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<li><a class="reference internal" href="#"><code class="docutils literal"><span class="pre">sklearn.cross_validation</span></code>.StratifiedKFold</a></li>
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<div class="section" id="sklearn-cross-validation-stratifiedkfold">
<h1><code class="xref py py-mod docutils literal"><span class="pre">sklearn.cross_validation</span></code>.StratifiedKFold<a class="headerlink" href="#sklearn-cross-validation-stratifiedkfold" title="Permalink to this headline">¶</a></h1>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last"><strong>DEPRECATED</strong></p>
</div>
<dl class="class">
<dt id="sklearn.cross_validation.StratifiedKFold">
<em class="property">class </em><code class="descclassname">sklearn.cross_validation.</code><code class="descname">StratifiedKFold</code><span class="sig-paren">(</span><em>y</em>, <em>n_folds=3</em>, <em>shuffle=False</em>, <em>random_state=None</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/474b5e0/sklearn/cross_validation.py#L474"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cross_validation.StratifiedKFold" title="Permalink to this definition">¶</a></dt>
<dd><p>Stratified K-Folds cross validation iterator</p>
<div class="deprecated">
<p><span class="versionmodified">Deprecated since version 0.18: </span>This module will be removed in 0.20.
Use <a class="reference internal" href="sklearn.model_selection.StratifiedKFold.html#sklearn.model_selection.StratifiedKFold" title="sklearn.model_selection.StratifiedKFold"><code class="xref py py-class docutils literal"><span class="pre">sklearn.model_selection.StratifiedKFold</span></code></a> instead.</p>
</div>
<p>Provides train/test indices to split data in train test sets.</p>
<p>This cross-validation object is a variation of KFold that
returns stratified folds. The folds are made by preserving
the percentage of samples for each class.</p>
<p>Read more in the <a class="reference internal" href="../cross_validation.html#cross-validation"><span class="std std-ref">User Guide</span></a>.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>y</strong> : array-like, [n_samples]</p>
<blockquote>
<div><p>Samples to split in K folds.</p>
</div></blockquote>
<p><strong>n_folds</strong> : int, default=3</p>
<blockquote>
<div><p>Number of folds. Must be at least 2.</p>
</div></blockquote>
<p><strong>shuffle</strong> : boolean, optional</p>
<blockquote>
<div><p>Whether to shuffle each stratification of the data before splitting
into batches.</p>
</div></blockquote>
<p><strong>random_state</strong> : int, RandomState instance or None, optional, default=None</p>
<blockquote class="last">
<div><p>If int, random_state is the seed used by the random number
generator; If RandomState instance, random_state is the random number
generator; If None, the random number generator is the RandomState
instance used by <cite>np.random</cite>. Used when <code class="docutils literal"><span class="pre">shuffle</span></code> == True.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference internal" href="sklearn.cross_validation.LabelKFold.html#sklearn.cross_validation.LabelKFold" title="sklearn.cross_validation.LabelKFold"><code class="xref py py-obj docutils literal"><span class="pre">LabelKFold</span></code></a></dt>
<dd>K-fold iterator variant with non-overlapping labels.</dd>
</dl>
</div>
<p class="rubric">Notes</p>
<p>Train and test sizes may be different in each fold, with a difference of at
most <code class="docutils literal"><span class="pre">n_classes</span></code>.</p>
<p class="rubric">Examples</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">sklearn.cross_validation</span> <span class="k">import</span> <span class="n">StratifiedKFold</span>
<span class="gp">>>> </span><span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">skf</span> <span class="o">=</span> <span class="n">StratifiedKFold</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">n_folds</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="gp">>>> </span><span class="nb">len</span><span class="p">(</span><span class="n">skf</span><span class="p">)</span>
<span class="go">2</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">skf</span><span class="p">)</span>
<span class="go">sklearn.cross_validation.StratifiedKFold(labels=[0 0 1 1], n_folds=2,</span>
<span class="go"> shuffle=False, random_state=None)</span>
<span class="gp">>>> </span><span class="k">for</span> <span class="n">train_index</span><span class="p">,</span> <span class="n">test_index</span> <span class="ow">in</span> <span class="n">skf</span><span class="p">:</span>
<span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="s2">"TRAIN:"</span><span class="p">,</span> <span class="n">train_index</span><span class="p">,</span> <span class="s2">"TEST:"</span><span class="p">,</span> <span class="n">test_index</span><span class="p">)</span>
<span class="gp">... </span> <span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span> <span class="o">=</span> <span class="n">X</span><span class="p">[</span><span class="n">train_index</span><span class="p">],</span> <span class="n">X</span><span class="p">[</span><span class="n">test_index</span><span class="p">]</span>
<span class="gp">... </span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">y</span><span class="p">[</span><span class="n">train_index</span><span class="p">],</span> <span class="n">y</span><span class="p">[</span><span class="n">test_index</span><span class="p">]</span>
<span class="go">TRAIN: [1 3] TEST: [0 2]</span>
<span class="go">TRAIN: [0 2] TEST: [1 3]</span>
</pre></div>
</div>
<dl class="method">
<dt id="sklearn.cross_validation.StratifiedKFold.__init__">
<code class="descname">__init__</code><span class="sig-paren">(</span><em>y</em>, <em>n_folds=3</em>, <em>shuffle=False</em>, <em>random_state=None</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/474b5e0/sklearn/cross_validation.py#L535"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cross_validation.StratifiedKFold.__init__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
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