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<ul>
<li><a class="reference internal" href="#"><code class="docutils literal"><span class="pre">sklearn.cross_validation</span></code>.StratifiedShuffleSplit</a></li>
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<div class="section" id="sklearn-cross-validation-stratifiedshufflesplit">
<h1><code class="xref py py-mod docutils literal"><span class="pre">sklearn.cross_validation</span></code>.StratifiedShuffleSplit<a class="headerlink" href="#sklearn-cross-validation-stratifiedshufflesplit" 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.StratifiedShuffleSplit">
<em class="property">class </em><code class="descclassname">sklearn.cross_validation.</code><code class="descname">StratifiedShuffleSplit</code><span class="sig-paren">(</span><em>y</em>, <em>n_iter=10</em>, <em>test_size=0.1</em>, <em>train_size=None</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#L999"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cross_validation.StratifiedShuffleSplit" title="Permalink to this definition">¶</a></dt>
<dd><p>Stratified ShuffleSplit 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.StratifiedShuffleSplit.html#sklearn.model_selection.StratifiedShuffleSplit" title="sklearn.model_selection.StratifiedShuffleSplit"><code class="xref py py-class docutils literal"><span class="pre">sklearn.model_selection.StratifiedShuffleSplit</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 merge of StratifiedKFold and
ShuffleSplit, which returns stratified randomized folds. The folds
are made by preserving the percentage of samples for each class.</p>
<p>Note: like the ShuffleSplit strategy, stratified random splits
do not guarantee that all folds will be different, although this is
still very likely for sizeable datasets.</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, [n_samples]</p>
<blockquote>
<div><p>Labels of samples.</p>
</div></blockquote>
<p><strong>n_iter</strong> : int (default 10)</p>
<blockquote>
<div><p>Number of re-shuffling & splitting iterations.</p>
</div></blockquote>
<p><strong>test_size</strong> : float (default 0.1), int, or None</p>
<blockquote>
<div><p>If float, should be between 0.0 and 1.0 and represent the
proportion of the dataset to include in the test split. If
int, represents the absolute number of test samples. If None,
the value is automatically set to the complement of the train size.</p>
</div></blockquote>
<p><strong>train_size</strong> : float, int, or None (default is None)</p>
<blockquote>
<div><p>If float, should be between 0.0 and 1.0 and represent the
proportion of the dataset to include in the train split. If
int, represents the absolute number of train samples. If None,
the value is automatically set to the complement of the test size.</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>.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<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">StratifiedShuffleSplit</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">sss</span> <span class="o">=</span> <span class="n">StratifiedShuffleSplit</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="gp">>>> </span><span class="nb">len</span><span class="p">(</span><span class="n">sss</span><span class="p">)</span>
<span class="go">3</span>
<span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">sss</span><span class="p">)</span>
<span class="go">StratifiedShuffleSplit(labels=[0 0 1 1], n_iter=3, ...)</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">sss</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 2] TEST: [3 0]</span>
<span class="go">TRAIN: [0 2] TEST: [1 3]</span>
<span class="go">TRAIN: [0 2] TEST: [3 1]</span>
</pre></div>
</div>
<dl class="method">
<dt id="sklearn.cross_validation.StratifiedShuffleSplit.__init__">
<code class="descname">__init__</code><span class="sig-paren">(</span><em>y</em>, <em>n_iter=10</em>, <em>test_size=0.1</em>, <em>train_size=None</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#L1063"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cross_validation.StratifiedShuffleSplit.__init__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
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