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<li><a class="reference internal" href="#"><code class="docutils literal"><span class="pre">sklearn.datasets</span></code>.fetch_california_housing</a><ul>
<li><a class="reference internal" href="#examples-using-sklearn-datasets-fetch-california-housing">Examples using <code class="docutils literal"><span class="pre">sklearn.datasets.fetch_california_housing</span></code></a></li>
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<div class="section" id="sklearn-datasets-fetch-california-housing">
<h1><a class="reference internal" href="../classes.html#module-sklearn.datasets" title="sklearn.datasets"><code class="xref py py-mod docutils literal"><span class="pre">sklearn.datasets</span></code></a>.fetch_california_housing<a class="headerlink" href="#sklearn-datasets-fetch-california-housing" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="sklearn.datasets.fetch_california_housing">
<code class="descclassname">sklearn.datasets.</code><code class="descname">fetch_california_housing</code><span class="sig-paren">(</span><em>data_home=None</em>, <em>download_if_missing=True</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/51a765a/sklearn/datasets/california_housing.py#L52"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.datasets.fetch_california_housing" title="Permalink to this definition">¶</a></dt>
<dd><p>Loader for the California housing dataset from StatLib.</p>
<p>Read more in the <a class="reference internal" href="../../datasets/index.html#datasets"><span>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>data_home</strong> : optional, default: None</p>
<blockquote>
<div><p>Specify another download and cache folder for the datasets. By default
all scikit learn data is stored in ‘~/scikit_learn_data’ subfolders.</p>
</div></blockquote>
<p><strong>download_if_missing: optional, True by default</strong> :</p>
<blockquote>
<div><p>If False, raise a IOError if the data is not locally available
instead of trying to download the data from the source site.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>dataset</strong> : dict-like object with the following attributes:</p>
<p><strong>dataset.data</strong> : ndarray, shape [20640, 8]</p>
<blockquote>
<div><p>Each row corresponding to the 8 feature values in order.</p>
</div></blockquote>
<p><strong>dataset.target</strong> : numpy array of shape (20640,)</p>
<blockquote>
<div><p>Each value corresponds to the average house value in units of 100,000.</p>
</div></blockquote>
<p><strong>dataset.feature_names</strong> : array of length 8</p>
<blockquote>
<div><p>Array of ordered feature names used in the dataset.</p>
</div></blockquote>
<p><strong>dataset.DESCR</strong> : string</p>
<blockquote class="last">
<div><p>Description of the California housing dataset.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Notes</p>
<p>This dataset consists of 20,640 samples and 9 features.</p>
</dd></dl>
<div class="section" id="examples-using-sklearn-datasets-fetch-california-housing">
<h2>Examples using <code class="docutils literal"><span class="pre">sklearn.datasets.fetch_california_housing</span></code><a class="headerlink" href="#examples-using-sklearn-datasets-fetch-california-housing" title="Permalink to this headline">¶</a></h2>
<div class="thumbnailContainer" tooltip="Partial dependence plots show the dependence between the target function [2]_ and a set of 'tar..."><div class="figure" id="id1">
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<p class="caption"><span class="caption-text"><a class="reference internal" href="../../auto_examples/ensemble/plot_partial_dependence.html#example-ensemble-plot-partial-dependence-py"><span>Partial Dependence Plots</span></a></span></p>
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