssem23x/getting-started-with-lgbm,Binary Classification with a Bank Churn Dataset
17371,159828544,1283.0,,15,37,/yeonseokcho/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17372,158267051,1353.0,0.8815715605352137,0,2,/yeemeitsang/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17373,161326874,1282.0,0.8688212420616696,2,2,/antoniobrych/multilayerperceptron-xgboost-churn-detector,Binary Classification with a Bank Churn Dataset
17374,160926788,1548.0,,0,7,/bionicml/88-6-churn-randomforest-surname-frequency-count,Binary Classification with a Bank Churn Dataset
17375,161116928,1544.0,0.8860185598067085,0,0,/sanmatijain/bank-churn-binary-classification-using-lightgbm,Binary Classification with a Bank Churn Dataset
17376,159059432,1242.0,,0,13,/mukul74/lb-0-86-s4e1-randomforest-bankchurnprediction,Binary Classification with a Bank Churn Dataset
17377,160981640,1408.0,,15,33,/siukhan/feature-scaling-on-bank-churn-data,Binary Classification with a Bank Churn Dataset
17378,160837979,1290.0,0.8855189869126426,5,17,/erikfolkesson/detailed-explanation-churn-prediction,Binary Classification with a Bank Churn Dataset
17379,158431828,1251.0,0.8738473398179529,0,9,/neelabhsomani/churn-prediction-with-ann,Binary Classification with a Bank Churn Dataset
17380,159223985,1417.0,0.8831823945251254,2,9,/anmolarora15/bank-churn-s04e01-eda-rf-xgboost-d,Binary Classification with a Bank Churn Dataset
17381,159846921,1846.0,0.8842987655500213,2,13,/ashish32700/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17382,162722770,1589.0,0.8855311616588538,2,24,/aradhakkandhari/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17383,162446967,1338.0,,1,26,/brmil07/binary-classification-with-a-bank-churn-data,Binary Classification with a Bank Churn Dataset
17384,158741274,1687.0,0.8857871282743139,0,14,/ryzhokhina/binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17385,158916566,1452.0,0.8798407050761762,0,8,/mohamedmaboshady/votingclassifier-lgbm-rf,Binary Classification with a Bank Churn Dataset
17386,159982739,1563.0,,0,0,/quratulain20/bank-customer-churn-prediction,Binary Classification with a Bank Churn Dataset
17387,158907296,1312.0,,2,21,/kashish50/bank-churn50,Binary Classification with a Bank Churn Dataset
17388,162410153,1701.0,,0,3,/fatihkgg/churn-classification-xgboost-ann,Binary Classification with a Bank Churn Dataset
17389,157463927,1592.0,,0,3,/connorjd/simple-xgboost-baseline-submission-with-gridsearch,Binary Classification with a Bank Churn Dataset
17390,162459206,1552.0,,0,4,/xinyuanm/bank-churn-newbie-steps,Binary Classification with a Bank Churn Dataset
17391,161404124,1263.0,,0,2,/eu1234/bankchurn-nn-cat-xgb-lgbm-for-generalization,Binary Classification with a Bank Churn Dataset
17392,158266838,1179.0,0.8859086901457803,0,5,/ucas0v0zhuoqunli/ps4e1-flaml,Binary Classification with a Bank Churn Dataset
17393,159353918,1849.0,0.8859010499976244,0,10,/rahulgurwannn/notebookcc547665c2,Binary Classification with a Bank Churn Dataset
17394,157462307,1545.0,,0,3,/eldarsarajlic/bank-churn-simple-modeling,Binary Classification with a Bank Churn Dataset
17395,160903244,986.0,0.884494872996611,0,7,/skipperad/bank-churn,Binary Classification with a Bank Churn Dataset
17396,160602619,1601.0,,1,28,/chetalipushkarna/using-xgboost-classifier,Binary Classification with a Bank Churn Dataset
17397,161094091,1603.0,,2,7,/tyatsenk/xgboost-classifier-for-customer-churn-probability,Binary Classification with a Bank Churn Dataset
17398,161221126,1871.0,0.8851474158853713,4,17,/joochaicoski/churn-prediction-eda-models,Binary Classification with a Bank Churn Dataset
17399,159307137,1961.0,0.8858112859897376,0,7,/krishnanshu1/notebook150446f6c0,Binary Classification with a Bank Churn Dataset
17400,159153200,1550.0,0.8788986222245538,0,4,/kagankoral/ps-s04e01-bank-churn-eda-binary-classification,Binary Classification with a Bank Churn Dataset
17401,161248758,1245.0,,1,15,/aldrinlambon/15-insights-on-bank-churn,Binary Classification with a Bank Churn Dataset
17402,160134353,1505.0,,1,21,/shayalvaghasiya/binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17403,157802913,1610.0,,1,16,/legendsoul/surname-phonetic-analysis,Binary Classification with a Bank Churn Dataset
17404,159349806,1684.0,0.8857767846891182,0,12,,Binary Classification with a Bank Churn Dataset
17405,159349946,1468.0,0.8853815199230318,0,6,/arjav007/ensembles,Binary Classification with a Bank Churn Dataset
17406,157643749,1812.0,,0,10,/lucasdataartist/eda-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17407,159785458,1805.0,0.8846859942412462,0,0,/joaquinmorillas/binary-regression-xgb,Binary Classification with a Bank Churn Dataset
17408,157656267,1631.0,,0,0,/yeehawww/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17409,160315497,1856.0,0.8852891329007174,2,8,/kadernarn/bank-churn-with-classification-models,Binary Classification with a Bank Churn Dataset
17410,160315497,1856.0,0.8852611705771027,2,8,/kadernarn/bank-churn-with-classification-models,Binary Classification with a Bank Churn Dataset
17411,158902311,1640.0,0.8857089884270622,0,10,/mohammadbizhani/bank-churn-cat-lgb-mlp-voting-models-eda,Binary Classification with a Bank Churn Dataset
17412,159361574,1818.0,0.8857206806376003,0,20,/aestroe/bank-churn,Binary Classification with a Bank Churn Dataset
17413,157803624,1165.0,0.8857123785494829,0,3,/ilhambagaz/kompetisi-bank-churn,Binary Classification with a Bank Churn Dataset
17414,159761953,1714.0,0.8855757838358963,0,0,/orestasdulinskas/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17415,160493189,1633.0,,1,10,/utkarshx27/bank-churn-data-analysis-classification,Binary Classification with a Bank Churn Dataset
17416,160562482,1466.0,,3,23,/muhammadfurqan0/bank-churn-prediction-with-xgb-and-lgbm,Binary Classification with a Bank Churn Dataset
17417,159185998,1407.0,0.8856792506196252,0,3,/sergeypolivin/churn-prediction-using-catboost-with-bagging,Binary Classification with a Bank Churn Dataset
17418,161097662,1711.0,,3,7,/carlosalvro/bank-churn-analisys,Binary Classification with a Bank Churn Dataset
17419,161115952,1447.0,0.3614871390633165,0,6,/vishnuoum/bank-churn-classification-nb,Binary Classification with a Bank Churn Dataset
17420,157964281,1580.0,,0,2,/esmailessam/bank-churn-classification-full-eda-xgboost,Binary Classification with a Bank Churn Dataset
17421,160130550,1595.0,0.8854009760088213,0,1,/martinkolda/binary-classification-comparing-lgbm-xgbrf,Binary Classification with a Bank Churn Dataset
17422,161293650,1611.0,0.8859342583500943,0,7,/vivekchaudhary04/churn-i-xgb-i-ann-i-eda-and-feature-engineering,Binary Classification with a Bank Churn Dataset
17423,157826742,1523.0,0.8856360698632469,0,3,/qw1zzard/playground-series-s4e1,Binary Classification with a Bank Churn Dataset
17424,159274209,1712.0,0.8856346593743567,1,16,,Binary Classification with a Bank Churn Dataset
17425,159473064,1413.0,0.885633910825428,0,14,/aayushibareja/notebook,Binary Classification with a Bank Churn Dataset
17426,159840748,1693.0,0.8856330199903394,0,3,/muhammadawaistayyab/bank-churn-xgboost,Binary Classification with a Bank Churn Dataset
17427,159509564,1907.0,0.88563115789755,0,8,/bhavikjikadara/bank-churn-classification-using-xgbclassifier,Binary Classification with a Bank Churn Dataset
17428,160766475,1784.0,,0,1,/rajkumardubey10/bank-churn-using-ann,Binary Classification with a Bank Churn Dataset
17429,160678738,1271.0,,3,22,/hrhuynguyen/s24ep1-binary-classification-w-voting-classifier,Binary Classification with a Bank Churn Dataset
17430,159332686,1404.0,0.8856123142608839,0,10,/pranav28/notebooke2b776720f,Binary Classification with a Bank Churn Dataset
17431,161066541,1514.0,0.8856017355942069,0,3,/suvammistry/ps-s04e1,Binary Classification with a Bank Churn Dataset
17432,160374626,1557.0,,0,1,/guanmingwang/binary-classification,Binary Classification with a Bank Churn Dataset
17433,159020615,1729.0,0.8855847849821041,4,7,/grandmastershaurya/notebook098924a5d8,Binary Classification with a Bank Churn Dataset
17434,161070250,1806.0,,1,3,/pawelkauf/89-playground-s4-e1-lgbm,Binary Classification with a Bank Churn Dataset
17435,161029424,1512.0,,0,1,/ashiksrinivas32/88-acc-xgbclassifier,Binary Classification with a Bank Churn Dataset
17436,160374970,1782.0,,0,7,/pixelshooter/bank-churn-eda,Binary Classification with a Bank Churn Dataset
17437,159856400,1473.0,,39,187,/akhiljethwa/playground-s4e1-eda-modeling-xgboost,Binary Classification with a Bank Churn Dataset
17438,160950857,1485.0,0.7962173966730277,0,1,/naiku007/bank-churn-naive-model-jan24,Binary Classification with a Bank Churn Dataset
17439,161459996,1839.0,,0,1,/arnavs19/bank-churn-binary-classification-torch-lgbm,Binary Classification with a Bank Churn Dataset
17440,160479607,1666.0,0.8854804521087056,0,3,/rgarg1234/bank-churn-prediction-eda,Binary Classification with a Bank Churn Dataset
17441,158879140,1885.0,,0,8,/sandeepbora/eda-s4e1-bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17442,159428189,1576.0,0.8765875609232219,0,9,/nikhilmunakhiya/xgboost-0-88-score,Binary Classification with a Bank Churn Dataset
17443,165560840,1664.0,,0,4,/thedatageek/bank-churn-classfication-eda-analysis,Binary Classification with a Bank Churn Dataset
17444,163715940,1662.0,,1,2,/zhangmaomi/notebook3a093b2e3d,Binary Classification with a Bank Churn Dataset
17445,158457765,1959.0,,1,11,/conradkleykamp/s4e1-bank-churn-binary-classification,Binary Classification with a Bank Churn Dataset
17446,160096891,1704.0,0.8848684236574126,1,13,/chalseo/xgboost-bank-churn-binary-classification,Binary Classification with a Bank Churn Dataset
17447,157798220,1838.0,0.885342607751453,1,0,/fatmanurcetnturk/binary-classification-with-optuna-xgboost,Binary Classification with a Bank Churn Dataset
17448,157798220,1838.0,0.1146573922485469,1,0,/fatmanurcetnturk/binary-classification-with-optuna-xgboost,Binary Classification with a Bank Churn Dataset
17449,160621553,1735.0,,1,11,/agshiv92/beginner-friendly-eda-modeling-submission,Binary Classification with a Bank Churn Dataset
17450,160140560,1629.0,,2,13,/ashwinmali/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17451,161214117,1922.0,0.8834543714267614,0,5,/santiago123678/randomforest-for-bank-exit,Binary Classification with a Bank Churn Dataset
17452,159460389,1810.0,,4,33,/arshiyakishore/notebook-arshiya,Binary Classification with a Bank Churn Dataset
17453,160260479,1930.0,,2,17,/ihsanbt/bank-churn-88-accuracy,Binary Classification with a Bank Churn Dataset
17454,157690180,1738.0,0.8851946610768415,0,0,/hmikraminfo/ps4e1-bankchurn-xgb,Binary Classification with a Bank Churn Dataset
17455,160291156,1465.0,,0,4,/mbhosseini70/churn-problem-0-89-roc-auc,Binary Classification with a Bank Churn Dataset
17456,161232849,1851.0,0.8841362747553172,0,14,/fajemisinadeniyi/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17457,160093201,1697.0,,1,11,/bertrandguillaume/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17458,158864149,1945.0,0.885135476220642,4,17,/mdshariaremonshaikat/bank-customer-churn-prediction-gradient-boost-lr,Binary Classification with a Bank Churn Dataset
17459,159315901,2024.0,0.8851337440413032,1,12,/dhruv5775/notebooka5931c1c86,Binary Classification with a Bank Churn Dataset
17460,160977546,1717.0,0.8838609077312607,1,5,/naimishbhoi/using-hyperparameter-tuning-feature-selection,Binary Classification with a Bank Churn Dataset
17461,159678905,1535.0,,2,8,/wahajsayyed/binaryclassification-bankchurn-lgbm-gridsrch,Binary Classification with a Bank Churn Dataset
17462,158547523,1828.0,0.8848814088161,0,15,/skv1436/pg-s04e01-bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17463,159882125,1910.0,,0,10,/yashsharma1216/prediction-using-various-models,Binary Classification with a Bank Churn Dataset
17464,157898887,1904.0,,1,13,/amanmukati/bank-churn-season-4-episode-1,Binary Classification with a Bank Churn Dataset
17465,157734542,1862.0,0.8849156997806565,0,4,/lseongho/binary-classification-with-a-bank-churn-lightgbm,Binary Classification with a Bank Churn Dataset
17466,159295182,1896.0,,3,18,,Binary Classification with a Bank Churn Dataset
17467,157955353,1890.0,0.8848386054273634,0,9,/chhatrakhandelwal966/binary-classification-with-bank-churn,Binary Classification with a Bank Churn Dataset
17468,157761146,1797.0,0.5009483496290167,0,0,/lmipicaec/very-easy-network,Binary Classification with a Bank Churn Dataset
17469,160244534,1931.0,0.882913300464818,2,11,/towhidultonmoy/bank-churn-submission-roc-89,Binary Classification with a Bank Churn Dataset
17470,162647806,1897.0,,1,16,/ramjaslangdi/binary-classification-bank-church,Binary Classification with a Bank Churn Dataset
17471,160711443,2104.0,,0,17,/samarjeet09/basline-notebook-for-churn,Binary Classification with a Bank Churn Dataset
17472,160540668,1814.0,0.7052845389136562,0,0,/varunguttikonda/bank-churn-competition,Binary Classification with a Bank Churn Dataset
17473,159230617,1872.0,0.6809250493423656,0,9,/desolationofsmaug/data-preprocessing-lightbgm-88,Binary Classification with a Bank Churn Dataset
17474,159325970,1779.0,0.88470319230754,0,3,/obliquedbishop/bank-churn-analysis,Binary Classification with a Bank Churn Dataset
17475,159932884,1933.0,,0,0,/ragul1010101/cifar-10-dataset-prediction,Binary Classification with a Bank Churn Dataset
17476,164355175,2044.0,,0,5,/panavprasoon/bin-classification-with-churn-dataset,Binary Classification with a Bank Churn Dataset
17477,158269880,1815.0,,0,8,/umar47/s4-e1-churns-eda-tuning-submisson-baseline,Binary Classification with a Bank Churn Dataset
17478,158787010,2118.0,0.8779473711951443,2,8,/alirezaze/86-acc-testing-typical-classifiers,Binary Classification with a Bank Churn Dataset
17479,161208689,1895.0,0.8841039572379361,0,2,/sangammahajan01/bank-churn-analysis-with-gradient-boost,Binary Classification with a Bank Churn Dataset
17480,160132153,1951.0,0.8845626321405381,1,7,/rohan1489/binary-classification-easy,Binary Classification with a Bank Churn Dataset
17481,163098356,1843.0,,0,9,/thaparrishav/bankchurndataset-catboostclassifier,Binary Classification with a Bank Churn Dataset
17482,160184643,2043.0,0.8845521029646992,0,4,/prajaktakohinkar/bank-churn-prediction-xgb-acc-0-89,Binary Classification with a Bank Churn Dataset
17483,160184643,2043.0,0.8845521029646992,0,4,/prajaktakohinkar/bank-churn-prediction-xgb-acc-0-89,Binary Classification with a Bank Churn Dataset
17484,160879088,1936.0,,0,2,/chiragsanadhya/bank-churn-with-randomforestclassifier,Binary Classification with a Bank Churn Dataset
17485,159884306,2023.0,,0,8,/khushiattri/bank-churn,Binary Classification with a Bank Churn Dataset
17486,158478847,2106.0,,7,13,/anopsy/xgb-pseudolabels-no-eda-no-fe,Binary Classification with a Bank Churn Dataset
17487,162187091,2091.0,,0,17,/shivamvermathapar/bank-churn-beginner-friendly-shivam-verma,Binary Classification with a Bank Churn Dataset
17488,159144771,2053.0,0.8842408674556166,0,5,/vinaykashyap52/binary-classification-xgboost-classification,Binary Classification with a Bank Churn Dataset
17489,159201184,2099.0,,0,16,/nikhilchadha1537/bank-churn-playground-problem,Binary Classification with a Bank Churn Dataset
17490,160775997,2283.0,0.8089151929944729,0,8,/sawandikirby/r-binary-classification-with-a-bank-churn,Binary Classification with a Bank Churn Dataset
17491,160855257,2018.0,0.8840983338414392,0,7,/tanyajain3108/binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17492,158589294,2016.0,0.8777484180253551,0,3,/kaushaltiwari/basic-ensemble-model,Binary Classification with a Bank Churn Dataset
17493,158257408,2102.0,,12,37,/keenanzhuo/bank-churn-simple-ensemble-ok-results,Binary Classification with a Bank Churn Dataset
17494,166994486,2120.0,,1,2,/kaibalyabiswal/binary-classification-bank-exited-probability,Binary Classification with a Bank Churn Dataset
17495,161096433,2068.0,0.8838649350482239,2,7,/ouaraskhelilrafik/binary-classification-with-a-bank-churn,Binary Classification with a Bank Churn Dataset
17496,161345704,1978.0,,0,0,/uzdavinys/pg-s04e01-fastai-tabular-model,Binary Classification with a Bank Churn Dataset
17497,158799364,1992.0,0.8826230057666725,0,6,/loycelorenzo/bank-churn-imbalance-data-oversampling-fast-ai,Binary Classification with a Bank Churn Dataset
17498,159259691,2004.0,0.8824338084783745,0,1,/nos4a2/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17499,159956298,1963.0,0.8702402990533392,7,17,/junaidullhassan/churn-analysis-gradiantboosting-acc-88-auc-89,Binary Classification with a Bank Churn Dataset
17500,160455542,2126.0,0.8828728478908985,0,4,/zgnzekibozkurt/eda-catboost-probability-prediction,Binary Classification with a Bank Churn Dataset
17501,162347555,2035.0,0.883680699216461,2,50,/alnourabdalrahman9/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17502,161905248,1756.0,,2,23,/eakanshagarwal24/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17503,158570211,2095.0,,0,15,/younesaziz/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17504,159093050,2073.0,0.8739771171685696,0,6,/suranjandas1990/playground-s4e1-eda-bank-churn-data,Binary Classification with a Bank Churn Dataset
17505,159324808,1642.0,,0,20,/raghavdargan/bankchurn-classification,Binary Classification with a Bank Churn Dataset
17506,159335321,1643.0,0.8834640406992857,0,15,/rohanthakur336/bank-churn-binary-classification-first-playground,Binary Classification with a Bank Churn Dataset
17507,159346960,1644.0,0.8834640406992857,0,15,/himanshu230/notebookcc86c35725,Binary Classification with a Bank Churn Dataset
17508,159346960,1644.0,0.8834640406992857,0,15,/himanshu230/notebookcc86c35725,Binary Classification with a Bank Churn Dataset
17509,159348266,1645.0,0.8834640406992857,2,6,/jhaaayush40/bank-churn-pred,Binary Classification with a Bank Churn Dataset
17510,160231974,1646.0,,0,10,,Binary Classification with a Bank Churn Dataset
17511,161490635,2312.0,,0,1,/meantaek/binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17512,160269524,2249.0,,0,5,/samiratpadkar/classification-using-gradientboosting-lightgbm,Binary Classification with a Bank Churn Dataset
17513,160862623,2248.0,0.8833755139623553,0,5,/akhilpm1996/bank-churn-classification-using-h2oautoml,Binary Classification with a Bank Churn Dataset
17514,160836626,2055.0,,0,1,/diphylleia/s4e1-sub1,Binary Classification with a Bank Churn Dataset
17515,157426512,2196.0,0.8831675782054225,1,23,/manavgupta92/smallest-notebook-you-ever-need-ps4e1,Binary Classification with a Bank Churn Dataset
17516,161212853,2152.0,0.8827078268770886,2,16,/danielfourie/ps4e1-bank-churn-eda-feature-engineering-ann,Binary Classification with a Bank Churn Dataset
17517,157872159,2181.0,,0,0,/shwetalishimangaud/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17518,161203855,2017.0,,0,4,/samsonoo/bank-churn-notebook-88,Binary Classification with a Bank Churn Dataset
17519,159183593,2169.0,0.882112439720159,0,7,/ssarkar445/s4e1-bank-churn-dataset-nn-xgb,Binary Classification with a Bank Churn Dataset
17520,158626093,2074.0,0.8814531475183316,6,15,/deepakdodi/neural-networks-end-end-cat-boost-0-88-score,Binary Classification with a Bank Churn Dataset
17521,160772009,2219.0,,2,19,/sibtainali110/bank-churn-compeition,Binary Classification with a Bank Churn Dataset
17522,161054622,2230.0,,0,2,/taqijaved/bank-churn-with-xgboost,Binary Classification with a Bank Churn Dataset
17523,157888716,2005.0,,1,14,/yiwenyuan1998/tabular-deep-learning-with-pytorch-frame,Binary Classification with a Bank Churn Dataset
17524,159156565,2213.0,0.882837245419128,2,9,/vidyalakshmy/ps-s4e1-eda-model-building-hyperparamtuning,Binary Classification with a Bank Churn Dataset
17525,161238575,2154.0,,0,1,/adisongoh/bank-churn-using-neural-nets-kerastuner,Binary Classification with a Bank Churn Dataset
17526,163046034,2139.0,,2,19,/drishtiagarwal20/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17527,163045657,2140.0,,0,28,/mannatpruthi/bank-churn-problem,Binary Classification with a Bank Churn Dataset
17528,163151911,2141.0,,0,0,/ashnaarora/binary-classification-with-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17529,159355797,2143.0,,0,11,/paramvir705/bank-churn-classification-problem,Binary Classification with a Bank Churn Dataset
17530,157744824,2308.0,0.8826777550064933,4,10,/natchananprabhong/basic-bank-churn-prediction-xgb-random-forest,Binary Classification with a Bank Churn Dataset
17531,159505069,2204.0,,0,3,/moorekevin/bank-churn,Binary Classification with a Bank Churn Dataset
17532,157671050,2135.0,,0,4,/leonanmaciel/using-neural-networks-for-predictions,Binary Classification with a Bank Churn Dataset
17533,161125669,2233.0,0.8700422119732194,0,2,/encode0/binary-classification-with-tensorflow,Binary Classification with a Bank Churn Dataset
17534,159450486,2351.0,0.8804073318697243,5,40,/rajneesh231/bank-churn-random-forest,Binary Classification with a Bank Churn Dataset
17535,158696720,2303.0,0.88253637824066,0,5,/islamic/customer-churn-competition,Binary Classification with a Bank Churn Dataset
17536,160839505,2294.0,,4,22,/sabinakhadysy/binary-classification-bank-churn-dataset-xgb-model,Binary Classification with a Bank Churn Dataset
17537,160930645,2103.0,0.8814568964493292,0,4,/touficissa/bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17538,160975265,2182.0,,0,17,/priyanshuganwani09/binary-classification-eda-modeling-gbdt,Binary Classification with a Bank Churn Dataset
17539,157537101,2260.0,0.8151690037890186,4,8,/wanana20/ps-s4e1-r,Binary Classification with a Bank Churn Dataset
17540,161441438,2166.0,,0,4,/ambrustorok/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17541,160173908,2125.0,,0,5,/eviltrtl/bank-churn-with-embeddings,Binary Classification with a Bank Churn Dataset
17542,158567195,2263.0,,0,4,/vaibhavbawej07/random-forest-binary-classification,Binary Classification with a Bank Churn Dataset
17543,157480531,2264.0,0.8819690028981836,1,10,/fanhuaiyuan/my-simple-baseline235235,Binary Classification with a Bank Churn Dataset
17544,162806997,2311.0,,2,19,/adrianasalcedo/xgb-rf-lr,Binary Classification with a Bank Churn Dataset
17545,160056390,2287.0,0.8818739866750867,29,57,/danishammar/bank-churn-165034-dl,Binary Classification with a Bank Churn Dataset
17546,160439363,2310.0,0.8818201220839997,0,5,/lorispanza/basic-nn-0-88182,Binary Classification with a Bank Churn Dataset
17547,161085807,2291.0,0.881771559198961,0,0,/amitankushwaghmare/predict-churn,Binary Classification with a Bank Churn Dataset
17548,158446659,2208.0,0.8817313478928781,0,0,/divyanshuxyz/binary-classification-using-tensorflow,Binary Classification with a Bank Churn Dataset
17549,160707737,2323.0,0.8817283722562279,0,7,/eminztrk/xgboost-identifying-outliers,Binary Classification with a Bank Churn Dataset
17550,158366511,2338.0,0.8537106869526313,0,9,/andrewbremner/bankchurn-s4e1-sklearn-models-vs-pytorch,Binary Classification with a Bank Churn Dataset
17551,159030257,2297.0,0.8815020320938187,6,26,/prathamesh0205/bank-crunch-eda-xgboost-lightgbm,Binary Classification with a Bank Churn Dataset
17552,157699660,2306.0,0.3362795188104778,0,1,/rajsahu2004/initial-eda,Binary Classification with a Bank Churn Dataset
17553,159323997,2298.0,0.8814311735861458,0,6,/pratul007/bank-churn-prediction-with-adaptive-learning-rate,Binary Classification with a Bank Churn Dataset
17554,159632962,2348.0,0.8812804739836562,0,1,/pavlobaranchuk/binary-classification-with-bank-churn,Binary Classification with a Bank Churn Dataset
17555,157825561,2355.0,,0,3,/hitenmandaliya/bank-churn-classification-eda-modelling,Binary Classification with a Bank Churn Dataset
17556,157569488,2336.0,0.7304103136927294,0,1,/bhaskarboruah/bank-churn,Binary Classification with a Bank Churn Dataset
17557,159574563,2319.0,0.8808806931785788,0,15,/junaidk0012/customer-churn-ann,Binary Classification with a Bank Churn Dataset
17558,159889275,2349.0,,0,2,/ridanshkaul/notebook460bb58c9d,Binary Classification with a Bank Churn Dataset
17559,161207581,2386.0,,0,2,/abdelrahmanahmed110/bank-churn-binary-classification,Binary Classification with a Bank Churn Dataset
17560,158665297,2327.0,,0,0,/divakaivan12/various-svm-models-for-bank-churn-classification,Binary Classification with a Bank Churn Dataset
17561,161060119,2360.0,,0,8,/farwa99/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17562,163100822,2464.0,,0,14,/suhawni/notebook376af7ede3,Binary Classification with a Bank Churn Dataset
17563,160430702,2419.0,,0,33,/ankit1743/bank-churn-gradient-boosting,Binary Classification with a Bank Churn Dataset
17564,159350373,2370.0,0.8803312644513247,0,6,/gamablobyt/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17565,161178822,2463.0,0.8801840168348036,0,12,/sirishasingla1906/binary-classification-with-bank-churn,Binary Classification with a Bank Churn Dataset
17566,160560165,2365.0,,0,4,/abhijeetrao/beginner-binary-classification-bank-churn-data,Binary Classification with a Bank Churn Dataset
17567,159730639,2413.0,,3,22,/nishthakumari20/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17568,159300630,2414.0,0.8798531334629331,2,19,/namishjindal4/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17569,159333160,2415.0,0.8798531334629331,0,11,/adityagoel2205/binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17570,159344059,2416.0,0.8798531334629331,2,23,/mannatsadana/bank-churn-binary-classification,Binary Classification with a Bank Churn Dataset
17571,157550788,2434.0,0.8795584526392475,0,1,/pohzixiang/ps4e1-bank-churn-with-resampling,Binary Classification with a Bank Churn Dataset
17572,160151824,2493.0,,4,24,/hamzashakeel30/data-detective-s-tale-about-bank-churn,Binary Classification with a Bank Churn Dataset
17573,161350249,2409.0,0.636980142048604,0,11,/raghavendrarao/bankchurn-v1,Binary Classification with a Bank Churn Dataset
17574,158996030,2455.0,0.8790665322660468,0,12,/kavyas21itr052/bank-churn-xgboost,Binary Classification with a Bank Churn Dataset
17575,160351788,2392.0,0.8789940714924853,0,0,/debyulbae/bank-churn-fcn,Binary Classification with a Bank Churn Dataset
17576,160382080,2457.0,,1,16,/tanejanikhil/binary-classification,Binary Classification with a Bank Churn Dataset
17577,157571658,2448.0,0.8038012118821565,0,1,/tracyporter/play-4-1-predict-proba,Binary Classification with a Bank Churn Dataset
17578,158887149,2449.0,0.8788866021372123,0,1,/akashmishra091/prediction-by-randomforest,Binary Classification with a Bank Churn Dataset
17579,158887149,2449.0,0.8788866021372123,0,1,/akashmishra091/prediction-by-randomforest,Binary Classification with a Bank Churn Dataset
17580,159363666,2452.0,0.8788866021372123,0,7,/swasti19/notebooka94e131937,Binary Classification with a Bank Churn Dataset
17581,160251694,2402.0,0.8763964767967155,0,0,/virajhemantha/xgboost-algorithm-fine-tuned-hyperparameters,Binary Classification with a Bank Churn Dataset
17582,160862255,2504.0,,0,0,/shashankray7/notebookdef0e3a9b1,Binary Classification with a Bank Churn Dataset
17583,159400885,2406.0,,0,3,/vengadeshwaran58/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17584,160002910,2521.0,,0,4,/gregemmen/binary-classification-for-bank-churn-ge-notebook,Binary Classification with a Bank Churn Dataset
17585,157637061,2488.0,,0,1,/abdallahgomaa/binary-classification-for-bank-customers,Binary Classification with a Bank Churn Dataset
17586,160255587,2454.0,0.8783162820898596,0,0,/shadenabdulah1/shaden-playground-series-s4e1,Binary Classification with a Bank Churn Dataset
17587,160382936,2497.0,0.8777969190468461,0,2,,Binary Classification with a Bank Churn Dataset
17588,160967687,2556.0,,0,9,/vayanshgarg/rf-xgb-cat-ensemble-bank-churn-notebook,Binary Classification with a Bank Churn Dataset
17589,159307670,2501.0,,1,4,/fabrciomacena/bank-churn-eda-gradientboosting-roc-curve,Binary Classification with a Bank Churn Dataset
17590,159652525,2439.0,0.8776568228564529,0,14,/nitleenk/bank-churn-notebook,Binary Classification with a Bank Churn Dataset
17591,159899962,2513.0,,0,1,/satomi54/churnprediction,Binary Classification with a Bank Churn Dataset
17592,159357349,2526.0,0.8772997897629191,0,20,/devbansal2140/binary-classification-using-xgboost,Binary Classification with a Bank Churn Dataset
17593,158286808,2545.0,,0,3,/vladislavonufrienko/s4e1-eda-enn-catboostclass,Binary Classification with a Bank Churn Dataset
17594,157430070,2538.0,,0,3,/thaonguyentrang/dummy-coding-preprocess-by-rapidminer-lightgbm,Binary Classification with a Bank Churn Dataset
17595,159361346,2575.0,0.8764660485425937,0,7,/pritishpriyam4/bank-churn-basic-s-notebook,Binary Classification with a Bank Churn Dataset
17596,158961704,2502.0,0.8764657825293382,1,18,/sabasolgol/96-accurate-customer-churn-prediction-woe-iv,Binary Classification with a Bank Churn Dataset
17597,158961704,2502.0,0.8764657825293382,1,18,/sabasolgol/96-accurate-customer-churn-prediction-woe-iv,Binary Classification with a Bank Churn Dataset
17598,158358756,2498.0,0.8701384716536276,0,14,/mlbysoham/fine-tuned-ensemble-learning-on-churn,Binary Classification with a Bank Churn Dataset
17599,160285633,2540.0,,11,52,/yessicatuteja/bank-churn-classification-with-neural-network,Binary Classification with a Bank Churn Dataset
17600,158395434,2547.0,,0,6,/ibragimovuzoqmurod/bank-churn-123,Binary Classification with a Bank Churn Dataset
17601,157936071,2559.0,,0,4,/graphicsmonster/deep-learning-model-to-predict-bank-churn,Binary Classification with a Bank Churn Dataset
17602,159884241,2568.0,0.8759517026333083,0,9,/jasrehmatkaur/ramen-bankchurn,Binary Classification with a Bank Churn Dataset
17603,159365028,2558.0,0.8755129539794592,0,14,/shamsin/notebook7fe827b2b7,Binary Classification with a Bank Churn Dataset
17604,158437740,2588.0,0.8751515223876757,0,1,/dhayalanrajamohan/notebook-analysis-bank-churn-dataset-0-87515,Binary Classification with a Bank Churn Dataset
17605,159308715,2582.0,0.8751298082823907,0,24,/chiragmohangupta/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17606,161052835,2609.0,0.8676449994951934,0,9,/yazeedalsahouri03/binary-classification-with-a-bank-churn,Binary Classification with a Bank Churn Dataset
17607,157455325,2600.0,0.8750348662955513,0,7,/marcogherbezza/bank-churn-dataset-eda-modelling,Binary Classification with a Bank Churn Dataset
17608,159075219,2601.0,0.8750348662955513,0,9,/ridhii19/problem-1,Binary Classification with a Bank Churn Dataset
17609,160653072,2596.0,,1,8,/harharharhar/bank-churnxbg-8-0,Binary Classification with a Bank Churn Dataset
17610,160768554,2578.0,,0,11,/bhavyaprakash02/bank-churn-86-accuracy,Binary Classification with a Bank Churn Dataset
17611,161128014,2611.0,0.8722067556478945,0,3,/waleedejaz/xgboost-classification,Binary Classification with a Bank Churn Dataset
17612,158353851,2648.0,,0,1,/abdullahkhanuet22/bank-churn-prediction-eda-accuracy-87-1,Binary Classification with a Bank Churn Dataset
17613,159352053,2675.0,0.8709611331125382,0,6,/chaitanya2605/notebook228fe7958c,Binary Classification with a Bank Churn Dataset
17614,160810798,2647.0,,0,5,/melodykoh/bank-churn-prediction-eda-optuna,Binary Classification with a Bank Churn Dataset
17615,159354744,2708.0,0.8709307952286873,0,6,/lookitskhushboo/notebookca6a1e3a68,Binary Classification with a Bank Churn Dataset
17616,161210042,2627.0,,0,4,/natapelysynka/bank-churn-binary-classification-task,Binary Classification with a Bank Churn Dataset
17617,159181823,2684.0,0.8708544123061939,0,24,/akshita0560/randomforest-bankchurn,Binary Classification with a Bank Churn Dataset
17618,159184045,2685.0,0.8708544123061939,0,17,/neelakshigupta/test1,Binary Classification with a Bank Churn Dataset
17619,159226972,2670.0,,2,19,/khushibansal15/bank-churn-data,Binary Classification with a Bank Churn Dataset
17620,159300047,2689.0,,0,8,/saanvi004/binary-classification,Binary Classification with a Bank Churn Dataset
17621,159358074,2691.0,0.8708544123061939,0,8,/parthvashish/notebook76f106bf8a,Binary Classification with a Bank Churn Dataset
17622,159478472,2693.0,0.8708544123061939,1,9,/akshit2605/notebook7a6dff8a08,Binary Classification with a Bank Churn Dataset
17623,158556991,2654.0,,0,10,/snehalpawar22/simple-eda-and-insights,Binary Classification with a Bank Churn Dataset
17624,159776246,2666.0,0.8706528794264605,0,0,/yasithakavishka/bank-churn-competition,Binary Classification with a Bank Churn Dataset
17625,159354684,2700.0,,0,8,/jindal05/bank-churn,Binary Classification with a Bank Churn Dataset
17626,159843232,2650.0,0.1227550646449329,0,6,/goutham01/binary-classification,Binary Classification with a Bank Churn Dataset
17627,159167605,2681.0,,0,0,/farheenshaukat/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17628,160534550,2620.0,0.5,0,2,/shivanshuverma/easy-beginner-friendly-80-accuracy,Binary Classification with a Bank Churn Dataset
17629,160776065,2621.0,,0,10,/tarndeepsingh16/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17630,160023718,2622.0,0.8701508196177724,0,13,/nitishjolly/bank-churn,Binary Classification with a Bank Churn Dataset
17631,160023718,2622.0,0.8701508196177724,0,13,/nitishjolly/bank-churn,Binary Classification with a Bank Churn Dataset
17632,158928117,2671.0,0.8698830618100977,0,14,/hardik201003/binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17633,157806378,2706.0,,2,12,/samrat12/churn-prediction-with-random-forest-87-03,Binary Classification with a Bank Churn Dataset
17634,159232264,2629.0,0.8693566525089875,0,9,/garvitmadaan/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17635,159339483,2630.0,0.8693566525089875,0,17,/dubeyarpit/notebookf44163aa68,Binary Classification with a Bank Churn Dataset
17636,159346779,2631.0,,1,12,/aryandogra/aryandogra-bankchurn,Binary Classification with a Bank Churn Dataset
17637,160766828,2661.0,0.8691136153750217,0,20,/bhavikasaini/bank-churn-smotetomek-and-randomforest,Binary Classification with a Bank Churn Dataset
17638,164550890,2730.0,,0,0,/denisemtatih/bank-churn,Binary Classification with a Bank Churn Dataset
17639,163001821,2780.0,,0,9,/jasleen234/notebook9a18423ca6,Binary Classification with a Bank Churn Dataset
17640,159301490,2672.0,0.8688068959049301,0,9,/shauryachichra5/binary-classification-with-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17641,157909741,2704.0,,0,2,/ishratunnisa/bankchurn-eda-n-prediction,Binary Classification with a Bank Churn Dataset
17642,162392116,2754.0,,0,2,/temiloluwapikuda/bank-customer-churn-prediction,Binary Classification with a Bank Churn Dataset
17643,157469432,2740.0,0.8675668101571037,0,11,/hubert101/pg-s04e01-your-universal-data-visualization-pipe,Binary Classification with a Bank Churn Dataset
17644,159360958,2726.0,0.8674203234622206,0,20,/khushiagarwal2068/notebook3d6a012e0a,Binary Classification with a Bank Churn Dataset
17645,159360958,2726.0,0.8674203234622206,0,20,/khushiagarwal2068/notebook3d6a012e0a,Binary Classification with a Bank Churn Dataset
17646,161683358,2732.0,0.7115985243811666,0,12,/adityav32/bankchurn,Binary Classification with a Bank Churn Dataset
17647,158737875,2741.0,0.8654774368793848,0,9,/hrshpreet/my-first-notebook,Binary Classification with a Bank Churn Dataset
17648,159744786,2767.0,0.8654510211444657,2,7,/nyagami/bank-churn-classification-eda-boosting-ensemble,Binary Classification with a Bank Churn Dataset
17649,158743474,2710.0,,0,2,/phuocnguyenn/mlp-bank-churn,Binary Classification with a Bank Churn Dataset
17650,157798065,2763.0,0.8581829389243464,2,9,/dhineshbabbu/adb-binary-classification-with-a-bank-churn,Binary Classification with a Bank Churn Dataset
17651,162320870,2771.0,,0,1,/sanarpit/bank-churn-beginner-friendly-trying-various-models,Binary Classification with a Bank Churn Dataset
17652,158172382,2785.0,0.8603642414341257,0,0,/mohdarifhakim/notebook20637050a5,Binary Classification with a Bank Churn Dataset
17653,160035364,2789.0,0.8599033765619308,2,11,/haroon669/binary-classification-with-the-bank-churn,Binary Classification with a Bank Churn Dataset
17654,160035364,2789.0,0.8599033765619308,2,11,/haroon669/binary-classification-with-the-bank-churn,Binary Classification with a Bank Churn Dataset
17655,158866975,2786.0,,0,7,/mostafaemad123/binary-classification-with-churn,Binary Classification with a Bank Churn Dataset
17656,160852263,2793.0,,0,8,/betlbaak/ps4e01-bank-churn-classification-random-forest,Binary Classification with a Bank Churn Dataset
17657,159180627,2805.0,,0,0,/saravanadhanabal/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17658,160239647,2802.0,0.8515231176654577,0,15,/enizzzz/beginner-friendly-regression-classification,Binary Classification with a Bank Churn Dataset
17659,158270312,2799.0,0.8530576429691337,0,1,/amaninaman/gridsearchcv-decisiontree-on-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17660,157998959,2808.0,0.8449748116378697,0,10,/suyashkapil/bank-churn-neural-networks,Binary Classification with a Bank Churn Dataset
17661,160635047,2828.0,,0,3,/soumyadeepsarkar12/notebook66c137efe7,Binary Classification with a Bank Churn Dataset
17662,158687201,2839.0,,0,8,/sturarods/bank-churn-preditions-w-lr-rf-knn-dt,Binary Classification with a Bank Churn Dataset
17663,159234903,2836.0,0.8377072057670685,2,5,/adam23r/bank-churn-classification-new-in-kaggle,Binary Classification with a Bank Churn Dataset
17664,158253181,2849.0,0.8350433242798093,4,13,/seokhyokang/r-bank-churn-classification-w-nb-rf-and-lgbm,Binary Classification with a Bank Churn Dataset
17665,160136451,2854.0,,6,28,/marianadeem755/bank-churn-classification-neural-network-xgboost,Binary Classification with a Bank Churn Dataset
17666,160371031,2841.0,,0,1,/thermostatic/eda-ml-classifier-implementation,Binary Classification with a Bank Churn Dataset
17667,159351376,2853.0,0.8283299539339277,1,13,/khyatimunjal/bank-churn-playground,Binary Classification with a Bank Churn Dataset
17668,159351376,2853.0,0.8283299539339277,1,13,/khyatimunjal/bank-churn-playground,Binary Classification with a Bank Churn Dataset
17669,160698107,2859.0,,4,35,/alfredkondoro/k-competition-playgrounds4e1,Binary Classification with a Bank Churn Dataset
17670,160286986,2855.0,0.7275779344602726,0,4,/tuhinm2002/bank-churn-classification-pytorch,Binary Classification with a Bank Churn Dataset
17671,159322298,2867.0,0.8231653746258493,0,9,/navjotkaur1312/binary-classification-with-bank-churn,Binary Classification with a Bank Churn Dataset
17672,167034513,2871.0,,14,21,/muhammadnaeem779/eda-churn-prediction-xgboostclassifier,Binary Classification with a Bank Churn Dataset
17673,160789285,2881.0,,4,19,/muhammadhaseebabbasi/tickle-me-xgboost,Binary Classification with a Bank Churn Dataset
17674,157565297,2869.0,,2,4,/vidhikishorwaghela/binary-classification-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17675,161228686,2879.0,0.8148400320007759,0,1,/nickfecondo/s4e01-bank-churn-classification,Binary Classification with a Bank Churn Dataset
17676,160841514,2891.0,,4,51,/ujjvalvashisht/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17677,159370539,2878.0,0.8132272616818175,2,7,/sanyamgoyal401/binary-classification-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17678,158085940,2930.0,0.6794127268660026,6,17,/elaheesl/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17679,159655109,2929.0,0.804190908928939,0,22,/figolm10/bank-churn-prediction-acc-0-81,Binary Classification with a Bank Churn Dataset
17680,159240245,2914.0,0.8035775256659488,0,10,/praneykalra/binary-classification,Binary Classification with a Bank Churn Dataset
17681,158921611,2935.0,,0,0,/sinjoysaha/binary-classification-bank-churn-eda,Binary Classification with a Bank Churn Dataset
17682,160004908,2915.0,,0,0,/sanskritikanagala/bank-churn-data,Binary Classification with a Bank Churn Dataset
17683,161203387,2931.0,0.8030007532505583,6,15,/divyam88/bank-chrun,Binary Classification with a Bank Churn Dataset
17684,163329100,2928.0,,1,9,/adhyanbaluja/bank-churn,Binary Classification with a Bank Churn Dataset
17685,159335807,2937.0,,0,7,/harshitajakiya/xgboost-for-classification,Binary Classification with a Bank Churn Dataset
17686,159070546,2923.0,0.1141700064734016,0,1,/kanimozhiu/eda-modelbenchmarks-lbgm,Binary Classification with a Bank Churn Dataset
17687,158827948,2947.0,,0,7,/hasnainadil/bank-churn-binary-classification-different-methods,Binary Classification with a Bank Churn Dataset
17688,160046798,2976.0,0.7922500316741365,0,3,/biswanathbose/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17689,159118999,3000.0,,0,2,/hasibullahaman/bank-churn-eda-binary-classification,Binary Classification with a Bank Churn Dataset
17690,160244543,2975.0,,2,13,/adityasingh1231/binary-classification-on-bank-churn-data-set,Binary Classification with a Bank Churn Dataset
17691,160313418,2980.0,,0,3,/abhinandansamal/bank-churn-prediction-logistic-regression,Binary Classification with a Bank Churn Dataset
17692,159193625,2990.0,0.7863721780324026,0,14,/palak98039/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17693,159237778,3009.0,,0,13,/burakksz/deep-learning-network-for-bank-churn-dataset-82,Binary Classification with a Bank Churn Dataset
17694,158805195,3018.0,,0,11,/shaikhabdulrafay03/bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17695,158878577,3020.0,,0,14,/chhavidhankhar11/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17696,159946258,3008.0,0.7717690834197775,1,15,/graceveraa/binary-classifaction-with-random-forest,Binary Classification with a Bank Churn Dataset
17697,157498719,3034.0,,0,7,/kirtanmatalia26/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17698,160198147,3027.0,,0,13,/yinn94/bank-churn-predict-acc-0-76,Binary Classification with a Bank Churn Dataset
17699,160037207,3031.0,,0,6,/shagalsajid/binary-classification-eda-tensorflow,Binary Classification with a Bank Churn Dataset
17700,161025935,3035.0,0.7614424302773071,3,33,/maverickss26/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17701,165181935,3036.0,0.8863560254600669,1,15,/japjotsingh699/bank-churn-data,Binary Classification with a Bank Churn Dataset
17702,160738832,3050.0,,0,12,/kaushikkrsarma/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17703,161020254,3056.0,,0,13,/jsonali2003/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17704,157496044,3067.0,0.7489213719256291,0,1,/ericibarra/pss4e1,Binary Classification with a Bank Churn Dataset
17705,159957281,3093.0,,0,4,/philopateergeorgei/using-lightgbm-valid-0-s-auc-95,Binary Classification with a Bank Churn Dataset
17706,161278156,3112.0,0.7462981595347069,0,9,/sanjugag/bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17707,159365661,3158.0,,2,14,/tarushirastogi/bankchurn,Binary Classification with a Bank Churn Dataset
17708,159079763,3099.0,0.741071357870231,0,2,/srsses/binary-classifipcation,Binary Classification with a Bank Churn Dataset
17709,161769437,3133.0,,0,14,/manvirkaur19/bank-churn-notebook,Binary Classification with a Bank Churn Dataset
17710,160977186,3096.0,0.7477330968991021,0,9,/anmol111pal/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17711,160218234,3135.0,,0,9,/myash21/bank-churn-xgb,Binary Classification with a Bank Churn Dataset
17712,159225806,3182.0,0.7469948173194179,0,4,/anastasiyagurinovich/binary-classification-bank-churn,Binary Classification with a Bank Churn Dataset
17713,159663070,3164.0,0.746202295781005,0,10,/utkrishtdutta/banc-churn,Binary Classification with a Bank Churn Dataset
17714,161200872,3193.0,0.7447417716532315,0,5,/qwerty29544/visualization,Binary Classification with a Bank Churn Dataset
17715,159200956,3314.0,,0,14,/kushagrekaushik/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17716,160903961,3256.0,0.7429256558525885,4,4,/guptapriya2609/prediction-using-logistic-regression,Binary Classification with a Bank Churn Dataset
17717,160123518,3217.0,0.7413516244872749,2,5,/scienceenthusiast/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17718,161177713,3251.0,0.7405648933769382,0,0,/codlitswati/bank-churn-classification,Binary Classification with a Bank Churn Dataset
17719,157702443,3247.0,,1,7,/koushikphy/ps4e1-eda-random-forest,Binary Classification with a Bank Churn Dataset
17720,164623308,3244.0,,0,1,/anurag629/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17721,164147028,3242.0,0.8853318125623586,0,3,/mdniazulislamroky/bank-churn-prediction-for-beginners,Binary Classification with a Bank Churn Dataset
17722,160471448,3245.0,0.7375867079486245,0,6,/mirfayzirgashevdku/playground-series-bank-churn-s4-e1,Binary Classification with a Bank Churn Dataset
17723,159475278,3294.0,,0,4,/eduardomarinho44/bank-churn-competition-binary-classification,Binary Classification with a Bank Churn Dataset
17724,159867110,3284.0,0.7369973463012526,0,1,/imran2501/classification-using-randomforestclassifier,Binary Classification with a Bank Churn Dataset
17725,159215217,3331.0,,0,4,/dinamus/xgboost-churn-model-attempt,Binary Classification with a Bank Churn Dataset
17726,161008966,3298.0,,0,7,/marcogtt/74-with-randomforest-need-help-to-improve,Binary Classification with a Bank Churn Dataset
17727,161073020,3266.0,,0,3,/golu20201singh/bank-churn-copm,Binary Classification with a Bank Churn Dataset
17728,163312435,3274.0,,1,10,/sannidhyajain/bank-churn-prediction-random-forest,Binary Classification with a Bank Churn Dataset
17729,157424298,3315.0,0.7345404478722899,0,8,/kavinbr20isr022/random-forest2,Binary Classification with a Bank Churn Dataset
17730,160238105,3340.0,0.7287819413870105,0,5,/gullude/classification-using-logistic-regression-basic,Binary Classification with a Bank Churn Dataset
17731,159728939,3363.0,,0,0,/anuragfx818/notebook-for-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17732,160804984,3370.0,,0,0,/vishnumuralikrishnan/bank-churn-basic-notebook,Binary Classification with a Bank Churn Dataset
17733,157632700,3368.0,,0,3,/prashikmeshram37/bank-churn,Binary Classification with a Bank Churn Dataset
17734,159859487,3381.0,0.7222989632659201,0,129,/hardikgarg03/bank-churn-random-forest-xgboost-and-lightbgm,Binary Classification with a Bank Churn Dataset
17735,158283694,3384.0,,0,1,/a21cdr025/logistic-regression,Binary Classification with a Bank Churn Dataset
17736,160483172,3373.0,0.7218876944000125,2,12,/jurk06/lgbm-for-classification,Binary Classification with a Bank Churn Dataset
17737,157438852,3371.0,0.7182426941624567,0,19,/mdismielhossenabir/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17738,159737134,3390.0,,0,9,/josmyrose/bank-customer-churn1-1,Binary Classification with a Bank Churn Dataset
17739,159129789,3391.0,0.717743232622777,0,7,/jyoti404/binary-classification-with-bankchurndataset,Binary Classification with a Bank Churn Dataset
17740,159217456,3400.0,0.7167136004782795,1,47,/shresthapundir/bank-churn,Binary Classification with a Bank Churn Dataset
17741,157657238,3395.0,0.7163448937332721,0,0,/abhijitdarekar001/eda-baseline-models-customer-churning,Binary Classification with a Bank Churn Dataset
17742,159833664,3420.0,,0,3,/rafsunahmad/bank-churn-classification-kaggle-competition,Binary Classification with a Bank Churn Dataset
17743,159040098,3437.0,,0,0,/healedbike/bankcustomer-dataanalysis,Binary Classification with a Bank Churn Dataset
17744,159661328,3452.0,0.6909041283277639,0,4,/dolomone/simple-rf-model,Binary Classification with a Bank Churn Dataset
17745,157800499,3441.0,0.6869581248119349,0,2,/rajendrakpandey/binary-classification-with-a-bank-churn-dataset-v2,Binary Classification with a Bank Churn Dataset
17746,157877289,3471.0,,1,8,/vinitkp/binaryclassification-churn,Binary Classification with a Bank Churn Dataset
17747,159344591,3472.0,0.6631121026875505,0,13,/kunal025/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17748,159344591,3472.0,0.6631121026875505,0,13,/kunal025/binary-classification-with-a-bank-churn-dataset,Binary Classification with a Bank Churn Dataset
17749,163331290,3473.0,,0,9,/dhruvsinghchauhan01/bank-churn,Binary Classification with a Bank Churn Dataset
17750,159357723,3479.0,0.6622329226913514,0,17,/mayankgupta9/notebookbe73ad5f02,Binary Classification with a Bank Churn Dataset
17751,157992491,3488.0,0.656172670565225,0,9,/venkateshtantravahi/predicting-bank-customer-churn,Binary Classification with a Bank Churn Dataset
17752,160852569,3504.0,,0,11,/prachik2/bank-churn-prediction-simple-code-random-forest,Binary Classification with a Bank Churn Dataset
17753,163791190,3512.0,,0,9,/kirtigupta25/regression,Binary Classification with a Bank Churn Dataset
17754,159365146,3517.0,0.5758611653310739,0,31,/priyanshu54200/bankchurn-ml-ps,Binary Classification with a Bank Churn Dataset
17755,160445574,3524.0,,0,11,/allan7yin/bankchurn,Binary Classification with a Bank Churn Dataset
17756,160174069,3526.0,0.5605698820534343,1,32,/krishuppal/binary-classification-for-bank-churn,Binary Classification with a Bank Churn Dataset
17757,160540395,3529.0,0.5407980694613813,1,12,/meesh11/s4e1-rough-catboost,Binary Classification with a Bank Churn Dataset
17758,160895965,3532.0,0.5,0,7,/punamcheberwal/will-bank-user-exit,Binary Classification with a Bank Churn Dataset
17759,161215995,3547.0,0.5166486684984876,0,3,/muradpitafi/binary-classification-with-bank-churn,Binary Classification with a Bank Churn Dataset
17760,158006503,3553.0,,0,6,/sakshimunde/bank-churn-data-prediction,Binary Classification with a Bank Churn Dataset
17761,161222759,3561.0,0.5002306273062731,2,4,/ikjotsingh221/bankchurnbinclassification,Binary Classification with a Bank Churn Dataset
17762,158950876,3576.0,,0,0,/neeltambe/bank-churn-classification-eda-machine-learning,Binary Classification with a Bank Churn Dataset
17763,159776458,3581.0,0.5,0,2,/kollurusuhaas/binary-classification,Binary Classification with a Bank Churn Dataset
17764,161518928,3583.0,,6,18,/muhammadhidayat99/bank-churn-prediction-by-hidayat,Binary Classification with a Bank Churn Dataset
17765,160642023,3590.0,,0,8,/dibyashree16/using-xgboost-classifier,Binary Classification with a Bank Churn Dataset
17766,160993001,3593.0,0.5,0,16,/vinee0/playgrounds04e01sub1,Binary Classification with a Bank Churn Dataset
17767,160807675,3604.0,0.4796461998954754,2,12,/kkhandekar/comparing-logistic-regression-frameworks,Binary Classification with a Bank Churn Dataset
17768,159793187,3607.0,0.4422820708055525,0,4,/alfiansyach23/bank-churned-prediction-gradient-boosting,Binary Classification with a Bank Churn Dataset
17769,160990258,3608.0,0.3914148242877278,0,5,/somya2115/85-accuracy-bank-churn,Binary Classification with a Bank Churn Dataset
17770,160169514,3616.0,,0,15,/engrhurrirah/mystery-of-bank-churns-ensemble-family,Binary Classification with a Bank Churn Dataset
17771,159201923,3619.0,0.3095042453241056,0,1,/yashaskirnapure/notebook5cc55b36a6,Binary Classification with a Bank Churn Dataset
17772,160628498,3625.0,0.141773063720444,0,7,/avinashtokada25/binary-classification-with-lr-rf,Binary Classification with a Bank Churn Dataset
17773,157454547,3629.0,,0,1,/akshaykharate/bank-churn-prediction,Binary Classification with a Bank Churn Dataset
17774,166542405,5.0,,4,24,/byteliberator/wids-lgbm805-trials-with-new-features-lb-scores,WiDS Datathon 2024 Challenge #1
17775,158475541,33.0,0.7762521071485012,3,9,/jjleesunny/0-776-lb-cleaning-data-stratified-kfold,WiDS Datathon 2024 Challenge #1
17776,163138447,300.0,,10,12,/onurkoc83/catboost-base-feats,WiDS Datathon 2024 Challenge #1
17777,165708088,1.0,,0,4,/ujunwafatima/wids-2024-1st-place,WiDS Datathon 2024 Challenge #1
17778,160374585,85.0,,0,29,/thiagomantuani/wids-datathon2024-eda-modeling,WiDS Datathon 2024 Challenge #1
17779,159236002,168.0,,1,7,/andreakvasnak/wids2024-data-exploration,WiDS Datathon 2024 Challenge #1
17780,166504483,7.0,,0,0,/sajidshahbs/the-synergistic-solvers-top-first-timer,WiDS Datathon 2024 Challenge #1
17781,164967592,129.0,,0,0,/wispvale/catboost-joker,WiDS Datathon 2024 Challenge #1
17782,165159386,163.0,0.8106886989110558,0,2,/nicolsalayoarias/wids-datathon-2024-desaf-o-1-private-score-0-795,WiDS Datathon 2024 Challenge #1
17783,158572029,135.0,0.7983350704765918,2,14,/annafabris/wids-datathon-1-starter-with-catboost,WiDS Datathon 2024 Challenge #1
17784,162656935,139.0,,0,9,/keyuchen2024/catboost-with-detailed-comments,WiDS Datathon 2024 Challenge #1
17785,166339859,4.0,,0,1,/mounvipodapati/pax2m-solution,WiDS Datathon 2024 Challenge #1
17786,163791127,94.0,0.8130919299975166,0,0,/maggiegggggg/wids-datathon-2024-entry-2,WiDS Datathon 2024 Challenge #1
17787,159012935,95.0,0.8039665189154206,0,11,/wolfmedal/equity-in-healthcare-eda-baseline-model,WiDS Datathon 2024 Challenge #1
17788,164589146,113.0,,0,3,/prajja1990/accelerator-wids,WiDS Datathon 2024 Challenge #1
17789,164041813,119.0,,8,52,/ddosad/wids-data-exploration-ml-starter,WiDS Datathon 2024 Challenge #1
17790,158838058,20.0,0.7800948310894711,0,8,/sergeydeev/tfdf-and-wids-datathon,WiDS Datathon 2024 Challenge #1
17791,163178299,131.0,,4,14,/mrsimple07/xgbclassifier-with-optuna,WiDS Datathon 2024 Challenge #1
17792,164046609,188.0,,4,20,/anopsy/wids2024-diagperiodl90-per-state-viz-msnomatrix,WiDS Datathon 2024 Challenge #1
17793,163210127,181.0,0.7963290462895373,8,8,/kooaslansefat/wids-2024-av-bo-catboost,WiDS Datathon 2024 Challenge #1
17794,163184512,201.0,,1,10,/thejas2002/eda-insights,WiDS Datathon 2024 Challenge #1
17795,163463277,202.0,,0,4,/gabrielfreddi/xgboost-optuna-gpu-wids-datathon-2024,WiDS Datathon 2024 Challenge #1
17796,160549288,284.0,,0,1,/tammyroberson/notebookee5eda153a,WiDS Datathon 2024 Challenge #1
17797,162022081,333.0,0.7995497381115433,0,10,/uzairshafique/wids2024-eda-xgboost-0-799,WiDS Datathon 2024 Challenge #1
17798,159822686,240.0,,0,17,/cristianlazoquispe/understanding-cancer-full-eda-icd10-icd9,WiDS Datathon 2024 Challenge #1
17799,164165136,307.0,0.8039782775566109,0,0,/jaspreetkochar1/baseline-notebook-using-h2o,WiDS Datathon 2024 Challenge #1
17800,161721218,255.0,,0,4,/omarvivas/catboost-wids2024,WiDS Datathon 2024 Challenge #1
17801,164309532,350.0,,1,2,/sarahhayounggoldman/wids-v2,WiDS Datathon 2024 Challenge #1
17802,159453193,377.0,0.7977165659499853,1,17,/farzonaeraj/equity-in-healthcare-eda-baseline-model,WiDS Datathon 2024 Challenge #1
17803,164423675,489.0,0.8012074713465431,1,1,/phyosandarwin/wids-2024-prediction-excl-nlp-xgboost-0-801,WiDS Datathon 2024 Challenge #1
17804,165339568,296.0,,1,1,/rahulkrishnag6699/predictive-timely-cancer-treatment,WiDS Datathon 2024 Challenge #1
17805,159223652,352.0,0.7831887647594464,0,5,/sandeepbora/wids-datathone-2024,WiDS Datathon 2024 Challenge #1
17806,165914532,434.0,,0,0,/lilychebotarova/wids-2024-datathon,WiDS Datathon 2024 Challenge #1
17807,163495638,426.0,0.7991217235722188,0,6,/adizz2407/xgboost-wids,WiDS Datathon 2024 Challenge #1
17808,164578498,427.0,0.7991217235722188,0,0,/rekhakanojia/data-champs,WiDS Datathon 2024 Challenge #1
17809,164578498,427.0,0.7991217235722188,0,0,/rekhakanojia/data-champs,WiDS Datathon 2024 Challenge #1
17810,164578498,427.0,0.7991217235722188,0,0,/rekhakanojia/data-champs,WiDS Datathon 2024 Challenge #1
17811,164578498,427.0,0.7991217235722188,0,0,/rekhakanojia/data-champs,WiDS Datathon 2024 Challenge #1
17812,164578498,427.0,0.7991217235722188,0,0,/rekhakanojia/data-champs,WiDS Datathon 2024 Challenge #1
17813,159539858,370.0,,3,16,/vrushalimanka/wids-datathon-eda-baseline-model,WiDS Datathon 2024 Challenge #1
17814,159975518,482.0,,0,0,/farheenshaukat/wids-project,WiDS Datathon 2024 Challenge #1
17815,158900282,324.0,0.7983101421572686,0,12,/danofer/catboost-starter-wids-2024,WiDS Datathon 2024 Challenge #1
17816,164879326,497.0,,0,0,/omniaahmedmahmoud/wids-datathon-2024-challenge-1,WiDS Datathon 2024 Challenge #1
17817,158667611,462.0,0.7327552471760447,0,6,/manavgupta92/the-2-min-maggi-simplest-notebook,WiDS Datathon 2024 Challenge #1
17818,158667611,462.0,0.7573308072636419,0,6,/manavgupta92/the-2-min-maggi-simplest-notebook,WiDS Datathon 2024 Challenge #1
17819,165029511,521.0,,0,5,/bettyhagos/wids-san-diego-students-1sttimekagglers-bkh-ss,WiDS Datathon 2024 Challenge #1
17820,160523977,416.0,,0,7,/katenjoki/wids-2024-eda-mlclassification,WiDS Datathon 2024 Challenge #1
17821,162067063,549.0,,0,1,/yiwenzhuang2606/wids-datathon-2024-timely-treatment-prediction,WiDS Datathon 2024 Challenge #1
17822,158853509,566.0,0.7593786922133337,0,8,/eleonora0/wids-2024-with-pycaret,WiDS Datathon 2024 Challenge #1
17823,158853509,566.0,0.7593786922133337,0,8,/eleonora0/wids-2024-with-pycaret,WiDS Datathon 2024 Challenge #1
17824,158749936,568.0,,0,1,/neerajbansal/neeraj-wids,WiDS Datathon 2024 Challenge #1
17825,164001169,584.0,,0,0,/temwekac/wids-datathon-2024-challenge-first-look,WiDS Datathon 2024 Challenge #1
17826,160782007,608.0,,1,7,/manhhuynguyen/wids-2024,WiDS Datathon 2024 Challenge #1
17827,164271156,620.0,0.6680018211783476,0,3,/petregr/ml-project-bbg,WiDS Datathon 2024 Challenge #1
17828,166293869,619.0,,0,3,/akshilm/akshil-wids-solution-using-rf-svm-lgbmclassifier,WiDS Datathon 2024 Challenge #1
17829,164128300,631.0,,0,0,/qnguyen/eda-xgboost,WiDS Datathon 2024 Challenge #1
17830,159658674,656.0,0.5,4,18,/jennarussell/wids-notebook-intro-to-data-science-concepts,WiDS Datathon 2024 Challenge #1
17831,163003476,667.0,0.4949407270414882,0,4,/gauravkoradiya/wids-assignment-gaurav,WiDS Datathon 2024 Challenge #1
17832,161483666,14.0,0.9064306358381504,0,6,/rockiecao/pss4e2-obesityriskpredict-multiclassification,Multi-Class Prediction of Obesity Risk
17833,165329113,166.0,,7,28,/muzammilbaloch/automl-and-obesity-risk-outcomes,Multi-Class Prediction of Obesity Risk
17834,164748228,316.0,,2,21,/onurrr90/probing-the-public-lb-in-obesity-risk-s4-e2,Multi-Class Prediction of Obesity Risk
17835,161355074,186.0,0.8789739884393064,0,2,/esakaty/pgs42-autogluon-regression,Multi-Class Prediction of Obesity Risk
17836,164922365,1016.0,0.9197976878612716,4,33,/vishnupriyagarige/obesity-risk,Multi-Class Prediction of Obesity Risk
17837,164066686,10.0,,21,44,/kuldeeprathoree/0-92196-multi-class-obesity,Multi-Class Prediction of Obesity Risk
17838,161605118,503.0,,4,18,/moazeldsokyx/playgrounds3e02-eda-modeling-lightgbm,Multi-Class Prediction of Obesity Risk
17839,163045506,19.0,0.91257225433526,1,24,/samlakhmani/91-58-no-fe-cat-lgbm,Multi-Class Prediction of Obesity Risk
17840,161683762,2.0,0.9060693641618496,0,6,/tdoh86/pg4-2-eda-and-baseline,Multi-Class Prediction of Obesity Risk
17841,161814547,1017.0,,1,11,/shyshcuk/score-0-70736-using-transformation-only,Multi-Class Prediction of Obesity Risk
17842,161875891,104.0,0.9140173410404624,9,24,/mfmfmf3/ensemble-multi-class-obesity-risk,Multi-Class Prediction of Obesity Risk
17843,165484714,473.0,,4,10,/natsukihashimoto/sinple-multi-classifier,Multi-Class Prediction of Obesity Risk
17844,161681157,864.0,,8,30,/hassaneskikri/0-9154-accuracy-obesity-risk-season-4-episode,Multi-Class Prediction of Obesity Risk
17845,161457577,107.0,,0,10,/dbreyfogle/eda-key-takeaways-preprocessing-ideas,Multi-Class Prediction of Obesity Risk
17846,164467826,701.0,0.9219653179190752,2,12,/jialuehuang/prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17847,164829569,1025.0,,0,1,/veirding/s4e02-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17848,162431548,1030.0,0.9194364161849712,1,27,/rijuljain2003/soln-obesity-risk-rijul-jain,Multi-Class Prediction of Obesity Risk
17849,162462887,8.0,,3,10,/act18l/s4e2-ordinal-model,Multi-Class Prediction of Obesity Risk
17850,164408086,1035.0,0.9107658959537572,1,9,/bennyfung/multi-class-obesity-flaml,Multi-Class Prediction of Obesity Risk
17851,162932633,1036.0,,0,0,/yuvrajsinghspd09/s4e2-91-simple-eda-modeling-xgb-optuna,Multi-Class Prediction of Obesity Risk
17852,164153759,602.0,,1,9,/ashishkumarak/obesity-risk-prediction-eda-feature-engineering,Multi-Class Prediction of Obesity Risk
17853,161764574,281.0,,0,8,/annadsjp/eda-quick-insights-easy-visualization,Multi-Class Prediction of Obesity Risk
17854,161340142,88.0,0.9096820809248556,1,32,/eishkaran/shortest-code-autogluon,Multi-Class Prediction of Obesity Risk
17855,161649760,1040.0,,0,5,/rangalamahesh/prediction-of-obesity-risk-multi-class,Multi-Class Prediction of Obesity Risk
17856,164522209,603.0,0.911127167630058,1,4,/varunraskar/baseline-lgbm-model-91-40,Multi-Class Prediction of Obesity Risk
17857,164355801,1046.0,,0,5,/panavprasoon/prediction-of-obesity,Multi-Class Prediction of Obesity Risk
17858,161266608,389.0,0.904985549132948,0,5,/ankurgarg04/obesity-risk-predictor-baseline,Multi-Class Prediction of Obesity Risk
17859,162327123,1058.0,0.8948699421965318,0,3,/shahezky/feature-eng-xgbolgbm-cv0-91,Multi-Class Prediction of Obesity Risk
17860,164151650,914.0,,67,231,/ddosad/ps4e2-visual-eda-lgbm-obesity-risk,Multi-Class Prediction of Obesity Risk
17861,161481736,893.0,0.9078757225433526,0,7,/abramova/s4e2-catboost-with-kfold-train,Multi-Class Prediction of Obesity Risk
17862,161318115,410.0,,0,10,/bharathtoutireddy/exploratory-data-analysis-with-plotly,Multi-Class Prediction of Obesity Risk
17863,161532840,673.0,0.91257225433526,0,12,/dghosh05/xgboost-solution-0-91-score,Multi-Class Prediction of Obesity Risk
17864,162031154,49.0,0.8984826589595376,1,4,/humbleyll/mcpor-baseline,Multi-Class Prediction of Obesity Risk
17865,162728564,746.0,,2,21,/mrsimple07/91-5-with-xgbclassifier-optuna,Multi-Class Prediction of Obesity Risk
17866,164174273,24.0,0.9140173410404624,0,0,/nicowxd/ps4e2-top-25-simple-ensemble-private-0-91067,Multi-Class Prediction of Obesity Risk
17867,165668095,1075.0,0.9179913294797688,0,7,/yellayujin/beginner-friendly-obesity-risk-prediction-ml,Multi-Class Prediction of Obesity Risk
17868,164152339,174.0,0.916907514450867,2,10,/aspillai/obesity-risk-prediction-simple-lightgbm-91-7,Multi-Class Prediction of Obesity Risk
17869,164808881,991.0,0.9219653179190752,0,1,/mst923/92-14-obesity-classification,Multi-Class Prediction of Obesity Risk
17870,163104432,1077.0,,0,17,/yatharthgautam123789/xgboost-and-catboost-obesity-risk,Multi-Class Prediction of Obesity Risk
17871,161659357,221.0,,0,5,/subhamsarkar2002/xgboost-on-obesity-gpu,Multi-Class Prediction of Obesity Risk
17872,165635996,1078.0,,0,7,/ssumiii/90-64-private-score-multi-class-lgbm-optuna,Multi-Class Prediction of Obesity Risk
17873,164859748,1081.0,0.9219653179190752,0,6,/hyelin606/multi-class-lgbm-optuna,Multi-Class Prediction of Obesity Risk
17874,161398722,994.0,,2,10,/natapelysynka/obesity-multiclass-classification-feature-eng-xgb,Multi-Class Prediction of Obesity Risk
17875,162777892,310.0,,0,7,/hallojong0319/91-eda-preprocessing-baseline-model-easy,Multi-Class Prediction of Obesity Risk
17876,164924143,899.0,,0,0,/cnezhmar/eda-multiclass-prediction-obesity-risk,Multi-Class Prediction of Obesity Risk
17877,162227260,797.0,,0,21,/harshitstark/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17878,162132532,81.0,,0,8,/itasps/data-analysis-using-clustering,Multi-Class Prediction of Obesity Risk
17879,163389265,82.0,0.9172687861271676,4,21,/chinmayadatt/comparative-study-of-performance-0-92015,Multi-Class Prediction of Obesity Risk
17880,163155872,92.0,,0,2,/kapoorprakhar/multi-class-prediction-of-obesity-risk-2,Multi-Class Prediction of Obesity Risk
17881,161803870,102.0,,4,28,,Multi-Class Prediction of Obesity Risk
17882,161517304,103.0,,26,65,/divyam6969/easy-solution-91-accuracy-xgboost-optuna,Multi-Class Prediction of Obesity Risk
17883,163660406,116.0,,0,19,/jojoyin/multi-class-prediction-with-open-box,Multi-Class Prediction of Obesity Risk
17884,164550306,138.0,0.8670520231213873,0,2,/arinasinghai/obesity-prediction,Multi-Class Prediction of Obesity Risk
17885,164594354,605.0,,0,3,/kuryakin/ps-s4e2-prediction-obesity-risk,Multi-Class Prediction of Obesity Risk
17886,163414053,838.0,,1,9,/juniorbertrand/ps4e02-solution-feature-store-model-registry,Multi-Class Prediction of Obesity Risk
17887,163930243,171.0,0.9053468208092486,0,0,/juyoungss/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17888,163930249,175.0,0.9057080924855492,0,3,/jhw010110/my-first-contest-on-kaggle,Multi-Class Prediction of Obesity Risk
17889,162323843,336.0,,0,7,/miroslavtyurin/ps4e2-obesity-gone-wrong-way-voting-lgbm-xgb,Multi-Class Prediction of Obesity Risk
17890,165110810,2945.0,,0,0,/kaungmyatkyaw/random-forest-optuna-private-lb-0-88665,Multi-Class Prediction of Obesity Risk
17891,163659679,356.0,0.9057080924855492,0,8,/uzairshafique/ps-s4e2-eda-optuna-xgboost-91-accuracy,Multi-Class Prediction of Obesity Risk
17892,163965604,285.0,,0,10,/saurav9786/eda-baseline-model-for-obesity-risk,Multi-Class Prediction of Obesity Risk
17893,161724295,247.0,,4,17,/eouedraogo4/obesity-risk-xgboost-optuna,Multi-Class Prediction of Obesity Risk
17894,163347577,287.0,,20,32,/muhammadfurqan0/ps4e2-obesity-risk-gb-0-90,Multi-Class Prediction of Obesity Risk
17895,162651909,23.0,0.828757225433526,4,13,/ucupsedaya/90-bayesianoptimization-meta-learning-s4e2-comp,Multi-Class Prediction of Obesity Risk
17896,162824076,273.0,0.9107658959537572,0,5,/maehashitatsuya/one-hour-practice,Multi-Class Prediction of Obesity Risk
17897,163206716,278.0,,2,10,/thejas2002/eda-mcpor,Multi-Class Prediction of Obesity Risk
17898,162090467,177.0,0.9183526011560692,5,28,/rzatemizel/lgbm-baseline-tune-to-death,Multi-Class Prediction of Obesity Risk
17899,161809428,191.0,0.9140173410404624,1,7,/paddykb/ps-s4e2-tableau-flaml-brute-force-oh-my,Multi-Class Prediction of Obesity Risk
17900,163930189,497.0,0.8901734104046243,0,0,/hhandaehee/alpha,Multi-Class Prediction of Obesity Risk
17901,163930189,497.0,0.8901734104046243,0,0,/hhandaehee/alpha,Multi-Class Prediction of Obesity Risk
17902,161323527,32.0,0.910043352601156,0,2,/avayaaggarwal27/h2o-auto-ml-for-obesity-dataset,Multi-Class Prediction of Obesity Risk
17903,161921247,35.0,,4,12,/shantanugupta2004/xgboost-91-2-accuracy,Multi-Class Prediction of Obesity Risk
17904,162430241,283.0,0.9151011560693642,1,16,/lashfire/insightfull-noise-feature-exploration,Multi-Class Prediction of Obesity Risk
17905,164312623,209.0,0.9205202312138728,0,1,/soranoki/obesity-risk-lgb-xgb-cat-92,Multi-Class Prediction of Obesity Risk
17906,165645040,210.0,,0,0,/anhkhoango/dap391-thuyet-tr-nh,Multi-Class Prediction of Obesity Risk
17907,162516486,219.0,0.9042630057803468,0,5,/talhabarkaatahmad/ps4e2-obesity-risk-tree-models,Multi-Class Prediction of Obesity Risk
17908,165044134,226.0,,0,6,/luxluxshan/obesity-pri-0-90968-pub-0-91871,Multi-Class Prediction of Obesity Risk
17909,164831608,229.0,0.9194364161849712,0,4,/naokinozawa/lightgbm-stratified-k-fold-model-averaging,Multi-Class Prediction of Obesity Risk
17910,161401696,819.0,0.9071531791907514,2,8,/noepinefrin/ps4e2-cleanest-notebook-w-automl,Multi-Class Prediction of Obesity Risk
17911,161847346,37.0,0.9122109826589596,1,10,/mouadberqia/obesity-risk-prediction-lgbm-xgboost,Multi-Class Prediction of Obesity Risk
17912,161339606,324.0,,0,7,/jokerinthapack/playground-s4e2-dae-ensemble,Multi-Class Prediction of Obesity Risk
17913,164327885,181.0,,0,1,/himayankgour/tensorflow-keras-nn-multiclass-obesity-risk-88,Multi-Class Prediction of Obesity Risk
17914,165423141,193.0,,0,0,/mohammadahmar/obesity-class-predictions,Multi-Class Prediction of Obesity Risk
17915,162761998,960.0,,2,14,/seifwael123/s4e2-91-simple-eda-modeling-xgb-optuna,Multi-Class Prediction of Obesity Risk
17916,161403087,504.0,0.8742774566473989,0,13,/venkatkumar001/obesitys4-tensorflow-embed-xgb-lb-0-874,Multi-Class Prediction of Obesity Risk
17917,161615382,431.0,0.9151011560693642,0,23,/aryangupta30/easy-soluton-91-accuracy-xgboost,Multi-Class Prediction of Obesity Risk
17918,161861678,508.0,0.9194364161849712,0,11,/vanshsethi0198/soln-obesity-risk-vansh,Multi-Class Prediction of Obesity Risk
17919,161861686,509.0,0.9194364161849712,1,7,/hardik2003/soln-obesity-risk-hardik-sharma,Multi-Class Prediction of Obesity Risk
17920,161863343,511.0,0.9194364161849712,0,0,/aparnasingh02/notebook9a38b432ef,Multi-Class Prediction of Obesity Risk
17921,161864980,513.0,0.9194364161849712,0,5,/qdebffg/soln-obesity-risk-shadow,Multi-Class Prediction of Obesity Risk
17922,162657615,400.0,,0,10,/mohamedtahaouf/multi-class-prediction-of-obesity-risk-919,Multi-Class Prediction of Obesity Risk
17923,162479501,527.0,0.9194364161849712,0,17,/bhavya4400/soln-obesity-risk-bhavya-rampal,Multi-Class Prediction of Obesity Risk
17924,161452003,531.0,0.9071531791907514,3,32,/rohangulati14/leading-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17925,162537516,532.0,,0,4,/salonijaroli/notebooka9b91e8447,Multi-Class Prediction of Obesity Risk
17926,161554563,534.0,0.9085982658959536,0,9,/ivanmitriakhin/ps-s4e2-simple-eda-different-models,Multi-Class Prediction of Obesity Risk
17927,161837950,702.0,0.9078757225433526,1,18,/oscarm524/ps-s4-ep2-eda-modeling-submission,Multi-Class Prediction of Obesity Risk
17928,165492591,542.0,,0,0,/kanyaratp29/csc532-obesityrisk,Multi-Class Prediction of Obesity Risk
17929,164554786,544.0,,0,1,/hosseintimasi/obesity-risk-xgboost-tuning,Multi-Class Prediction of Obesity Risk
17930,165636120,546.0,,0,12,/jigeonpark/jgp-s-kaggle-competition,Multi-Class Prediction of Obesity Risk
17931,165574075,393.0,,0,2,/aalex123321/lgbm-with-best-tuning-params-obesity-risk,Multi-Class Prediction of Obesity Risk
17932,166829755,1087.0,,0,5,/alokrajsidhaarth/s4e2-last,Multi-Class Prediction of Obesity Risk
17933,162780000,446.0,,30,68,/mariushinsberger/xgboost-on-obesity-risk,Multi-Class Prediction of Obesity Risk
17934,161713702,449.0,0.8840317919075145,4,16,/waelr1985/playground-series-eda-obesity-risk,Multi-Class Prediction of Obesity Risk
17935,164439971,1215.0,0.8948699421965318,0,1,/sujanadesam/notebookdfc287bcb2,Multi-Class Prediction of Obesity Risk
17936,165356124,788.0,0.9197976878612716,12,36,/ddolddi/eda-with-plotly-ml-obesity-risk,Multi-Class Prediction of Obesity Risk
17937,162544634,443.0,0.6853323699421965,0,0,/swojandattasammya/try-different-cnn-x,Multi-Class Prediction of Obesity Risk
17938,163879547,381.0,0.902456647398844,2,7,/fernandasubekti/88-accuracy-xgboost-obesity-risk,Multi-Class Prediction of Obesity Risk
17939,162947151,366.0,0.9042630057803468,0,1,/kevin114514/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17940,166492651,320.0,,4,19,/kamalapousajja/beginner-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17941,162336397,433.0,0.9035404624277455,1,6,/gulnihall/eda-lgbm-xgb-hyperparameter-tunning-ensemble,Multi-Class Prediction of Obesity Risk
17942,163203486,733.0,0.91871387283237,2,4,/chunhsientsai/ps4e2-feature-engineering-xgb,Multi-Class Prediction of Obesity Risk
17943,163402951,384.0,0.91871387283237,0,10,/parulkumartiet/comparative-study-of-performance,Multi-Class Prediction of Obesity Risk
17944,163250705,241.0,,0,5,/chenjiexu/catboost-baseline,Multi-Class Prediction of Obesity Risk
17945,164955768,1528.0,,0,0,/mania07/classifier-models,Multi-Class Prediction of Obesity Risk
17946,161857809,1089.0,,10,31,/cheesegue/eda-obesity,Multi-Class Prediction of Obesity Risk
17947,161237567,592.0,0.9060693641618496,0,12,/ucas0v0zhuoqunli/pss4e2-flaml,Multi-Class Prediction of Obesity Risk
17948,163034639,331.0,,0,1,/pinoystat/neural-networks-ensemble-voting-classifier,Multi-Class Prediction of Obesity Risk
17949,162104420,318.0,,0,6,/yyazidd/91-076-accuracy-obesity-risk-lgbm,Multi-Class Prediction of Obesity Risk
17950,164422982,459.0,,0,7,/mikhailnaumov/obesity-risk-lgb-xgb-cat-ensemble,Multi-Class Prediction of Obesity Risk
17951,162736954,205.0,0.909320809248555,0,3,/werger/cat-model,Multi-Class Prediction of Obesity Risk
17952,161400868,297.0,,0,10,/anuwaz/ps-s4e2-simple-neural-network,Multi-Class Prediction of Obesity Risk
17953,162332603,822.0,0.9158236994219652,2,8,/abdelrhmanelhelaly/91-5-accuracy,Multi-Class Prediction of Obesity Risk
17954,162332603,822.0,0.9158236994219652,2,8,/abdelrhmanelhelaly/91-5-accuracy,Multi-Class Prediction of Obesity Risk
17955,164301134,289.0,0.9078757225433526,3,23,/victormarzluf/lgbm-optuna-0-917,Multi-Class Prediction of Obesity Risk
17956,161770522,204.0,0.903179190751445,0,5,/neupane9sujal/multi-class-prediction-catboost,Multi-Class Prediction of Obesity Risk
17957,164727551,435.0,0.911127167630058,7,49,/iamdal/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17958,164900996,651.0,0.9165462427745664,0,11,/sunilkumaradapa/automatic-machine-learning-with-h2o-multi-class-pr,Multi-Class Prediction of Obesity Risk
17959,162845249,395.0,,2,10,/karamel03/code-with-explanations-for-beginners,Multi-Class Prediction of Obesity Risk
17960,162494617,723.0,0.9147398843930636,0,4,/harshvardhan21/multi-class-obesity-prediction,Multi-Class Prediction of Obesity Risk
17961,162494617,723.0,0.9147398843930636,0,4,/harshvardhan21/multi-class-obesity-prediction,Multi-Class Prediction of Obesity Risk
17962,163755819,1629.0,,0,2,/vijaychandrareddy/notebook48f600b240,Multi-Class Prediction of Obesity Risk
17963,161300655,333.0,,1,9,/pawelkauf/complexities-of-obesity-comprehensive-eda,Multi-Class Prediction of Obesity Risk
17964,165175874,294.0,,0,4,/metehanpolat1705/obesity-risk,Multi-Class Prediction of Obesity Risk
17965,166452138,637.0,,2,6,/jpkochar/obesity-risk,Multi-Class Prediction of Obesity Risk
17966,162060582,378.0,0.9172687861271676,7,31,/cybersimar08/obesity-risk-prediction-xgb-lgb-oof,Multi-Class Prediction of Obesity Risk
17967,164461910,955.0,,3,15,/kagleo123/playgrounds4e2-obesity-risk-xgb-lgbm-optuna,Multi-Class Prediction of Obesity Risk
17968,163206497,472.0,,2,6,/abdullahkhanuet22/obesity-risk-eda-find-errors,Multi-Class Prediction of Obesity Risk
17969,164225477,812.0,0.9129335260115607,1,9,/hieundai/feature-engineering-xgboost-optuna,Multi-Class Prediction of Obesity Risk
17970,161233912,390.0,,2,18,/gauravduttakiit/pss4e2-autoviz,Multi-Class Prediction of Obesity Risk
17971,161660716,1329.0,,0,1,/kishorevishal/getting-started,Multi-Class Prediction of Obesity Risk
17972,161898451,1332.0,,0,1,/siddharthdash123/obesity-prediction-using-xgboost,Multi-Class Prediction of Obesity Risk
17973,162224576,1117.0,,0,7,/akshatshaw7/simplicity-is-the-key-0-9169,Multi-Class Prediction of Obesity Risk
17974,163098609,931.0,0.9165462427745664,8,7,/satvshr/feature-engineering-at-its-peak-xgb-91-69,Multi-Class Prediction of Obesity Risk
17975,163098609,931.0,0.9154624277456648,8,7,/satvshr/feature-engineering-at-its-peak-xgb-91-69,Multi-Class Prediction of Obesity Risk
17976,163098609,931.0,0.916184971098266,8,7,/satvshr/feature-engineering-at-its-peak-xgb-91-69,Multi-Class Prediction of Obesity Risk
17977,163091430,1339.0,,1,10,/linhhhhhhhh/s4e2-eda-kmean-probabilitystastic-0-91,Multi-Class Prediction of Obesity Risk
17978,162855247,334.0,,0,6,/jedrzejm/basic-usage-of-xgboost-with-default-parameters-91,Multi-Class Prediction of Obesity Risk
17979,165036248,965.0,0.916907514450867,4,28,/radturkin/babys-first-obesity-notebook,Multi-Class Prediction of Obesity Risk
17980,165036248,965.0,0.916907514450867,4,28,/radturkin/babys-first-obesity-notebook,Multi-Class Prediction of Obesity Risk
17981,163930119,1780.0,0.900650289017341,0,1,/j2nhyeok/notebook9431cf47b0,Multi-Class Prediction of Obesity Risk
17982,165220085,854.0,,0,8,/jinyoungheo/91-5-obesity-baseline-essential-contents,Multi-Class Prediction of Obesity Risk
17983,164835529,1108.0,0.916907514450867,0,0,/lixfzz/hypergbm-multiclass-pred-of-obesity-risk,Multi-Class Prediction of Obesity Risk
17984,164920939,1173.0,0.916907514450867,33,41,/danielfourie/ps4e2-obesity-risk-advanced-eda-xgboost,Multi-Class Prediction of Obesity Risk
17985,162472620,481.0,,0,8,/armanzhalgasbayev/ps-s4-e2-lgbm-experiment,Multi-Class Prediction of Obesity Risk
17986,161886152,439.0,,9,26,/kdmitrie/pgs42-just-few-lines-of-autogluon,Multi-Class Prediction of Obesity Risk
17987,162242912,1354.0,0.9165462427745664,2,11,/abyssskb/obesity-risk-xgboost-hyperopt-91-6,Multi-Class Prediction of Obesity Risk
17988,162006939,70.0,0.9085982658959536,0,14,/yunsuxiaozi/pss4e2-baseline-autogluon-classification,Multi-Class Prediction of Obesity Risk
17989,162370579,640.0,,0,32,/akshaykhanna05/prediction-of-obesity-risk-akshay,Multi-Class Prediction of Obesity Risk
17990,162764630,878.0,,0,0,/naimishbhoi/xgboost-with-parameter-tuning-rfecv,Multi-Class Prediction of Obesity Risk
17991,164786567,245.0,0.913656069364162,2,5,/waleedejaz/classification-via-xgboost-optuna-hyperparameters,Multi-Class Prediction of Obesity Risk
17992,162186315,422.0,0.9132947976878611,0,5,/sunny7712/s4e2-eda-baseline,Multi-Class Prediction of Obesity Risk
17993,162845032,881.0,,4,10,/maryamsikander/obesity-risk-prediction-92-accuracy-lgbm,Multi-Class Prediction of Obesity Risk
17994,162730861,886.0,,0,5,/fatmanurcetnturk/basic-eda-with-the-data-summary-function,Multi-Class Prediction of Obesity Risk
17995,164421947,1578.0,0.9114884393063584,0,1,/nivedithavudayagiri/obesity-risk-eda-baseline-results,Multi-Class Prediction of Obesity Risk
17996,162791254,576.0,,0,4,/amitadhi/multi-class-prediction-of-obesity-risk-rfc,Multi-Class Prediction of Obesity Risk
17997,161410060,428.0,0.9057080924855492,0,10,/netojoseeaugusto/obesity-risk-playground-baseline-and-simple-eda,Multi-Class Prediction of Obesity Risk
17998,164338027,1738.0,,0,0,/transhumanistx/exploring-tabnet-multiclass-obesity-prediction,Multi-Class Prediction of Obesity Risk
17999,161741287,903.0,,0,8,/yashusinghal/just-baseline-notebook-still-getting-good-score,Multi-Class Prediction of Obesity Risk
18000,161921039,427.0,,0,0,/shiwayz/97-4-orig-91-75-comp-obesity-pred,Multi-Class Prediction of Obesity Risk
18001,162378762,724.0,,2,7,/vivekrevi/pg-s4e2-lb-score-0-91-xgb-simple,Multi-Class Prediction of Obesity Risk
18002,165478148,623.0,,0,5,/sunseahappy/playground-202402-1,Multi-Class Prediction of Obesity Risk
18003,164901658,340.0,0.9129335260115607,0,2,/ghostdragons/obesity-prediction,Multi-Class Prediction of Obesity Risk
18004,161571656,715.0,0.9154624277456648,0,5,/iosaman/aman-s-soln5,Multi-Class Prediction of Obesity Risk
18005,163847911,1123.0,0.9114884393063584,3,27,/aradhakkandhari/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18006,161642894,656.0,0.9154624277456648,3,30,/jasmeet0516/obesity-risk-using-xgboost,Multi-Class Prediction of Obesity Risk
18007,161642741,657.0,0.9154624277456648,0,33,/jatinthakur706/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18008,161647089,658.0,0.9154624277456648,1,20,/kaurneetlove/multiclass-obesity-risk,Multi-Class Prediction of Obesity Risk
18009,162179384,739.0,0.9132947976878611,27,68,/apalladi/top-10-with-simple-eda-votingclassifier,Multi-Class Prediction of Obesity Risk
18010,161903958,741.0,,0,7,/umairabbasi6/20-simple-steps-fe-to-model-pred,Multi-Class Prediction of Obesity Risk
18011,162451059,517.0,,0,2,/imtommi/simple-eda-xgboost,Multi-Class Prediction of Obesity Risk
18012,162035599,1227.0,0.9154624277456648,0,17,/priyalsingla/multiclass-prediction-of-obesityrisk,Multi-Class Prediction of Obesity Risk
18013,162565904,868.0,,0,1,/priyang/91-55-multi-class-lgbmclassifier,Multi-Class Prediction of Obesity Risk
18014,161550084,1337.0,0.910043352601156,0,8,/fajemisinadeniyi/obesity-classification,Multi-Class Prediction of Obesity Risk
18015,162373315,722.0,,1,36,/udaysharma007/obesity-risk,Multi-Class Prediction of Obesity Risk
18016,163787853,399.0,0.907514450867052,3,17,/shadechen/eda-lgb-optuna-tunning,Multi-Class Prediction of Obesity Risk
18017,161635837,675.0,,0,3,/uviiiii/predictions-89-simple-xgboost,Multi-Class Prediction of Obesity Risk
18018,164820613,426.0,0.9129335260115607,5,26,/getanmolgupta01/obese-pred-92-eda-catboost-lgbm-xgboost,Multi-Class Prediction of Obesity Risk
18019,161780861,375.0,0.9017341040462428,1,13,/sergeydeev/multi-class-with-tfdf,Multi-Class Prediction of Obesity Risk
18020,161238392,690.0,,0,11,/taichiuemura/ps4e2-first-look,Multi-Class Prediction of Obesity Risk
18021,161494794,766.0,,0,8,/santosh1974/ps4-e2-v2-eda-and-stunning-visualizations,Multi-Class Prediction of Obesity Risk
18022,163417041,726.0,,0,4,/seyvom/91-5-tutorial-eda-xgbclassifier-optuna,Multi-Class Prediction of Obesity Risk
18023,164834062,1421.0,,0,0,/rushilmisra/obesity-risk-using-ensemble-model,Multi-Class Prediction of Obesity Risk
18024,164616152,374.0,,0,0,/aharun/data-py,Multi-Class Prediction of Obesity Risk
18025,161467630,1226.0,,0,3,/kowshikdebnath/ensamble-xgboost-catboost-lightgbm-90-35,Multi-Class Prediction of Obesity Risk
18026,161991301,1334.0,,0,0,/rasva1/obesity-risk,Multi-Class Prediction of Obesity Risk
18027,162283933,846.0,0.9147398843930636,0,4,/utkarshx27/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18028,162322939,486.0,0.8442919075144508,0,7,/kalpanagarige/obesity-risk-data,Multi-Class Prediction of Obesity Risk
18029,162322939,486.0,0.911849710982659,0,7,/kalpanagarige/obesity-risk-data,Multi-Class Prediction of Obesity Risk
18030,162322939,486.0,0.9147398843930636,0,7,/kalpanagarige/obesity-risk-data,Multi-Class Prediction of Obesity Risk
18031,161454002,747.0,0.904985549132948,2,14,/ivanvaccari/s04e02-90-eda-catboost-hyperoptimized,Multi-Class Prediction of Obesity Risk
18032,162470962,748.0,0.9147398843930636,1,49,/shresthapundir/multi-class-obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18033,162728252,1205.0,0.914378612716763,2,9,/victorhts/competition-prediction-of-obesity-risk-gbc,Multi-Class Prediction of Obesity Risk
18034,161692453,674.0,,0,0,/obliquedbishop/ps4e2-eda-and-visualization,Multi-Class Prediction of Obesity Risk
18035,163378264,754.0,0.9147398843930636,0,0,/tmsniper/multi-class-prediction-of-obesity-risk-using-lgbm,Multi-Class Prediction of Obesity Risk
18036,163371615,238.0,,0,1,/ntambaraetienne/obesity-team-combetition,Multi-Class Prediction of Obesity Risk
18037,164010397,570.0,,2,3,/mawro73/multi-class-prediction-0-92-lgbm-top15,Multi-Class Prediction of Obesity Risk
18038,164806299,1229.0,0.911849710982659,0,8,/hopesb/obesity-risk-get-above-0-9-in-the-leaderboard,Multi-Class Prediction of Obesity Risk
18039,164806299,1229.0,0.91257225433526,0,8,/hopesb/obesity-risk-get-above-0-9-in-the-leaderboard,Multi-Class Prediction of Obesity Risk
18040,164806299,1229.0,0.902456647398844,0,8,/hopesb/obesity-risk-get-above-0-9-in-the-leaderboard,Multi-Class Prediction of Obesity Risk
18041,164806299,1229.0,0.910043352601156,0,8,/hopesb/obesity-risk-get-above-0-9-in-the-leaderboard,Multi-Class Prediction of Obesity Risk
18042,164806299,1229.0,0.9107658959537572,0,8,/hopesb/obesity-risk-get-above-0-9-in-the-leaderboard,Multi-Class Prediction of Obesity Risk
18043,161977897,1466.0,,0,5,/mikolajkloczewski/ps4e2-xgb-optuna-91-4-short-simple,Multi-Class Prediction of Obesity Risk
18044,162246363,1115.0,0.9085982658959536,1,17,/meesh11/s4e2-forest-classifiers,Multi-Class Prediction of Obesity Risk
18045,162532614,1266.0,0.914378612716763,0,5,/ethanabimelech/obesity-risk-eda-xgboost,Multi-Class Prediction of Obesity Risk
18046,161381641,934.0,,0,11,/anzarwani2/beginner-notebook-91-accuracy,Multi-Class Prediction of Obesity Risk
18047,164536998,1303.0,,0,4,/ikromjonovhojiakbar/notebookab0f77037d,Multi-Class Prediction of Obesity Risk
18048,164870921,1238.0,,0,1,/benzilla987/pg-s4-e2,Multi-Class Prediction of Obesity Risk
18049,162227438,1107.0,0.9017341040462428,0,7,/zeyadsayedadbullah/s4e02-obesity-risk-pred-catboost-0-905,Multi-Class Prediction of Obesity Risk
18050,161350896,342.0,0.7727601156069365,0,7,/prateek2002154/playground-s4e2-ml-models,Multi-Class Prediction of Obesity Risk
18051,161507798,1154.0,0.9140173410404624,1,18,,Multi-Class Prediction of Obesity Risk
18052,161589856,1114.0,0.9140173410404624,1,11,/pollicio/easy-solution-92-accuracy-optuna-acuevas,Multi-Class Prediction of Obesity Risk
18053,162081808,950.0,,3,11,/userbitco/playground-s4e2-eda-ensemble-modeling,Multi-Class Prediction of Obesity Risk
18054,161634638,951.0,,0,7,/khedasusnigdha/babys-first-obesity-notebook,Multi-Class Prediction of Obesity Risk
18055,161689623,1260.0,0.9140173410404624,0,8,/manindermaan/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18056,161764559,358.0,0.9140173410404624,5,44,/kriti264/obesity-risk-prediction-using-lgbm-and-xgb,Multi-Class Prediction of Obesity Risk
18057,161765793,952.0,0.9140173410404624,2,57,/mdismielhossenabir/plotly-analysis-and-prediction,Multi-Class Prediction of Obesity Risk
18058,161898869,362.0,,2,9,/hbsaakashyadav/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18059,162713144,1161.0,0.9140173410404624,0,16,/aryandogra/multi-class-prediction-of-obesity-risk-aryandogra,Multi-Class Prediction of Obesity Risk
18060,162713144,1161.0,0.9140173410404624,0,16,/aryandogra/multi-class-prediction-of-obesity-risk-aryandogra,Multi-Class Prediction of Obesity Risk
18061,163930182,1535.0,0.9010115606936416,0,0,/jihoonyoon332/ml-mc,Multi-Class Prediction of Obesity Risk
18062,163930136,1580.0,,0,1,/ivvy107/notebookef5189001f,Multi-Class Prediction of Obesity Risk
18063,161238550,1555.0,0.913656069364162,1,19,/florianbeklein/autogluon-baseline-model,Multi-Class Prediction of Obesity Risk
18064,162659105,397.0,0.910043352601156,1,7,/ofirflaysher/pgs4-2-xgb-lgbm-catboost-tuning-ensemble,Multi-Class Prediction of Obesity Risk
18065,164029377,1203.0,0.9122109826589596,0,6,/vishnuoum/obesity-risk-eda-modelling,Multi-Class Prediction of Obesity Risk
18066,162627300,1565.0,,0,8,/smitraval24/eda-baseline-xgb-lgbm-catboost-pipelines,Multi-Class Prediction of Obesity Risk
18067,163122378,471.0,0.9042630057803468,0,8,/pinarismiguzel/obesity-risk-eda-catboost,Multi-Class Prediction of Obesity Risk
18068,161371842,629.0,,1,17,/dinamus/simple-eda-xgboost-90-accuracy,Multi-Class Prediction of Obesity Risk
18069,163238962,687.0,,1,10,/realpaulmahler/comparison-of-xgboost-categorical-params,Multi-Class Prediction of Obesity Risk
18070,161334649,1460.0,,2,11,/amjadbakri/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18071,164847273,1974.0,,0,2,/grazynah/prediction-with-tensorflow,Multi-Class Prediction of Obesity Risk
18072,163098332,321.0,0.9107658959537572,7,34,/yorkyong/obesity-risk-xgb-rf-cb-ensemble,Multi-Class Prediction of Obesity Risk
18073,161593711,634.0,,0,9,/parthr164/ps4e2-obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18074,161917626,742.0,0.9132947976878611,0,16,/paramvir705/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18075,162350742,524.0,,2,11,/gabedossantos/eda-xgboost-91-5,Multi-Class Prediction of Obesity Risk
18076,164969059,327.0,,0,4,/mvoulo/predictingobesity,Multi-Class Prediction of Obesity Risk
18077,162732428,1981.0,0.9132947976878611,0,0,/williamdieterfrank/obesity-risk-simple-xgboost-0-91329,Multi-Class Prediction of Obesity Risk
18078,163080172,1008.0,0.9132947976878611,0,0,/artemkhadris/optuna-solution-no-graphs,Multi-Class Prediction of Obesity Risk
18079,165026634,650.0,,1,12,/anubhavmaverick/anubhav-obesity-prediction,Multi-Class Prediction of Obesity Risk
18080,162519807,695.0,,0,4,/hirokisaitoreason/multi-class-prediction-of-obesity-risk-eda,Multi-Class Prediction of Obesity Risk
18081,163579922,963.0,,4,20,/conradkleykamp/s4e2-obesity-classification-w-lightgbm,Multi-Class Prediction of Obesity Risk
18082,161332366,564.0,,0,11,/atharva0577/s4e2-voting-neuralnetwork-catboost-optuna,Multi-Class Prediction of Obesity Risk
18083,164918367,923.0,,2,16,/jeremyhaakenson/obesity-fe-and-random-forest,Multi-Class Prediction of Obesity Risk
18084,161783609,721.0,0.9129335260115607,0,9,/gamablobyt/obesity-risk-classification,Multi-Class Prediction of Obesity Risk
18085,163109870,2050.0,,0,3,/raaggeesingh/ps4e2-a-beginners-guide-to-the-competition,Multi-Class Prediction of Obesity Risk
18086,162892170,1718.0,0.907514450867052,0,8,/claudiojnior/eda-xgbclassifier-model-fine-tune,Multi-Class Prediction of Obesity Risk
18087,163417015,1526.0,,0,8,/alhsan/obesity-risk-prediction-accuracy-0-91,Multi-Class Prediction of Obesity Risk
18088,164261833,1494.0,0.9114884393063584,4,13,/loycelorenzo/obesity-risk-fast-ai-xgboost-smote,Multi-Class Prediction of Obesity Risk
18089,163526582,1212.0,,3,10,/rudragujarathi/comp-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18090,163768978,624.0,,0,3,/brysonje/s2e4-lightboost-0-91221,Multi-Class Prediction of Obesity Risk
18091,161289981,1394.0,0.9067919075144508,0,9,/ayhampar/multi-class-catboostclassifier,Multi-Class Prediction of Obesity Risk
18092,164855698,2038.0,0.891257225433526,0,3,/jeosoyoung/obesity-risk,Multi-Class Prediction of Obesity Risk
18093,162968959,328.0,,0,4,/suranjandas1990/playground-s4e2-eda,Multi-Class Prediction of Obesity Risk
18094,165362269,1740.0,,1,16,/jweon96/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18095,162953330,1176.0,,0,10,/pritishpriyam4/simple-91-obesity-prediction-xgbm,Multi-Class Prediction of Obesity Risk
18096,161634055,1464.0,,0,16,/vanshbatra10/easy-solution-ensemble-xgb-lgbm-optuna-91-25,Multi-Class Prediction of Obesity Risk
18097,163846581,1470.0,,0,8,/jayantdon/easy-solution-ensemble-xgb-lgbm-optuna-91-25,Multi-Class Prediction of Obesity Risk
18098,161689216,1471.0,0.91257225433526,0,13,/kunal025/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18099,161689216,1471.0,0.91257225433526,0,13,/kunal025/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18100,161689232,1472.0,0.91257225433526,0,19,/mayankgupta9/notebook6e9b2c8dfe,Multi-Class Prediction of Obesity Risk
18101,161689495,1473.0,0.91257225433526,1,11,/iyasha/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18102,161702235,1225.0,0.9107658959537572,0,19,/anibansal/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18103,161808881,1646.0,,2,11,/aayushsharmacse/sklearn-ml-magic,Multi-Class Prediction of Obesity Risk
18104,161568751,396.0,0.8713872832369942,0,18,/iqmansingh/obesity-risk-simple-dl-approach,Multi-Class Prediction of Obesity Risk
18105,162134998,1359.0,,0,5,/sachinbulchandani/multiclassclassification,Multi-Class Prediction of Obesity Risk
18106,163120991,777.0,0.91257225433526,0,0,/valeriiabiruk/k-fold-training-and-ensemble,Multi-Class Prediction of Obesity Risk
18107,162338705,2099.0,0.91257225433526,0,0,/santusrk/initial-stage-xgboost-0-911,Multi-Class Prediction of Obesity Risk
18108,162338705,2099.0,0.91257225433526,0,0,/santusrk/initial-stage-xgboost-0-911,Multi-Class Prediction of Obesity Risk
18109,162338705,2099.0,0.91257225433526,0,0,/santusrk/initial-stage-xgboost-0-911,Multi-Class Prediction of Obesity Risk
18110,162338705,2099.0,0.91257225433526,0,0,/santusrk/initial-stage-xgboost-0-911,Multi-Class Prediction of Obesity Risk
18111,163897295,1592.0,,0,3,/aadityavardhan/randomforestextratreescatboostxgboostlgbm,Multi-Class Prediction of Obesity Risk
18112,163294711,1484.0,0.91257225433526,0,20,/himanshu230/notebookbd902c91ac,Multi-Class Prediction of Obesity Risk
18113,163472239,1340.0,0.911849710982659,0,8,/nickfecondo/s4e02-obesity-risk,Multi-Class Prediction of Obesity Risk
18114,165025139,1255.0,,2,9,/blade007/not-so-good-obesity-prediction,Multi-Class Prediction of Obesity Risk
18115,161281897,1795.0,,0,29,/chetalipushkarna/xgbclassifier-score-0-91,Multi-Class Prediction of Obesity Risk
18116,161399775,2063.0,,0,6,/juanpablolagos/obesity-risk-lgbmclassifier,Multi-Class Prediction of Obesity Risk
18117,161811591,1756.0,0.9122109826589596,0,3,/ahmetkoseoglu/ps4e2-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18118,161811591,1756.0,0.9122109826589596,0,3,/ahmetkoseoglu/ps4e2-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18119,161393708,1542.0,,2,7,/arjunjanamatti/basic-model,Multi-Class Prediction of Obesity Risk
18120,164324976,1409.0,0.8966763005780347,2,13,/raykdoyle/obesity-risk-kaggle-8,Multi-Class Prediction of Obesity Risk
18121,162401411,1799.0,0.9122109826589596,0,10,/chanchal24/obesity-risk-xgbclassifier,Multi-Class Prediction of Obesity Risk
18122,162401411,1799.0,0.9122109826589596,0,10,/chanchal24/obesity-risk-xgbclassifier,Multi-Class Prediction of Obesity Risk
18123,162401411,1799.0,0.9122109826589596,0,10,/chanchal24/obesity-risk-xgbclassifier,Multi-Class Prediction of Obesity Risk
18124,162463968,1800.0,0.9122109826589596,0,17,/shivamvermathapar/obesity-risk-beginners-guide,Multi-Class Prediction of Obesity Risk
18125,162526302,1802.0,0.9122109826589596,0,11,/jindal05/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18126,162536045,1803.0,0.9122109826589596,0,18,/akshitaakshita/multiclass-obesity,Multi-Class Prediction of Obesity Risk
18127,162643238,1267.0,0.910043352601156,0,10,/ryzhokhina/multiclass-prediction-obesity,Multi-Class Prediction of Obesity Risk
18128,162624599,1804.0,0.9122109826589596,0,10,/dubeyarpit/obesityrisk,Multi-Class Prediction of Obesity Risk
18129,165147254,346.0,,0,1,/zhichaocheng/obesity-risk-xgboost,Multi-Class Prediction of Obesity Risk
18130,164592492,1670.0,,0,6,/yashsharma1216/obesity-multiclass-prediction-accuracy-91,Multi-Class Prediction of Obesity Risk
18131,165178185,1533.0,0.9071531791907514,3,9,/anopsy/obesity-eda-and-ensemble,Multi-Class Prediction of Obesity Risk
18132,161459075,1198.0,,0,2,/ivodzalbs/91-2-obesity-risk-with-bmi-feature-added,Multi-Class Prediction of Obesity Risk
18133,162339958,1230.0,,7,33,/brmil07/multi-class-prediction,Multi-Class Prediction of Obesity Risk
18134,162663621,430.0,0.9089595375722545,0,8,/o2ka03/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18135,162971751,1548.0,0.911849710982659,1,22,/palak98039/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18136,163243518,644.0,0.9057080924855492,0,0,/lanceearldaxar/obesity-risk-first-attempt,Multi-Class Prediction of Obesity Risk
18137,163243518,644.0,0.9042630057803468,0,0,/lanceearldaxar/obesity-risk-first-attempt,Multi-Class Prediction of Obesity Risk
18138,163243518,644.0,0.9020953757225434,0,0,/lanceearldaxar/obesity-risk-first-attempt,Multi-Class Prediction of Obesity Risk
18139,163205243,1187.0,0.911849710982659,0,1,/lyastanriverd/obesity-risk,Multi-Class Prediction of Obesity Risk
18140,164438285,367.0,,0,9,/rushil999/good-game,Multi-Class Prediction of Obesity Risk
18141,163599197,1530.0,0.911849710982659,0,0,/tooba10/obesity-prediction,Multi-Class Prediction of Obesity Risk
18142,163772683,1921.0,,0,0,/sundayabraham/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18143,164894802,1251.0,0.911849710982659,0,6,/ahtabekdas/obesity-risk-multi-class-prediction-eng-tr,Multi-Class Prediction of Obesity Risk
18144,163039914,1552.0,0.911849710982659,3,22,/kushagrekaushik/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18145,164830016,541.0,0.9067919075144508,0,2,/vladislavsultanov/sultanov-multi-classifier-with-body-mass-index,Multi-Class Prediction of Obesity Risk
18146,164760981,1489.0,,0,7,/devavratpatil/multi-class-obesity-risk-eda-xgb-lgbm,Multi-Class Prediction of Obesity Risk
18147,162756698,1546.0,0.9096820809248556,0,11,/anmol111pal/obesity-risk-prediction-competition,Multi-Class Prediction of Obesity Risk
18148,161237508,633.0,0.8966763005780347,2,13,/pluspin/ps-s4-e02-baseline-catboost,Multi-Class Prediction of Obesity Risk
18149,161952261,1610.0,,0,2,/sayem01k/multiclass-prediction-using-lightgbm,Multi-Class Prediction of Obesity Risk
18150,163387233,1745.0,,0,4,/davidantonioteixeira/obesidade-91-comparing-classifiers,Multi-Class Prediction of Obesity Risk
18151,162532606,775.0,0.9107658959537572,0,2,/susanketsarkar/multi-class-obesity-prediction-beginner-notebook,Multi-Class Prediction of Obesity Risk
18152,164166996,489.0,0.9114884393063584,0,2,/zbeyde/obesity-prediction-xgboost,Multi-Class Prediction of Obesity Risk
18153,164166996,489.0,0.9114884393063584,0,2,/zbeyde/obesity-prediction-xgboost,Multi-Class Prediction of Obesity Risk
18154,164552068,1347.0,0.9114884393063584,0,2,/aayushsin7a/ml-obesity-or-cvd-risk,Multi-Class Prediction of Obesity Risk
18155,162266254,1581.0,0.8970375722543352,16,65,/akhiljethwa/playground-s4e2-eda-modeling-91-0,Multi-Class Prediction of Obesity Risk
18156,161554151,376.0,,0,10,/mathewshuvarikov/multi-class-prediction-of-obesity-risk-lightautoml,Multi-Class Prediction of Obesity Risk
18157,161524857,1707.0,0.911127167630058,0,12,/nrng19/notebook7876a9278d,Multi-Class Prediction of Obesity Risk
18158,161680518,738.0,0.911127167630058,0,7,/laparicio/obesity-risk-multi-class,Multi-Class Prediction of Obesity Risk
18159,162272859,1955.0,,0,7,/nitishviraktamath/obesity-cvd-risk-val-accuracy-0-9139,Multi-Class Prediction of Obesity Risk
18160,162289595,398.0,0.7937138728323699,0,3,/samikohvakka/using-domain-knowledge-to-obtain-a-simple-benchmar,Multi-Class Prediction of Obesity Risk
18161,162526436,269.0,0.9104046242774566,0,24,/sakshigoyal001/obesity-risk-competition,Multi-Class Prediction of Obesity Risk
18162,164735835,1904.0,,0,6,/eastonlarson/kaggle-project-8-easton-larson,Multi-Class Prediction of Obesity Risk
18163,163626524,1593.0,,0,1,/crisbebop/obesity-class-lgbm-ovr-vs-mult,Multi-Class Prediction of Obesity Risk
18164,161972993,1167.0,0.8941473988439307,0,0,/maxserra/multi-class-obesity-sklearn,Multi-Class Prediction of Obesity Risk
18165,164105564,1271.0,0.8591040462427746,0,0,/luigibungarodbx/multi-class-prediction-of-obesity-risk-sequential,Multi-Class Prediction of Obesity Risk
18166,164364436,1943.0,,0,0,/kimyoungki/kaggle-project,Multi-Class Prediction of Obesity Risk
18167,164908879,734.0,,0,1,/dhariniselvasekar/comp1-fs5142-dh,Multi-Class Prediction of Obesity Risk
18168,161508350,1673.0,,4,23,/arnavsharma45/91-s4e2-eda-ensembled-lightgbm-catboost-xgb,Multi-Class Prediction of Obesity Risk
18169,163762499,2036.0,0.9082369942196532,0,0,/robertorenna/obesity-risk-automl-approach,Multi-Class Prediction of Obesity Risk
18170,161772940,1755.0,,0,0,/cuneytharp83/pycaret-analyser-file,Multi-Class Prediction of Obesity Risk
18171,161776081,1730.0,,0,3,/siangwunsiao/obestity,Multi-Class Prediction of Obesity Risk
18172,161374249,1852.0,,0,7,/carlosalvro/obesity-risk-multiclass-analisys,Multi-Class Prediction of Obesity Risk
18173,164522546,2058.0,,0,7,/mahendra301/obesity-risk-prediction-light-gbm-with-91,Multi-Class Prediction of Obesity Risk
18174,162671481,1522.0,0.9107658959537572,0,7,/elireckless/xgboost-and-optuna,Multi-Class Prediction of Obesity Risk
18175,162080050,2240.0,0.8728323699421965,0,0,/carljvh/obesity-risk-baseline-fastai-deep-learning,Multi-Class Prediction of Obesity Risk
18176,163062094,880.0,0.9078757225433526,0,0,/annelimmj/obesity-risk-prediction-xgb-accuracy-0-906,Multi-Class Prediction of Obesity Risk
18177,163305646,420.0,0.9046242774566474,0,8,/vibhorejain1/ps4e2-0-91-eda-xgboost,Multi-Class Prediction of Obesity Risk
18178,163693595,2282.0,0.9107658959537572,4,13,/tonychirilus/eda-with-tensorflow-and-simple-lgbm,Multi-Class Prediction of Obesity Risk
18179,163670861,1708.0,0.9053468208092486,0,3,/herczeggyrgy/xgboost-class,Multi-Class Prediction of Obesity Risk
18180,163867759,369.0,0.9107658959537572,2,3,/cyrileremin/prediction-for-obesity-risk-xgboost-score-0-919,Multi-Class Prediction of Obesity Risk
18181,163966731,1856.0,0.9107658959537572,0,6,/shivanshtuteja/0-91-multiclass-prediction-using-xgbclassifier,Multi-Class Prediction of Obesity Risk
18182,165346588,813.0,,0,3,/ksh000325/obesity-prediction-with-xgboost-91-accuracy,Multi-Class Prediction of Obesity Risk
18183,164500407,1686.0,,1,22,/alexeyk12/the-fat-catboost,Multi-Class Prediction of Obesity Risk
18184,161263852,1781.0,0.9104046242774566,0,7,/saimondahal/pg-s4e1-eda-vote-xg-lgbm-catboost,Multi-Class Prediction of Obesity Risk
18185,161815261,1861.0,,0,4,/farid75/multi-class-prediction-of-obesity-risk-with-xgb,Multi-Class Prediction of Obesity Risk
18186,162296374,345.0,0.9042630057803468,0,7,/vassyesboy/eda-model-selection-ensemble,Multi-Class Prediction of Obesity Risk
18187,162468606,560.0,0.9104046242774566,0,16,,Multi-Class Prediction of Obesity Risk
18188,163998840,1479.0,,0,2,/jpedrou/prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18189,162956029,1185.0,,0,2,/energyshuma/91-lgbm-simple-kfold-baseline,Multi-Class Prediction of Obesity Risk
18190,163869883,1486.0,0.9104046242774566,0,6,/rajsahu2004/xgbclassifier-hybrid-randomizedsearch-gridsearchcv,Multi-Class Prediction of Obesity Risk
18191,164121986,1684.0,,0,4,/zephyrus1/prediction-of-obesityrisk-compe-xgb-onevrest-lgbm,Multi-Class Prediction of Obesity Risk
18192,162145101,1620.0,,0,6,/samsonoo/obesity-prediction-91,Multi-Class Prediction of Obesity Risk
18193,162812515,1380.0,,0,6,/joyygoswami/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18194,163640469,1998.0,0.910043352601156,0,1,/scottpitcher/obesity-prediction,Multi-Class Prediction of Obesity Risk
18195,164157766,2332.0,0.8970375722543352,2,3,/junaidullhassan/obesity-risk-prediction-gradientboosting-xgboost,Multi-Class Prediction of Obesity Risk
18196,164923797,1702.0,,0,3,/cascarino/eda-xgboost-optuna-ipynb,Multi-Class Prediction of Obesity Risk
18197,161307106,1706.0,,0,9,/karthikgangula/eda-on-obesity-factors,Multi-Class Prediction of Obesity Risk
18198,161827846,2186.0,0.9060693641618496,5,16,/simple11/predict-obesity-risk,Multi-Class Prediction of Obesity Risk
18199,162591908,1966.0,0.9078757225433526,3,21,/nikhilchadha1537/obesity-risk-notebook,Multi-Class Prediction of Obesity Risk
18200,162075149,1933.0,0.9071531791907514,0,14,/arshjot123/ps-s4e2-xgboost-obestiy-risk,Multi-Class Prediction of Obesity Risk
18201,161339535,1825.0,0.9035404624277455,0,11,/joaquinemsarg/simple-look-into-eda-t-sne-catboost,Multi-Class Prediction of Obesity Risk
18202,161557811,905.0,0.8973988439306358,0,11,/pratyushojha12/nobeyesdad-multiclass-classification,Multi-Class Prediction of Obesity Risk
18203,161557811,905.0,0.8973988439306358,0,11,/pratyushojha12/nobeyesdad-multiclass-classification,Multi-Class Prediction of Obesity Risk
18204,162403683,2250.0,,0,14,/arushibashambu/multiclass-obesity-risk,Multi-Class Prediction of Obesity Risk
18205,162611772,2251.0,,0,5,/romeodavid/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18206,162756788,1363.0,0.9096820809248556,0,8,/ogulcancck/obesity-risk-pred-eda-feature-eng-model,Multi-Class Prediction of Obesity Risk
18207,164191237,626.0,0.9096820809248556,0,1,/rucheiitr/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18208,164835593,1076.0,,0,0,/amyjieliu/multi-class-pred-of-obesity-risk-rf-xgboost,Multi-Class Prediction of Obesity Risk
18209,161840885,1887.0,,0,9,/nnjjpp/play-4-2-eda-baseline-model,Multi-Class Prediction of Obesity Risk
18210,161568047,1400.0,0.909320809248555,0,14,/aarushikamboj/sol-3,Multi-Class Prediction of Obesity Risk
18211,161787305,1261.0,0.9089595375722545,0,2,/ronitakhariya/eda-finetuning-0-909,Multi-Class Prediction of Obesity Risk
18212,162641168,1773.0,0.909320809248555,3,6,/ayaabdalsalam/analysis-of-obesityrisks,Multi-Class Prediction of Obesity Risk
18213,162641168,1773.0,0.909320809248555,3,6,/ayaabdalsalam/analysis-of-obesityrisks,Multi-Class Prediction of Obesity Risk
18214,162883013,1408.0,0.909320809248555,0,13,/chaitanyasood1/obesity,Multi-Class Prediction of Obesity Risk
18215,162883013,1408.0,0.909320809248555,0,13,/chaitanyasood1/obesity,Multi-Class Prediction of Obesity Risk
18216,163958102,1536.0,,1,3,/syedjaffri/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18217,161515108,2083.0,,0,8,/lucasdataartist/eda-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18218,163758264,1153.0,,0,2,/shylobohdan/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18219,162377856,593.0,0.9085982658959536,0,2,/johntoniutti/obesity-risk-competition,Multi-Class Prediction of Obesity Risk
18220,163492923,1122.0,0.8988439306358381,0,2,/pperna/xgboost-gpu-optuna-with-pruning,Multi-Class Prediction of Obesity Risk
18221,161560016,2039.0,,2,19,/kashish50/obesity50-optuna-90-8,Multi-Class Prediction of Obesity Risk
18222,162245768,1444.0,0.9085982658959536,3,9,/natsu18/pgs-s4e2-lgboost-and-adversarial-validation,Multi-Class Prediction of Obesity Risk
18223,162714135,1232.0,,0,0,/juanjosemuozpanos/obesity-risk-eda-baseline-models,Multi-Class Prediction of Obesity Risk
18224,164817395,1145.0,0.9042630057803468,0,6,/adrienriaux/histgradientboosting-with-optuna,Multi-Class Prediction of Obesity Risk
18225,164489171,1639.0,0.8992052023121387,0,2,/aryan210/s4e2-n2,Multi-Class Prediction of Obesity Risk
18226,164914442,2242.0,0.0,0,4,/santiago123678/notebook9ef069b633,Multi-Class Prediction of Obesity Risk
18227,161641015,1560.0,0.9053468208092486,0,8,/docxian/ps-s4-e02-obesity-risk-multiclass,Multi-Class Prediction of Obesity Risk
18228,161389789,2028.0,0.9082369942196532,1,18,,Multi-Class Prediction of Obesity Risk
18229,162647237,2029.0,,0,17,/ramjaslangdi/obesity-risk,Multi-Class Prediction of Obesity Risk
18230,161957107,1177.0,,0,1,/sachinsushilsingh/obesity-risk-prediction-most-basic-notebook,Multi-Class Prediction of Obesity Risk
18231,163417572,2390.0,,0,32,/akshita0560/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18232,162886492,1499.0,,0,9,/mohamedakkadir/90-accuracy-with-voting-classifier,Multi-Class Prediction of Obesity Risk
18233,163894984,1733.0,0.828757225433526,0,8,/andrewbremner/weightrisk-s4e2-sklearn-models-vs-pytorch,Multi-Class Prediction of Obesity Risk
18234,163211570,2555.0,,0,3,/karamalhanatleh/prediction-of-obesity-risk-98,Multi-Class Prediction of Obesity Risk
18235,162686582,2016.0,,4,10,/naarku30/obesity-risk-eda-scaling-model-build,Multi-Class Prediction of Obesity Risk
18236,164784334,1217.0,0.9002890173410405,0,5,/ginakkkk/baseline-scikit-learn-pipeline,Multi-Class Prediction of Obesity Risk
18237,161616798,1950.0,0.9078757225433526,2,12,/kaushaltiwari/preprocessing-training-an-xgboost-model,Multi-Class Prediction of Obesity Risk
18238,161851073,1952.0,,0,8,/akokoo/s4e02-data-xgboost-eda,Multi-Class Prediction of Obesity Risk
18239,164559946,839.0,0.9064306358381504,0,10,/toshimelonhead/tps-4-2-obesity-cvd,Multi-Class Prediction of Obesity Risk
18240,162174816,1772.0,0.9078757225433526,3,28,/samarjeetsinghgandhi/xgboost-in-obesity-risk-0-907-accuracy,Multi-Class Prediction of Obesity Risk
18241,162174146,1006.0,0.8688583815028902,0,5,/habilamar/simple-logistic-regression-s4e2-playground,Multi-Class Prediction of Obesity Risk
18242,162545129,1491.0,0.907514450867052,0,12,/xietaowang/s4e02-basic-baseline-eda,Multi-Class Prediction of Obesity Risk
18243,163937773,1381.0,,0,7,/ashwinmali/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18244,163099896,2146.0,0.8966763005780347,2,14,/sajjadhajian/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18245,163695215,1529.0,,0,5,/fabrciomacena/s4e2-obesity-risk-eda-lightgbm-optuna,Multi-Class Prediction of Obesity Risk
18246,163905896,1855.0,,4,2,/jiaojay28/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18247,163930141,1940.0,0.9078757225433526,0,0,/glenlee1/notebookd0564f5b83,Multi-Class Prediction of Obesity Risk
18248,164302147,1611.0,,0,5,/ustcer1984/obesity-eda-cluster-playground-s4e2,Multi-Class Prediction of Obesity Risk
18249,164741192,1959.0,,0,3,/baiqi301/competition,Multi-Class Prediction of Obesity Risk
18250,161480385,1493.0,0.8963150289017341,1,7,/strawhatdragon/playground-series-s4e2-eda-xgboost,Multi-Class Prediction of Obesity Risk
18251,161763358,1874.0,0.907514450867052,2,17,/grandmastershaurya/multiclass-obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18252,161298000,1934.0,0.8417630057803468,0,5,/naiku007/multi-class-feb24-basic-model-no-fe,Multi-Class Prediction of Obesity Risk
18253,163864799,2214.0,,0,2,/yogeshbarai/obesity-rfc,Multi-Class Prediction of Obesity Risk
18254,163645814,1011.0,0.9060693641618496,0,0,/kalpanatiwari30/multiclass-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18255,164490682,1779.0,0.900650289017341,0,9,/szymnq/multi-class-prediction-of-obesity-risk-ensemble,Multi-Class Prediction of Obesity Risk
18256,161491760,1281.0,0.8710260115606936,0,6,/renhuang8/multi-class-prediction-of-obesity-risk-mlp,Multi-Class Prediction of Obesity Risk
18257,162321158,1849.0,0.8999277456647399,0,4,/yazeedalsahouri03/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18258,162375378,1096.0,0.9071531791907514,0,9,/raghavdargan/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18259,163057004,1805.0,0.9053468208092486,0,0,/nguyenbnguyen/obesity-risk-prediction-with-sklearn,Multi-Class Prediction of Obesity Risk
18260,163419767,697.0,0.9071531791907514,0,4,/avikal30/mcp-for-obesity-risk,Multi-Class Prediction of Obesity Risk
18261,163442389,1365.0,0.9071531791907514,0,0,/hyrintalion/prediction-of-obesity-risk-lgbm,Multi-Class Prediction of Obesity Risk
18262,163760497,2254.0,0.9071531791907514,3,8,/mostafagamal777/playground-obesity-risk-rf-xgb-lgbm-ensemble,Multi-Class Prediction of Obesity Risk
18263,164882423,2260.0,0.9071531791907514,0,0,/parthdande/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18264,161245953,2085.0,,0,10,/carloscll/insights-s4e2-eda,Multi-Class Prediction of Obesity Risk
18265,164462732,2268.0,,0,7,/nobun123/data-cleaning-transformation-eda-xgboost,Multi-Class Prediction of Obesity Risk
18266,162423528,1817.0,0.9067919075144508,0,1,/sanyamgoyal401/obesity-classification-using-xgboost,Multi-Class Prediction of Obesity Risk
18267,162967689,2200.0,,0,6,/kaushalsurana/xgboost,Multi-Class Prediction of Obesity Risk
18268,163704718,2112.0,0.904985549132948,1,12,/vayanshgarg/playground-obesity-risk-rf-xgb-lgbm-ensemble,Multi-Class Prediction of Obesity Risk
18269,163816689,1911.0,,1,5,/l3llff/ps-s4-eda-catboost,Multi-Class Prediction of Obesity Risk
18270,163836101,1927.0,,1,2,/ashiksrinivas32/eda-xgboost,Multi-Class Prediction of Obesity Risk
18271,161708480,2090.0,,0,13,/kuboiyusuke/ps4e2-default-feature-rf-xgb-lgbm,Multi-Class Prediction of Obesity Risk
18272,161562497,2176.0,0.9064306358381504,2,16,/ananyagupta184/notebook333a5b9c14,Multi-Class Prediction of Obesity Risk
18273,161696349,1823.0,0.8916184971098265,1,9,/umar47/s4e2-obesity-risk-baseline-eda-model-evaluation,Multi-Class Prediction of Obesity Risk
18274,162391030,1181.0,0.9064306358381504,3,31,/chiragmohangupta/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18275,162448673,2220.0,,0,3,/vaibhavbawej07/multi-class-prediction-obesity-90-accuracy,Multi-Class Prediction of Obesity Risk
18276,162215242,2013.0,,0,15,/harbandanakaur/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18277,162713558,2014.0,0.9064306358381504,1,14,/japleenkaurbedi/obesity-102103204,Multi-Class Prediction of Obesity Risk
18278,164079592,2171.0,0.9064306358381504,2,11,/yeonseokcho/obesity-multi-class-prediction,Multi-Class Prediction of Obesity Risk
18279,163331985,2246.0,,0,1,/indranil98/mlp-mentoring-sessions-indranil,Multi-Class Prediction of Obesity Risk
18280,161454114,1146.0,0.8858381502890174,2,25,/abhinandansharma19/multi-class-prediction-of-obesity-risk-eda-0-90,Multi-Class Prediction of Obesity Risk
18281,164015016,1939.0,,0,0,/j2hoon85/baseline-scikit-learn-pipeline-sample-code,Multi-Class Prediction of Obesity Risk
18282,163930169,1941.0,0.9035404624277455,0,0,/kjk6336/ml-class1,Multi-Class Prediction of Obesity Risk
18283,163930169,1941.0,0.9035404624277455,0,0,/kjk6336/ml-class1,Multi-Class Prediction of Obesity Risk
18284,164485984,1942.0,0.8807803468208093,0,1,/kongalmengi/junho-s-notebook,Multi-Class Prediction of Obesity Risk
18285,163930161,1944.0,0.8977601156069365,0,0,/anbyeol/ml-obesity-risk,Multi-Class Prediction of Obesity Risk
18286,163548611,1845.0,,1,12,/aldrinlambon/15-insights-on-obesity-risk,Multi-Class Prediction of Obesity Risk
18287,161379194,1502.0,,2,12,/packinman/ps-s4e2-simple-eda,Multi-Class Prediction of Obesity Risk
18288,162623341,2294.0,0.9057080924855492,0,3,/rsesha/pss4e2-iterativedoubleclassifier-90-57-score,Multi-Class Prediction of Obesity Risk
18289,163772737,2103.0,0.9057080924855492,0,0,/alvinsoewin/obesity-risk-prediction-submission,Multi-Class Prediction of Obesity Risk
18290,163770513,2104.0,0.9057080924855492,0,0,/cy9899/homework-1-yi-chen,Multi-Class Prediction of Obesity Risk
18291,164119623,2451.0,0.9057080924855492,0,0,/nisha272004gmailcom/notebookdfff52f3b6,Multi-Class Prediction of Obesity Risk
18292,162409605,1739.0,,0,5,/ttskkb/ps4e2-a-beginners-notebook,Multi-Class Prediction of Obesity Risk
18293,164840792,2425.0,,0,0,/jayrdixit/obesity-competition,Multi-Class Prediction of Obesity Risk
18294,161526746,1675.0,0.9053468208092486,0,4,/aadhafun/pss4e2-eda-xgboost-optuna,Multi-Class Prediction of Obesity Risk
18295,161779560,1517.0,0.9053468208092486,4,19,/bhavyabhalla2701/multi-class-prediction-of-obesity-risk-bhavya,Multi-Class Prediction of Obesity Risk
18296,161819438,2154.0,0.8052745664739884,0,20,/nitishjolly/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18297,161956964,1963.0,,0,6,/pixelshooter/obesity-risk-eda,Multi-Class Prediction of Obesity Risk
18298,161910924,2155.0,0.9053468208092486,1,14,/tanejanikhil/notebookd06b22b3bf,Multi-Class Prediction of Obesity Risk
18299,162079889,2156.0,0.9053468208092486,0,15,/tarndeepsingh16/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18300,162739431,2189.0,,0,1,/mrrajsingh/multiple-implementations-of-obesity-disease-data,Multi-Class Prediction of Obesity Risk
18301,163261320,2307.0,0.9053468208092486,0,0,/gedewasistha/predictive-modeling-for-multiclass-obesity-risk,Multi-Class Prediction of Obesity Risk
18302,164647025,2315.0,0.8948699421965318,1,9,/rrishi23/beginner-eda-catboost-optuna-90-53,Multi-Class Prediction of Obesity Risk
18303,165153238,1659.0,0.9053468208092486,0,6,/jsonali2003/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18304,162069827,2285.0,0.904985549132948,0,0,/rainwashed/obesity-s4e2-notebook-r2,Multi-Class Prediction of Obesity Risk
18305,162975091,2271.0,0.903179190751445,0,1,/ziyadj/eda-lightgbm-90-accuracy,Multi-Class Prediction of Obesity Risk
18306,163487582,1922.0,,0,6,/mdtanviranjum/obesity-prediction-90-accuracy,Multi-Class Prediction of Obesity Risk
18307,164139839,2007.0,,0,3,/akumardev/obesity-risk-multi-classification-models,Multi-Class Prediction of Obesity Risk
18308,164207386,2810.0,0.904985549132948,0,2,/priyansh55/notebook8a92c79753,Multi-Class Prediction of Obesity Risk
18309,164488151,2811.0,0.904985549132948,0,3,/jaskiratsingh2003/obesity-risk,Multi-Class Prediction of Obesity Risk
18310,164407525,2081.0,0.9039017341040464,0,9,/muratbakirr/viz-i-lgbm-optuna-i-obesity-risk,Multi-Class Prediction of Obesity Risk
18311,165305374,2074.0,0.9085982658959536,0,4,/scarfx/prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18312,161367779,1727.0,,0,10,/ubaydullohasatullaev/random-forest-classifier-obesity-risk,Multi-Class Prediction of Obesity Risk
18313,161238968,1728.0,0.884393063583815,2,18,/ubaydulloasatullaev/obesity-risk-random-forest-0-88439,Multi-Class Prediction of Obesity Risk
18314,163308105,2120.0,0.9020953757225434,2,11,/hardik201003/multi-class-classification-obesity-risk,Multi-Class Prediction of Obesity Risk
18315,163216094,2306.0,0.9046242774566474,0,4,/devanshagarwal9/prediction-of-obesity,Multi-Class Prediction of Obesity Risk
18316,163971085,2499.0,,0,1,/mohamedabder/01-eda,Multi-Class Prediction of Obesity Risk
18317,164375320,2360.0,,0,8,/sardorwwe/multi-class-prediction-of-obesity-risk-pred,Multi-Class Prediction of Obesity Risk
18318,164616366,1925.0,0.9046242774566474,1,5,/sourenakhanzadeh/obesity-90-randomforest,Multi-Class Prediction of Obesity Risk
18319,162374606,2261.0,,5,66,/alnourabdalrahman9/prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18320,161328103,2084.0,,0,13,/ridwanakmal/effortless-baseline-a-one-line-code,Multi-Class Prediction of Obesity Risk
18321,161950639,2453.0,,2,6,/harharharhar/4-02-obesity-6-0-xgboost,Multi-Class Prediction of Obesity Risk
18322,161843672,2108.0,0.9042630057803468,1,14,/adityagoel2205/multiclass-prediction-obesity-lgbm,Multi-Class Prediction of Obesity Risk
18323,163615305,2121.0,0.9042630057803468,0,0,/lucasascarvalho/obesity-risk-voting-classifiers-and-massive-eda,Multi-Class Prediction of Obesity Risk
18324,164888116,2745.0,0.9042630057803468,0,4,/rizwanahmedabbasi/obesity-risk-using-xgbooster,Multi-Class Prediction of Obesity Risk
18325,163018168,2228.0,0.9039017341040464,2,10,/chalseo/catboost-optuna-obesity-risk-multiclassification,Multi-Class Prediction of Obesity Risk
18326,165047117,2528.0,,0,4,/natasha23/multi-classification-obesity-risk-python,Multi-Class Prediction of Obesity Risk
18327,163256165,2416.0,0.8999277456647399,1,12,/fanhuaiyuan/2024-2-12,Multi-Class Prediction of Obesity Risk
18328,162201319,1889.0,0.8992052023121387,0,7,/moyamoya/ps4e2-catboost-optuna,Multi-Class Prediction of Obesity Risk
18329,162173909,2331.0,,0,3,/jameslindseyjones/obesityrisk-xgboost,Multi-Class Prediction of Obesity Risk
18330,164620477,1989.0,0.903179190751445,0,1,/alexisvannaire/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18331,161511098,2624.0,0.9028179190751444,2,17,,Multi-Class Prediction of Obesity Risk
18332,161511098,2624.0,0.9028179190751444,2,17,,Multi-Class Prediction of Obesity Risk
18333,163229367,2012.0,0.901372832369942,0,1,/saroharutyunyan/notebook26e4328f51,Multi-Class Prediction of Obesity Risk
18334,162592097,1903.0,0.9028179190751444,0,11,/pranav28/obesity,Multi-Class Prediction of Obesity Risk
18335,164550353,2493.0,0.8619942196531792,0,5,/klyushnik/kears-multi-class-task,Multi-Class Prediction of Obesity Risk
18336,162370716,2175.0,,0,12,/kkamal2003/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18337,162526305,2041.0,0.902456647398844,0,0,/sergeypolivin/obesity-risk-prediction-using-gb-models,Multi-Class Prediction of Obesity Risk
18338,163015911,1937.0,0.902456647398844,0,2,/mohammedabdeldayem/multi-class-prediction-of-obesity-risk-challenge,Multi-Class Prediction of Obesity Risk
18339,162990427,2554.0,,0,9,/kartikkumaria/obese-classification-using-pycaret,Multi-Class Prediction of Obesity Risk
18340,163330657,1968.0,,0,9,/adhyanbaluja/notebook618a7e7e07,Multi-Class Prediction of Obesity Risk
18341,163665834,2517.0,,0,5,/youssefghaoui/gnrl-pred-93-obesity-97-overweight-89-90,Multi-Class Prediction of Obesity Risk
18342,163761955,1985.0,0.902456647398844,0,0,/mvabhishek/obesity-risk-prediction-using-classification,Multi-Class Prediction of Obesity Risk
18343,163236525,2488.0,0.8992052023121387,4,18,/amulyat29/multi-class-prediction-obesity-risk,Multi-Class Prediction of Obesity Risk
18344,162199507,2496.0,,0,7,/mirfayzirgashevdku/playground-series-obesity-risk-s4-e2-90-acc,Multi-Class Prediction of Obesity Risk
18345,164632338,2410.0,0.7763728323699421,0,6,/madao13/multiclasspredictionofobesityrisk-lightgbm,Multi-Class Prediction of Obesity Risk
18346,162389098,2269.0,0.5202312138728323,0,6,/riteshkushwaha08/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18347,162284833,2357.0,0.9020953757225434,3,19,/slythe/r-programming-getting-started-on-competitions,Multi-Class Prediction of Obesity Risk
18348,161481731,2197.0,0.9017341040462428,0,8,/haseebwar07/prediction-of-obesity-risk-gb-90,Multi-Class Prediction of Obesity Risk
18349,161957738,2389.0,,1,8,/palliplease/obesity-prediction-using-xgboost-90-1-accuracy,Multi-Class Prediction of Obesity Risk
18350,162007533,2210.0,0.9017341040462428,0,5,/akashmishra091/lgbm-90-173-easily-understandable,Multi-Class Prediction of Obesity Risk
18351,163770023,2204.0,0.9017341040462428,2,7,/harrybeasley/harry-beasley,Multi-Class Prediction of Obesity Risk
18352,166115366,2476.0,0.8731936416184971,2,10,/cristhianccalah/multi-class-prediction-of-obesity-risk-svm,Multi-Class Prediction of Obesity Risk
18353,164916988,2494.0,0.9017341040462428,0,10,/nazimcherpanov/obesity-risk-prediction-for-beginners,Multi-Class Prediction of Obesity Risk
18354,161441729,2618.0,0.901372832369942,2,24,/piyush1234ggfuvi/prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18355,161762679,2405.0,0.901372832369942,0,29,/rajneesh231/multiclassifier-solution-catboost,Multi-Class Prediction of Obesity Risk
18356,163089074,2455.0,,0,3,/gunjan2509/90-accuracy-obesity-risk,Multi-Class Prediction of Obesity Risk
18357,162212257,2492.0,0.8966763005780347,2,8,/eduardod/98-82-accuracy-obesity-risk-with-xgboost,Multi-Class Prediction of Obesity Risk
18358,164154709,2612.0,,0,13,/manuelandersen/update-pgs4e2-extensive-eda,Multi-Class Prediction of Obesity Risk
18359,164130530,2589.0,,2,3,/jclohjc/multiclass-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18360,161445977,2604.0,0.9002890173410405,1,11,/ridhii19/problem-3,Multi-Class Prediction of Obesity Risk
18361,161445977,2604.0,0.9002890173410405,1,11,/ridhii19/problem-3,Multi-Class Prediction of Obesity Risk
18362,161633951,2542.0,0.9002890173410405,0,8,/dhineshbabbu/abd-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18363,161669523,2605.0,0.9002890173410405,0,14,/yogeshratheea/notebookfcd8114bf1,Multi-Class Prediction of Obesity Risk
18364,162637791,2748.0,0.8746387283236994,6,14,/ibragimovuzoqmurod/multi-class-randomforest-100-best-score-89-9,Multi-Class Prediction of Obesity Risk
18365,162709348,2415.0,0.9002890173410405,0,6,/temiloluwapikuda/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18366,161536934,2322.0,,0,0,/chiragsanadhya/obesityrisk,Multi-Class Prediction of Obesity Risk
18367,162851808,2445.0,,0,2,/harshitajakiya/xgb-with-90-60,Multi-Class Prediction of Obesity Risk
18368,161686405,2642.0,,0,9,/enizzzz/beginner-friendly-eda-with-seaborn-and-matplot,Multi-Class Prediction of Obesity Risk
18369,163124623,2131.0,,0,4,/sofiaromanovna/first-attempt-kaggle-obesity-prediction,Multi-Class Prediction of Obesity Risk
18370,163773581,2283.0,0.8999277456647399,0,1,/danieldelasheras/daniel-ryan,Multi-Class Prediction of Obesity Risk
18371,163904008,2630.0,,2,12,/cid007/obesity-risk-eda-bl,Multi-Class Prediction of Obesity Risk
18372,161618120,2631.0,0.8995664739884393,0,10,/sankalp102/obesity-risk-eda-bl,Multi-Class Prediction of Obesity Risk
18373,161889227,2431.0,,0,3,/poonzhexuan/bayesian-optimization-lgbm-xgboost-rf-ensemble,Multi-Class Prediction of Obesity Risk
18374,161701259,2515.0,0.8963150289017341,0,8,/mohamedkhaledsadik/multi-class-prediction-of-obesity-risk-89,Multi-Class Prediction of Obesity Risk
18375,161901229,2580.0,,0,13,/vinodkumargurjar/multi-class-prediction-of-obesity-risk-vk,Multi-Class Prediction of Obesity Risk
18376,162026811,2732.0,,0,12,/abduazizabduraxmonov/playground-series-obesity-risk-s4-e2,Multi-Class Prediction of Obesity Risk
18377,164242791,2375.0,0.8984826589595376,0,2,/tyatsenk/multi-class-pred-of-obesity-risk-xgboost,Multi-Class Prediction of Obesity Risk
18378,162766719,2635.0,0.888728323699422,0,1,/hemanthhvv/obesity-playground,Multi-Class Prediction of Obesity Risk
18379,165112888,2457.0,,0,5,/martinapreusse/obesity-risk-prediction-with-xgboost-in-r,Multi-Class Prediction of Obesity Risk
18380,164690408,2424.0,,0,3,/nonscop/obesity-risk-fastai-chapter-9,Multi-Class Prediction of Obesity Risk
18381,162315066,2799.0,0.8977601156069365,4,24,/nishthakumari20/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18382,162322472,2800.0,0.8977601156069365,1,20,/namishjindal4/multi-class-prediction-of-obesity-risk-notebook,Multi-Class Prediction of Obesity Risk
18383,162529197,2656.0,0.8977601156069365,1,8,/arryuannkhanna123/easy-solution-xgb-hyper-parameter-tuning,Multi-Class Prediction of Obesity Risk
18384,163112502,2844.0,0.8977601156069365,4,17,/tarushirastogi/obesityrisk-prediction,Multi-Class Prediction of Obesity Risk
18385,163284852,2816.0,,2,12,/srsses/multiclass-classification-obesity,Multi-Class Prediction of Obesity Risk
18386,161565865,2125.0,,0,10,/ashmeet02/notebook3fa06219ec,Multi-Class Prediction of Obesity Risk
18387,163435852,2895.0,0.8840317919075145,0,4,/jovanagenti/neural-network-89-obesity-prediction,Multi-Class Prediction of Obesity Risk
18388,163097716,2949.0,0.8973988439306358,1,18,/thaparrishav/obesityrisk-xgboost,Multi-Class Prediction of Obesity Risk
18389,163269465,2761.0,0.8923410404624278,25,58,/ziadaymantesla/obesity,Multi-Class Prediction of Obesity Risk
18390,161412314,2553.0,,0,8,/marcogtt/playground-competition-s4e2,Multi-Class Prediction of Obesity Risk
18391,161443049,2356.0,0.8970375722543352,0,10,/marcogherbezza/are-you-at-risk-of-obesity,Multi-Class Prediction of Obesity Risk
18392,162035225,2568.0,0.8970375722543352,0,3,/avinashtokada25/multi-class-obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18393,162146334,2858.0,,1,8,/galalqassas/obesity-risk-with-great-visuals-and-basic-model,Multi-Class Prediction of Obesity Risk
18394,163323365,2633.0,0.7286849710982659,0,4,/danishelahi/obesity-risk,Multi-Class Prediction of Obesity Risk
18395,162265330,2784.0,,0,13,/jasleen234/notebookb558f66ab6,Multi-Class Prediction of Obesity Risk
18396,162637360,2787.0,0.8966763005780347,1,17,/akankshasolanki123/mynotebook,Multi-Class Prediction of Obesity Risk
18397,163767614,2663.0,0.8966763005780347,0,2,/andrianaamankwah/andriana-amankwah-bonsu-hw1,Multi-Class Prediction of Obesity Risk
18398,162946964,2634.0,0.8952312138728323,0,5,/kepler296b/obesity-risk,Multi-Class Prediction of Obesity Risk
18399,165362850,2672.0,,0,0,/sorrawitkwanja/obesity-prediction,Multi-Class Prediction of Obesity Risk
18400,162404719,2736.0,,0,9,/saliharanauzun/multiclass-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18401,163566174,2836.0,0.8746387283236994,2,5,/samarrathore402/obesity-perediction-metric,Multi-Class Prediction of Obesity Risk
18402,161270103,2714.0,,0,10,/viliuspstininkas/the-only-eda-you-will-need,Multi-Class Prediction of Obesity Risk
18403,162745717,2817.0,,1,1,/akshg203/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18404,161683420,2404.0,,2,12,/asmahachaichi/prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18405,164030944,2896.0,,0,18,/sanchibatra/obesity-risk-prediction-using-xgboost,Multi-Class Prediction of Obesity Risk
18406,161585426,2899.0,0.8908959537572254,0,8,/ridanshkaul/competitionnotebookforobesity,Multi-Class Prediction of Obesity Risk
18407,164552303,2809.0,,0,0,/lilakashi/fork-of-obesity-rick,Multi-Class Prediction of Obesity Risk
18408,164691410,2614.0,,0,4,/alexeinaxeli/obesity-class-prediction,Multi-Class Prediction of Obesity Risk
18409,161901404,2516.0,0.8945086705202312,1,13,/manvirkaur19/prediction-on-obesity-risk,Multi-Class Prediction of Obesity Risk
18410,163242210,2726.0,0.534320809248555,0,10,/rishitaverma02/obesity-risk,Multi-Class Prediction of Obesity Risk
18411,161714358,2380.0,0.8937861271676301,0,4,/josephmargaryan/89-voting-classifier,Multi-Class Prediction of Obesity Risk
18412,164516216,2569.0,,2,50,,Multi-Class Prediction of Obesity Risk
18413,162369108,3088.0,0.8934248554913294,3,34,/priyanshu54200/obesity-risk-ps-ml,Multi-Class Prediction of Obesity Risk
18414,163488615,2879.0,0.8934248554913294,4,21,/adhidevx369/obesity-risk-ensemblemlpredictor,Multi-Class Prediction of Obesity Risk
18415,163692178,2683.0,0.8153901734104047,0,6,/chopper53/multiclassobesityprediction,Multi-Class Prediction of Obesity Risk
18416,164909824,2673.0,0.8919797687861272,1,7,/dimabuhai/obesity-risk-random-forest-90,Multi-Class Prediction of Obesity Risk
18417,162691212,2886.0,0.8930635838150289,0,4,/oheula/obesity-prediction,Multi-Class Prediction of Obesity Risk
18418,163307497,3020.0,0.8927023121387283,1,9,/yuvam21/obesityprediction21,Multi-Class Prediction of Obesity Risk
18419,163760466,2670.0,0.8927023121387283,0,0,/jennietmt/thi-minh-hoa-tran,Multi-Class Prediction of Obesity Risk
18420,164451566,2538.0,,0,1,/tianmaru/obelix,Multi-Class Prediction of Obesity Risk
18421,164575169,2965.0,0.8916184971098265,3,15,/kaushalkrishna2000/playground-s4e2-obesity-multiclass-normal-wora,Multi-Class Prediction of Obesity Risk
18422,164688510,2751.0,0.8916184971098265,0,1,/vijaypatha/vp-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18423,161555180,2940.0,,1,15,/khushibansal15/multiclass-prediction-for-obesity-risk,Multi-Class Prediction of Obesity Risk
18424,161685989,2942.0,0.8908959537572254,0,6,/chaitanya2605/notebook5d0c542ce7,Multi-Class Prediction of Obesity Risk
18425,164532277,2632.0,,1,31,/harleenkaurdeora/multi-class-prediction-of-obesity,Multi-Class Prediction of Obesity Risk
18426,163622407,2981.0,,0,1,/aigerimtokhmetova/multi-class-catboost,Multi-Class Prediction of Obesity Risk
18427,162083639,2653.0,0.8901734104046243,1,16,/sirishasingla1906/obesity-risk-multi-class,Multi-Class Prediction of Obesity Risk
18428,162085154,2654.0,0.8901734104046243,0,22,/suvansh03/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18429,162085154,2654.0,0.8901734104046243,0,22,/suvansh03/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18430,162308615,2655.0,0.8901734104046243,0,27,/neelakshigupta/obesity,Multi-Class Prediction of Obesity Risk
18431,162531061,2657.0,0.8901734104046243,0,8,/akshit2605/notebookb176190f70,Multi-Class Prediction of Obesity Risk
18432,162532238,2658.0,0.8901734104046243,0,5,/parthvashish/notebook2715eca3f9,Multi-Class Prediction of Obesity Risk
18433,162951179,2661.0,0.8901734104046243,0,18,/kanishhkaa/obesity-risk,Multi-Class Prediction of Obesity Risk
18434,162951179,2661.0,0.8901734104046243,0,18,/kanishhkaa/obesity-risk,Multi-Class Prediction of Obesity Risk
18435,163004855,2859.0,0.759393063583815,0,0,/anirudhasutar/multi-class-prediction-for-obesity-risk,Multi-Class Prediction of Obesity Risk
18436,162668658,2996.0,0.8703034682080925,5,19,/barbagrande007/bbg007-s4e2-obesity,Multi-Class Prediction of Obesity Risk
18437,162713651,2778.0,0.8894508670520231,0,8,/sehajbirsinghbains/obesity-prediction,Multi-Class Prediction of Obesity Risk
18438,162449030,3017.0,0.6705202312138728,0,9,/jayyanamandala/neural-nets-predictions-for-obesity-risk,Multi-Class Prediction of Obesity Risk
18439,163474070,3036.0,,0,10,/najeebz/obesity-risk-study-eda-auto-visualization-tools,Multi-Class Prediction of Obesity Risk
18440,164900267,3009.0,0.8836705202312138,0,3,/uzdavinys/pg-s04e02-fastai-tabular-model,Multi-Class Prediction of Obesity Risk
18441,164752944,2934.0,0.8829479768786127,0,0,/ericmundt/obesity-risk-mc-playground-series,Multi-Class Prediction of Obesity Risk
18442,163801475,2994.0,0.888728323699422,0,0,/subhendudharua/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18443,161935824,2989.0,0.8833092485549133,6,33,/cheesecke/obesity-prediction-with-deep-neural-network,Multi-Class Prediction of Obesity Risk
18444,161528106,2805.0,0.8880057803468208,0,11,/saanvi004/obesity-risk,Multi-Class Prediction of Obesity Risk
18445,161922420,2808.0,0.8880057803468208,4,73,/bravo03/prediction-of-obesity-risk-using-randomforest,Multi-Class Prediction of Obesity Risk
18446,161498029,2890.0,,0,12,/chhavidhankhar11/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18447,163848425,2974.0,0.8854768786127167,0,0,/hyojunyoung/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18448,164336865,2892.0,0.8876445086705202,0,9,/tanisha1604/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18449,165370403,2773.0,0.9158236994219652,0,0,/thamolwanjaru/multi-class-obesity-lgb,Multi-Class Prediction of Obesity Risk
18450,164901426,2951.0,,0,1,/abdelrahmanahmed110/obesity-risk-eda-prediction,Multi-Class Prediction of Obesity Risk
18451,161655664,2794.0,,0,4,/vidhikishorwaghela/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18452,161690541,3045.0,0.8869219653179191,3,39,/ankit1743/obesity-risk-gradient-boosting,Multi-Class Prediction of Obesity Risk
18453,161486291,2980.0,0.6029624277456648,0,13,/praneykalra/obesity,Multi-Class Prediction of Obesity Risk
18454,162623807,2929.0,0.8872832369942196,0,1,/osamaakhaled/ensemble-models-of-obesity-risk-problem,Multi-Class Prediction of Obesity Risk
18455,165631974,2938.0,,0,0,/phucdo2203/obesity-risk-prediction-multi-class,Multi-Class Prediction of Obesity Risk
18456,162735514,2943.0,,0,1,/juliastencel/prediction-of-obesity-risk-svm-rf-nn,Multi-Class Prediction of Obesity Risk
18457,162181290,2918.0,0.8869219653179191,2,17,,Multi-Class Prediction of Obesity Risk
18458,164538081,2915.0,,11,40,/kattat/obesity-prediction-eda-fe-pytorch,Multi-Class Prediction of Obesity Risk
18459,162520141,2919.0,0.8869219653179191,0,10,/garvitmadaan/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18460,163927354,2953.0,,0,1,/esaihuamanmeza/predicci-n-de-riesgo-de-obesidad-con-randomforest,Multi-Class Prediction of Obesity Risk
18461,162606007,2948.0,,0,7,/lumierebatalong/obesity-risk-keras-feature-engineering,Multi-Class Prediction of Obesity Risk
18462,165261009,3035.0,,0,0,/fancifulcrow/multi-class-prediction-of-obesity-risk-ann,Multi-Class Prediction of Obesity Risk
18463,161624084,3040.0,,0,7,/pmathur/obesity-risk-random-forest-pipelines-bmi,Multi-Class Prediction of Obesity Risk
18464,162474868,2871.0,0.8854768786127167,3,22,/simarjitkaur123/obesity-prediction,Multi-Class Prediction of Obesity Risk
18465,162712915,2872.0,0.8854768786127167,0,5,/pulkittarora/obesity-risk-using-randomforestclassifier,Multi-Class Prediction of Obesity Risk
18466,162522475,2873.0,0.8854768786127167,0,21,/devbansal2140/multi-class-prediction-using-random-forest,Multi-Class Prediction of Obesity Risk
18467,162529609,2874.0,0.8854768786127167,0,16,/aashimbansal/obesity-risk-aashim,Multi-Class Prediction of Obesity Risk
18468,162530707,2875.0,0.8854768786127167,0,2,/yashaskirnapure/notebook5f9764ac81,Multi-Class Prediction of Obesity Risk
18469,162593081,2876.0,0.8854768786127167,0,10,/ojaswanib/obesity-prediction-oj,Multi-Class Prediction of Obesity Risk
18470,164039076,2877.0,0.8854768786127167,0,6,/yashasgarg/obesity-prediction,Multi-Class Prediction of Obesity Risk
18471,161300600,2688.0,0.884393063583815,0,10,/aarushijuneja07/solution-obesity-risk,Multi-Class Prediction of Obesity Risk
18472,161300600,2688.0,0.884393063583815,0,10,/aarushijuneja07/solution-obesity-risk,Multi-Class Prediction of Obesity Risk
18473,161664562,2690.0,,5,46,/ujjvalvashisht/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18474,161689016,2691.0,0.884393063583815,0,16,/ashish32700/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18475,161775223,2694.0,,0,13,/nipun356/obesity-risk,Multi-Class Prediction of Obesity Risk
18476,162502574,2932.0,0.7738439306358381,1,22,/ehsaasdhand/obesity-predication,Multi-Class Prediction of Obesity Risk
18477,163159628,2700.0,0.884393063583815,0,2,/gargsarita/notebook1cdbeb9e88,Multi-Class Prediction of Obesity Risk
18478,163161912,2701.0,0.884393063583815,0,1,,Multi-Class Prediction of Obesity Risk
18479,163284674,2702.0,0.884393063583815,2,24,/kartikye10/multi-class-prediction-of-obesity-risk-easy,Multi-Class Prediction of Obesity Risk
18480,163333045,2704.0,0.884393063583815,1,11,/hrshpreet/notebook,Multi-Class Prediction of Obesity Risk
18481,162714028,2705.0,,0,15,/abhinavvvvvvvvvv/pycaret-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18482,163424310,2708.0,0.884393063583815,4,9,/hrshbachan3/obesityriskpred-multiclass,Multi-Class Prediction of Obesity Risk
18483,163424310,2708.0,0.884393063583815,4,9,/hrshbachan3/obesityriskpred-multiclass,Multi-Class Prediction of Obesity Risk
18484,163404533,3103.0,,0,11,/akulvaishnavi/obesity-cvd-risk-analysis,Multi-Class Prediction of Obesity Risk
18485,162952311,2930.0,,0,6,/mclegend/obese-classification-using-xgbclassifier,Multi-Class Prediction of Obesity Risk
18486,161455864,2967.0,0.8833092485549133,0,7,/sanjugag/obesity-risk,Multi-Class Prediction of Obesity Risk
18487,162738636,2924.0,,0,14,/sturarods/multiclass-prediction-w-random-forest,Multi-Class Prediction of Obesity Risk
18488,166430991,2979.0,,2,5,/adrianasalcedo/xgb-cat-nn,Multi-Class Prediction of Obesity Risk
18489,163482067,3107.0,,0,6,/icksir/pytorch-tabular-87-in-few-steps,Multi-Class Prediction of Obesity Risk
18490,164617741,3078.0,0.8815028901734104,0,2,/akashvenugopal99/obesity-risk-classification,Multi-Class Prediction of Obesity Risk
18491,164234651,3007.0,,0,1,/dedlinnn/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18492,165013900,2972.0,,0,3,/neamulislamfahim/prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18493,164257810,3052.0,0.8414017341040463,0,5,/yteshima/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18494,161735612,3082.0,0.4833815028901734,0,4,/khushikhushikhushi/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18495,163769090,3042.0,,0,0,/khalidemam/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18496,164751677,3170.0,0.8768063583815029,0,0,/ikramur/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18497,161688241,3074.0,0.8807803468208093,0,9,/shwetakk/notebooke325351c91,Multi-Class Prediction of Obesity Risk
18498,163051609,3085.0,0.8804190751445087,0,0,/codenamemadhav/multi-class-prediction-of-obesity-risk-t2,Multi-Class Prediction of Obesity Risk
18499,161835237,3141.0,,0,5,/anmolarora15/obesity-risk-prediction-in-depth-eda,Multi-Class Prediction of Obesity Risk
18500,164264033,3125.0,0.880057803468208,0,0,/ioancristianbratu/obesity-risk-prediction-with-adaboost,Multi-Class Prediction of Obesity Risk
18501,162220335,3134.0,0.8782514450867052,0,2,/michelecomotti/multi-class-prediction-of-obesity-risk-svc,Multi-Class Prediction of Obesity Risk
18502,164793558,3158.0,0.8782514450867052,0,0,/jigglyjonny/obesity-comp,Multi-Class Prediction of Obesity Risk
18503,162702125,3138.0,,0,17,/ishaangaba17/pycaret-classification-easy-to-understand,Multi-Class Prediction of Obesity Risk
18504,162443700,3105.0,,0,11,/sakibulislam216/feature-eda-eng-sfs-dt,Multi-Class Prediction of Obesity Risk
18505,164720299,3048.0,0.877528901734104,0,0,/amandakube/data119-multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18506,161559196,3030.0,,0,6,/sandeepbora/ps-s4e2-eda-random-forest,Multi-Class Prediction of Obesity Risk
18507,164228218,3168.0,,0,1,/akhilpm1996/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18508,161740654,3156.0,,0,6,/kaushikkrsarma/obesity-using-ann,Multi-Class Prediction of Obesity Risk
18509,161529368,3228.0,0.8746387283236994,0,16,/shamsin/notebook0a6b074a9a,Multi-Class Prediction of Obesity Risk
18510,164404762,3124.0,0.8742774566473989,0,0,/drsandeepmonga/multi-class-obesity-prediction,Multi-Class Prediction of Obesity Risk
18511,164404762,3124.0,0.8742774566473989,0,0,/drsandeepmonga/multi-class-obesity-prediction,Multi-Class Prediction of Obesity Risk
18512,161970372,3180.0,,0,9,/agarwalyashhh/obesity-ann-eda-keras,Multi-Class Prediction of Obesity Risk
18513,161905189,3165.0,,2,25,/eakanshagarwal24/multi-class-predict-obesity,Multi-Class Prediction of Obesity Risk
18514,161583372,3195.0,0.8688583815028902,0,19,/samarjeet09/starter-notebook-eda-comparisons,Multi-Class Prediction of Obesity Risk
18515,163490408,3122.0,0.8710260115606936,1,5,/huseinghadiali/lazypredict-gradientboosting-catboost-dt,Multi-Class Prediction of Obesity Risk
18516,163490408,3122.0,0.8710260115606936,1,5,/huseinghadiali/lazypredict-gradientboosting-catboost-dt,Multi-Class Prediction of Obesity Risk
18517,163359154,3152.0,,0,3,/shwetalishimangaud/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18518,161275881,3196.0,0.869942196531792,0,4,/seokhyokang/multi-class-obesity-prediction-w-lgbm-optuna,Multi-Class Prediction of Obesity Risk
18519,161923993,3188.0,,0,6,/samithanawarathna/obesity-risk-data-preprocessing-and-modeling,Multi-Class Prediction of Obesity Risk
18520,164740141,3208.0,,0,1,/monicabackes/multi-class-obesity-eda-and-mlp-classification,Multi-Class Prediction of Obesity Risk
18521,161693111,3174.0,0.8638005780346821,16,56,/yessicatuteja/obesity-risk-deep-neural-network,Multi-Class Prediction of Obesity Risk
18522,161536248,3225.0,0.8648843930635838,0,14,/shauryabansal05/obesity-multiclass-classification,Multi-Class Prediction of Obesity Risk
18523,161537136,3226.0,,0,2,/namaymahindru/notebookd83a13d04f,Multi-Class Prediction of Obesity Risk
18524,164423402,3169.0,0.8648843930635838,0,3,/akarshannirwan/playground-4-ep-02,Multi-Class Prediction of Obesity Risk
18525,164569027,3199.0,0.8641618497109826,0,0,/supaseksamurai88/james-obesity-prediction-notebook,Multi-Class Prediction of Obesity Risk
18526,161539764,3214.0,0.8580202312138728,4,20,/guedes5132/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18527,163095630,3266.0,,0,3,/devendrasingh22/playground-series-obesity,Multi-Class Prediction of Obesity Risk
18528,161587319,3249.0,0.8601878612716763,1,9,/tracyporter/play-4-2-obesity-flax-mlpc-softmax,Multi-Class Prediction of Obesity Risk
18529,164214513,3250.0,0.8601878612716763,1,2,/mohammedinfas/obesity-softmax,Multi-Class Prediction of Obesity Risk
18530,162399284,3253.0,,0,1,/inomjonov/mironshoh-obesityrisk,Multi-Class Prediction of Obesity Risk
18531,163424514,3286.0,0.7286849710982659,0,20,/saranshthegoat/smj-s-obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18532,162078082,3263.0,0.8565751445086706,1,2,/matthewsfarmer/pg-s4e2-micro-lit-review-eda-xgboost,Multi-Class Prediction of Obesity Risk
18533,163458370,3290.0,0.8565751445086706,0,6,/violeteb/fork-of-multi-class-prediction-of-obesity-risk-v,Multi-Class Prediction of Obesity Risk
18534,164017227,3287.0,0.8536849710982659,0,3,/mehranzeidi/obesity-risk,Multi-Class Prediction of Obesity Risk
18535,164017227,3287.0,0.8536849710982659,0,3,/mehranzeidi/obesity-risk,Multi-Class Prediction of Obesity Risk
18536,164209351,3311.0,0.8475433526011561,8,11,/desolationofsmaug/ensemble-learning-84-8-accuracy,Multi-Class Prediction of Obesity Risk
18537,162649187,3333.0,,0,1,/nilawilson/prediction-using-tensorflow-nn-with-0-88,Multi-Class Prediction of Obesity Risk
18538,162648705,3354.0,0.8367052023121387,1,11,/mridul2003/obesity-risk-prediction,Multi-Class Prediction of Obesity Risk
18539,164068715,3342.0,,0,4,/rahul45862/multi-class-of-obesity,Multi-Class Prediction of Obesity Risk
18540,162172758,3372.0,0.8348988439306358,0,20,/vinee0/multi-class-prediction-of-obesity-risk-playground,Multi-Class Prediction of Obesity Risk
18541,162002890,3364.0,,0,3,/akashpawar10/multi-class-classification,Multi-Class Prediction of Obesity Risk
18542,162847541,3368.0,0.8251445086705202,0,4,/muhriddinmalik/obesity-risk-competition-notebook,Multi-Class Prediction of Obesity Risk
18543,164902820,3383.0,,0,1,/giladaharoni/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18544,162761166,3401.0,,8,20,/rui314/multi-class-prediction-with-tensorflow,Multi-Class Prediction of Obesity Risk
18545,161933492,3405.0,0.7713150289017341,0,5,/oneskylord/multi-classification-98-3-random-forest,Multi-Class Prediction of Obesity Risk
18546,164385507,3440.0,,0,5,/manishpatil009/obesity-risk-competition,Multi-Class Prediction of Obesity Risk
18547,164392655,3444.0,0.5700867052023122,0,5,/dheerov/multi-class-obesity-prediction,Multi-Class Prediction of Obesity Risk
18548,162547135,3445.0,,0,2,/bhavyaprakash02/obesity-level-classification,Multi-Class Prediction of Obesity Risk
18549,162901931,3453.0,0.5653901734104047,2,9,/luckychitundu/obesity-risk-tpg,Multi-Class Prediction of Obesity Risk
18550,162717833,3457.0,0.5541907514450867,0,9,/jkaur28/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18551,163404695,3460.0,0.4938583815028902,0,9,/aarushijain24/notebook3599a97d15,Multi-Class Prediction of Obesity Risk
18552,164891481,3464.0,,0,0,/pogicat/obesity-rate-xgbclassifier-bayessearchcv,Multi-Class Prediction of Obesity Risk
18553,161677878,3477.0,0.3489884393063583,5,131,/hardikgarg03/obesity-risk-random-forest-xgboost-96-2-accuracy,Multi-Class Prediction of Obesity Risk
18554,162376630,3481.0,,2,7,/fekihmea/data-refinement-outliers-by-bmi-body-mass-index,Multi-Class Prediction of Obesity Risk
18555,161675016,3495.0,0.2424132947976878,1,50,/shiivvvaam/obesity-risk,Multi-Class Prediction of Obesity Risk
18556,163106043,3497.0,0.2124277456647398,0,4,/vishwasmishra1234/obesity,Multi-Class Prediction of Obesity Risk
18557,163140772,3555.0,0.1419797687861271,0,11,/mahmoudragabsaber/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18558,163006798,3553.0,,0,2,/alioraji/multi-class-prediction-a-o,Multi-Class Prediction of Obesity Risk
18559,162340916,3562.0,0.1199421965317919,1,1,/eyosiasteffera/multi-class-prediction-of-obesity-risk,Multi-Class Prediction of Obesity Risk
18560,162732847,3573.0,0.0,0,3,/sailikithd004/obesity-prediction-rf,Multi-Class Prediction of Obesity Risk
18561,162732847,3573.0,0.0,0,3,/sailikithd004/obesity-prediction-rf,Multi-Class Prediction of Obesity Risk
18562,163169721,3576.0,0.0,0,2,/jaisuryasundarbabu/basic-multi-classification-using-xgboost-and-rf,Multi-Class Prediction of Obesity Risk
18563,164027960,3582.0,,0,6,/myash21/multi-class-prediction-using-5-different-models,Multi-Class Prediction of Obesity Risk
18564,164981875,3585.0,,2,5,/praveshsharma2002/obesity-kaggle,Multi-Class Prediction of Obesity Risk