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<div class="section" id="sklearn-covariance-shrunk-covariance">
<h1><a class="reference internal" href="../classes.html#module-sklearn.covariance" title="sklearn.covariance"><code class="xref py py-mod docutils literal"><span class="pre">sklearn.covariance</span></code></a>.shrunk_covariance<a class="headerlink" href="#sklearn-covariance-shrunk-covariance" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="sklearn.covariance.shrunk_covariance">
<code class="descclassname">sklearn.covariance.</code><code class="descname">shrunk_covariance</code><span class="sig-paren">(</span><em>emp_cov</em>, <em>shrinkage=0.1</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/51a765a/sklearn/covariance/shrunk_covariance_.py#L27"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.covariance.shrunk_covariance" title="Permalink to this definition">¶</a></dt>
<dd><p>Calculates a covariance matrix shrunk on the diagonal</p>
<p>Read more in the <a class="reference internal" href="../covariance.html#shrunk-covariance"><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>emp_cov</strong> : array-like, shape (n_features, n_features)</p>
<blockquote>
<div><p>Covariance matrix to be shrunk</p>
</div></blockquote>
<p><strong>shrinkage</strong> : float, 0 <= shrinkage <= 1</p>
<blockquote>
<div><p>Coefficient in the convex combination used for the computation
of the shrunk estimate.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>shrunk_cov</strong> : array-like</p>
<blockquote class="last">
<div><p>Shrunk covariance.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Notes</p>
<p>The regularized (shrunk) covariance is given by</p>
<dl class="docutils">
<dt>(1 - shrinkage)*cov</dt>
<dd><ul class="first last simple">
<li>shrinkage*mu*np.identity(n_features)</li>
</ul>
</dd>
</dl>
<p>where mu = trace(cov) / n_features</p>
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