Published October 22, 2017
| Version v0.9.0
Software
Open
rasbt/mlxtend: Version 0.9.0
Creators
- Sebastian Raschka1
- Reiichiro Nakano
- Will McGinnis2
- James Bourbeau3
- chkoar
- Pablo Fernandez4
- Alejandro Correa Bahnsen5
- Vostretsov Nikita
- wahutch
- mrkaiser
- kernc
- jlopezpena
- Michael Peters
- Marc Abramowitz6
- Konstantinos Paliouras7
- Joshua Görner
- Jelmer Borst
- Ilya8
- Iaroslav Shcherbatyi9
- hsperr
- GILLES Armand10
- Francis T. O'Donovan11
- Eike Dehling12
- Batuhan Bardak13
- Anton Loss
- Anebi Agbo
- Ajinkya Kale
- Adam Erickson
- 1. Michigan State University
- 2. Predikto Inc.
- 3. @WIPACrepo
- 4. FANSI Motorsport
- 5. Easy Solutions
- 6. @adobe-platform
- 7. @Workable
- 8. LPI ASC
- 9. Saarland University
- 10. millesime.ai
- 11. @betteroutcomes
- 12. Trifork
- 13. STM
Description
New Features
- Added
evaluate.permutation_test
, a permutation test for hypothesis testing (or A/B testing) to test if two samples come from the same distribution. Or in other words, a procedure to test the null hypothesis that that two groups are not significantly different (e.g., a treatment and a control group). (#250) - Added
'leverage'
and'conviction
as evaluation metrics to thefrequent_patterns.association_rules
function. (#246 & #247) - Added a
loadings_
attribute toPrincipalComponentAnalysis
to compute the factor loadings of the features on the principal components. (#251) - Allow grid search over classifiers/regressors in ensemble and stacking estimators. (#259)
- New
make_multiplexer_dataset
function that creates a dataset generated by a n-bit Boolean multiplexer for evaluating supervised learning algorithms. (#263) - Added a new
BootstrapOutOfBag
class, an implementation of the out-of-bag bootstrap to evaluate supervised learning algorithms. (#265) - The parameters for
StackingClassifier
,StackingCVClassifier
,StackingRegressor
,StackingCVRegressor
, andEnsembleVoteClassifier
can now be tuned using scikit-learn'sGridSearchCV
(#254 via James Bourbeau)
- The
'support'
column returned byfrequent_patterns.association_rules
was changed to compute the support of "antecedant union consequent", and newantecedant support'
and'consequent support'
column were added to avoid ambiguity. (#245) - Allow the
OnehotTransactions
to be cloned via scikit-learn'sclone
function, which is required by e.g., scikit-learn'sFeatureUnion
orGridSearchCV
(via Iaroslav Shcherbatyi). (#249)
- Fix issues with
self._init_time
parameter in_IterativeModel
subclasses. (#256) - Fix imprecision bug that occurred in
plot_ecdf
when run on Python 2.7. (264) - The vectors from SVD in
PrincipalComponentAnalysis
are no being scaled so that the eigenvalues viasolver='eigen'
andsolver='svd'
now store eigenvalues that have the same magnitudes. (#251)
Files
rasbt/mlxtend-v0.9.0.zip
Files
(10.6 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/rasbt/mlxtend/tree/v0.9.0 (URL)