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<li><a class="reference internal" href="#"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.datasets</span></code>.fetch_rcv1</a><ul>
<li><a class="reference internal" href="#sklearn.datasets.fetch_rcv1"><code class="docutils literal notranslate"><span class="pre">fetch_rcv1</span></code></a></li>
</ul>
</li>
</ul>
</div>
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<section id="sklearn-datasets-fetch-rcv1">
<h1><a class="reference internal" href="../classes.html#module-sklearn.datasets" title="sklearn.datasets"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.datasets</span></code></a>.fetch_rcv1<a class="headerlink" href="#sklearn-datasets-fetch-rcv1" title="Permalink to this heading">¶</a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="sklearn.datasets.fetch_rcv1">
<span class="sig-prename descclassname"><span class="pre">sklearn.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_rcv1</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subset</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'all'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">download_if_missing</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_X_y</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/702316c27/sklearn/datasets/_rcv1.py#L75"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sklearn.datasets.fetch_rcv1" title="Permalink to this definition">¶</a></dt>
<dd><p>Load the RCV1 multilabel dataset (classification).</p>
<p>Download it if necessary.</p>
<p>Version: RCV1-v2, vectors, full sets, topics multilabels.</p>
<table class="docutils align-default">
<tbody>
<tr class="row-odd"><td><p>Classes</p></td>
<td><p>103</p></td>
</tr>
<tr class="row-even"><td><p>Samples total</p></td>
<td><p>804414</p></td>
</tr>
<tr class="row-odd"><td><p>Dimensionality</p></td>
<td><p>47236</p></td>
</tr>
<tr class="row-even"><td><p>Features</p></td>
<td><p>real, between 0 and 1</p></td>
</tr>
</tbody>
</table>
<p>Read more in the <a class="reference internal" href="../../datasets/real_world.html#rcv1-dataset"><span class="std std-ref">User Guide</span></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.17.</span></p>
</div>
<dl class="field-list">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl>
<dt><strong>data_home</strong><span class="classifier">str, default=None</span></dt><dd><p>Specify another download and cache folder for the datasets. By default
all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.</p>
</dd>
<dt><strong>subset</strong><span class="classifier">{‘train’, ‘test’, ‘all’}, default=’all’</span></dt><dd><p>Select the dataset to load: ‘train’ for the training set
(23149 samples), ‘test’ for the test set (781265 samples),
‘all’ for both, with the training samples first if shuffle is False.
This follows the official LYRL2004 chronological split.</p>
</dd>
<dt><strong>download_if_missing</strong><span class="classifier">bool, default=True</span></dt><dd><p>If False, raise an OSError if the data is not locally available
instead of trying to download the data from the source site.</p>
</dd>
<dt><strong>random_state</strong><span class="classifier">int, RandomState instance or None, default=None</span></dt><dd><p>Determines random number generation for dataset shuffling. Pass an int
for reproducible output across multiple function calls.
See <a class="reference internal" href="../../glossary.html#term-random_state"><span class="xref std std-term">Glossary</span></a>.</p>
</dd>
<dt><strong>shuffle</strong><span class="classifier">bool, default=False</span></dt><dd><p>Whether to shuffle dataset.</p>
</dd>
<dt><strong>return_X_y</strong><span class="classifier">bool, default=False</span></dt><dd><p>If True, returns <code class="docutils literal notranslate"><span class="pre">(dataset.data,</span> <span class="pre">dataset.target)</span></code> instead of a Bunch
object. See below for more information about the <code class="docutils literal notranslate"><span class="pre">dataset.data</span></code> and
<code class="docutils literal notranslate"><span class="pre">dataset.target</span></code> object.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.20.</span></p>
</div>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl>
<dt><strong>dataset</strong><span class="classifier"><a class="reference internal" href="sklearn.utils.Bunch.html#sklearn.utils.Bunch" title="sklearn.utils.Bunch"><code class="xref py py-class docutils literal notranslate"><span class="pre">Bunch</span></code></a></span></dt><dd><p>Dictionary-like object. Returned only if <code class="docutils literal notranslate"><span class="pre">return_X_y</span></code> is False.
<code class="docutils literal notranslate"><span class="pre">dataset</span></code> has the following attributes:</p>
<ul class="simple">
<li><dl class="simple">
<dt>data<span class="classifier">sparse matrix of shape (804414, 47236), dtype=np.float64</span></dt><dd><p>The array has 0.16% of non zero values. Will be of CSR format.</p>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>target<span class="classifier">sparse matrix of shape (804414, 103), dtype=np.uint8</span></dt><dd><p>Each sample has a value of 1 in its categories, and 0 in others.
The array has 3.15% of non zero values. Will be of CSR format.</p>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>sample_id<span class="classifier">ndarray of shape (804414,), dtype=np.uint32,</span></dt><dd><p>Identification number of each sample, as ordered in dataset.data.</p>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>target_names<span class="classifier">ndarray of shape (103,), dtype=object</span></dt><dd><p>Names of each target (RCV1 topics), as ordered in dataset.target.</p>
</dd>
</dl>
</li>
<li><dl class="simple">
<dt>DESCR<span class="classifier">str</span></dt><dd><p>Description of the RCV1 dataset.</p>
</dd>
</dl>
</li>
</ul>
</dd>
<dt><strong>(data, target)</strong><span class="classifier">tuple</span></dt><dd><p>A tuple consisting of <code class="docutils literal notranslate"><span class="pre">dataset.data</span></code> and <code class="docutils literal notranslate"><span class="pre">dataset.target</span></code>, as
described above. Returned only if <code class="docutils literal notranslate"><span class="pre">return_X_y</span></code> is True.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.20.</span></p>
</div>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
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