Software Open Access
Sebastian Raschka; James Bourbeau; Reiichiro Nakano; Zach Griffith; Kota Mori; Will McGinnis; JJLWHarrison; Guillaume Poirier-Morency; Daniel; Qiang Gu; Floris Hoogenboom; Colin; Vahid Mirjalili; selay01; Christos Aridas; Steve Harenberg; Pablo Fernandez; Oliver Tomic; Laurens Geffert; Janpreet Singh; Alejandro Correa Bahnsen; Benjamin Lee; Batuhan Bardak; Arfon Smith; Anton Loss; Anebi; Ajinkya Kale; Adam Erickson; Adam Cooper; Ackerley Tng
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for Strategic Infocomm Technologies</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:title>rasbt/mlxtend: Version 0.17.0</dct:title> <dct:publisher> <foaf:Agent> <foaf:name>Zenodo</foaf:name> </foaf:Agent> </dct:publisher> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2019</dct:issued> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2019-07-19</dct:issued> <owl:sameAs rdf:resource="https://zenodo.org/record/3343208"/> <adms:identifier> <adms:Identifier> <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/3343208</skos:notation> <adms:schemeAgency>url</adms:schemeAgency> </adms:Identifier> </adms:identifier> <dct:relation rdf:resource="https://github.com/rasbt/mlxtend/tree/v0.17.0"/> <dct:isVersionOf rdf:resource="https://doi.org/10.5281/zenodo.594432"/> <owl:versionInfo>v0.17.0</owl:versionInfo> <dct:description>New Features <ul> <li>Added an enhancement to the existing <code>iris_data()</code> such that both the UCI Repository version of the Iris dataset as well as the corrected, original version of the dataset can be loaded, which has a slight difference in two data points (consistent with Fisher's paper; this is also the same as in R). (via <a href="https://github.com/rasbt/mlxtend/pull/532">#539</a> via <a href="https://github.com/janismdhanbad">janismdhanbad</a>)</li> <li>Added optional <code>groups</code> parameter to <code>SequentialFeatureSelector</code> and <code>ExhaustiveFeatureSelector</code> <code>fit()</code> methods for forwarding to sklearn CV (<a href="https://github.com/rasbt/mlxtend/pull/537">#537</a> via <a href="https://github.com/qiaguhttps://github.com/arc12">arc12</a>)</li> <li>Added a new <code>plot_pca_correlation_graph</code> function to the <code>mlxtend.plotting</code> submodule for plotting a PCA correlation graph. (<a href="https://github.com/rasbt/mlxtend/pull/544">#544</a> via <a href="https://github.com/qiaguhttps://github.com/Gabriel-Azevedo-Ferreira">Gabriel-Azevedo-Ferreira</a>)</li> <li>Added a <code>zoom_factor</code> parameter to the <code>mlxten.plotting.plot_decision_region</code> function that allows users to zoom in and out of the decision region plots. (<a href="https://github.com/rasbt/mlxtend/pull/545">#545</a>)</li> <li>Added a function <code>fpgrowth</code> that implements the FP-Growth algorithm for mining frequent itemsets as a drop-in replacement for the existing <code>apriori</code> algorithm. (<a href="https://github.com/rasbt/mlxtend/pull/550">#550</a> via <a href="https://github.com/harenbergsd">Steve Harenberg</a>)</li> <li>New <code>heatmap</code> function in <code>mlxtend.plotting</code>. (<a href="https://github.com/rasbt/mlxtend/pull/552">#552</a>)</li> <li>Added a function <code>fpmax</code> that implements the FP-Max algorithm for mining maximal itemsets as a drop-in replacement for the <code>fpgrowth</code> algorithm. (<a href="https://github.com/rasbt/mlxtend/pull/553">#553</a> via <a href="https://github.com/harenbergsd">Steve Harenberg</a>)</li> <li>New <code>figsize</code> parameter for the <code>plot_decision_regions</code> function in <code>mlxtend.plotting</code>. (<a href="https://github.com/rasbt/mlxtend/pull/555">#555</a> via <a href="https://github.com/kazyka">Mirza Hasanbasic</a>)</li> <li>New <code>low_memory</code> option for the <code>apriori</code> frequent itemset generating function. Setting <code>low_memory=False</code> (default) uses a substantially optimized version of the algorithm that is 3-6x faster than the original implementation (<code>low_memory=True</code>). (<a href="https://github.com/rasbt/mlxtend/pull/567">#567</a> via <a href="https://github.com/jmayse">jmayse</a>)</li> </ul> Changes <ul> <li>Now uses the latest joblib library under the hood for multiprocessing instead of <code>sklearn.externals.joblib</code>. (<a href="https://github.com/rasbt/mlxtend/pull/547">#547</a>)</li> <li>Changes to <code>StackingCVClassifier</code> and <code>StackingCVRegressor</code> such that first-level models are allowed to generate output of non-numeric type. (<a href="https://github.com/rasbt/mlxtend/pull/562">#562</a>)</li> </ul> Bug Fixes <ul> <li>Fixed documentation of <code>iris_data()</code> under <code>iris.py</code> by adding a note about differences in the iris data in R and UCI machine learning repo.</li> <li>Make sure that if the <code>'svd'</code> mode is used in PCA, the number of eigenvalues is the same as when using <code>'eigen'</code> (append 0's zeros in that case) (<a href="https://github.com/rasbt/mlxtend/pull/565">#565</a>)</li> </ul></dct:description> <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/> <dct:accessRights> <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess"> <rdfs:label>Open Access</rdfs:label> </dct:RightsStatement> </dct:accessRights> <dcat:distribution> <dcat:Distribution> <dcat:accessURL rdf:resource="https://doi.org/10.5281/zenodo.3343208"/> </dcat:Distribution> </dcat:distribution> <dcat:distribution> <dcat:Distribution> <dcat:accessURL rdf:resource="https://doi.org/10.5281/zenodo.3343208"/> <dcat:byteSize>15939191</dcat:byteSize> <dcat:downloadURL rdf:resource="https://zenodo.org/record/3343208/files/rasbt/mlxtend-v0.17.0.zip"/> <dcat:mediaType>application/zip</dcat:mediaType> </dcat:Distribution> </dcat:distribution> </rdf:Description> </rdf:RDF>
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