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‎.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: 3f34364e6a3f0dddf53a9eb51e6bfdb7
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tags: 645f666f9bcd5a90fca523b33c5a78b7

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‎_modules/index.html

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<title>scikit-multilearn: Multi-Label Classification in Python &#8212; Multi-Label Classification for Python</title>
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<link rel="stylesheet" href="../_static/" type="text/css" />
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<li><a href="skmultilearn/adapt/brknn.html">skmultilearn.adapt.brknn</a></li>
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<li><a href="skmultilearn/adapt/mlaram.html">skmultilearn.adapt.mlaram</a></li>
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<li><a href="skmultilearn/cluster/networkx.html">skmultilearn.cluster.networkx</a></li>
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<li><a href="skmultilearn/cluster/random.html">skmultilearn.cluster.random</a></li>
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<li><a href="skmultilearn/dataset.html">skmultilearn.dataset</a></li>
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<li><a href="skmultilearn/embedding/classifier.html">skmultilearn.embedding.classifier</a></li>
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<li><a href="skmultilearn/embedding/clems.html">skmultilearn.embedding.clems</a></li>
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<li><a href="skmultilearn/embedding/openne.html">skmultilearn.embedding.openne</a></li>
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<li><a href="skmultilearn/embedding/skembeddings.html">skmultilearn.embedding.skembeddings</a></li>
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<li><a href="skmultilearn/ensemble/partition.html">skmultilearn.ensemble.partition</a></li>
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<li><a href="skmultilearn/ensemble/rakeld.html">skmultilearn.ensemble.rakeld</a></li>
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<li><a href="skmultilearn/model_selection/iterative_stratification.html">skmultilearn.model_selection.iterative_stratification</a></li>
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</div>
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<div class="footer-copyright blue-grey darken-4">
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Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.7.4.
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Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.8.2.
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‎_modules/sklearn/base.html

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‎_modules/skmultilearn/adapt/brknn.html

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<title>scikit-multilearn: Multi-Label Classification in Python &#8212; Multi-Label Classification for Python</title>
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<link rel="stylesheet" href="../../../_static/" type="text/css" />
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<span class="sd"> from sklearn.model_selection import GridSearchCV</span>
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<span class="sd"> parameters = {&#39;k&#39;: range(1,3)}</span>
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<span class="sd"> clf = GridSearchCV(BRkNNaClassifier(), parameters, scoring=score)</span>
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<span class="sd"> clf.fit(X, y)</span>
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Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.7.4.
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‎_modules/skmultilearn/adapt/mlaram.html

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<title>scikit-multilearn: Multi-Label Classification in Python &#8212; Multi-Label Classification for Python</title>
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‎_modules/skmultilearn/adapt/mlknn.html

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<title>scikit-multilearn: Multi-Label Classification in Python &#8212; Multi-Label Classification for Python</title>
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<link rel="stylesheet" href="../../../_static/" type="text/css" />
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<span class="sd"> from sklearn.model_selection import GridSearchCV</span>
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<span class="sd"> parameters = {&#39;k&#39;: range(1,3), &#39;s&#39;: [0.5, 0.7, 1.0]}</span>
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<span class="sd"> print (clf.best_params_, clf.best_score_)</span>
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<span class="sd"> # output</span>
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<span class="sd"> ({&#39;k&#39;: 1, &#39;s&#39;: 0.5}, 0.78988303374297597)</span>
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Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.7.4.
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Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.8.2.
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