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<li><a class="reference internal" href="#"><code class="docutils literal"><span class="pre">sklearn.datasets</span></code>.make_sparse_spd_matrix</a><ul>
<li><a class="reference internal" href="#examples-using-sklearn-datasets-make-sparse-spd-matrix">Examples using <code class="docutils literal"><span class="pre">sklearn.datasets.make_sparse_spd_matrix</span></code></a></li>
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<div class="section" id="sklearn-datasets-make-sparse-spd-matrix">
<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>.make_sparse_spd_matrix<a class="headerlink" href="#sklearn-datasets-make-sparse-spd-matrix" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="sklearn.datasets.make_sparse_spd_matrix">
<code class="descclassname">sklearn.datasets.</code><code class="descname">make_sparse_spd_matrix</code><span class="sig-paren">(</span><em>dim=1</em>, <em>alpha=0.95</em>, <em>norm_diag=False</em>, <em>smallest_coef=0.1</em>, <em>largest_coef=0.9</em>, <em>random_state=None</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/51a765a/sklearn/datasets/samples_generator.py#L1186"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.datasets.make_sparse_spd_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Generate a sparse symmetric definite positive matrix.</p>
<p>Read more in the <a class="reference internal" href="../../datasets/index.html#sample-generators"><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>dim: integer, optional (default=1)</strong> :</p>
<blockquote>
<div><p>The size of the random matrix to generate.</p>
</div></blockquote>
<p><strong>alpha: float between 0 and 1, optional (default=0.95)</strong> :</p>
<blockquote>
<div><p>The probability that a coefficient is non zero (see notes).</p>
</div></blockquote>
<p><strong>random_state</strong> : int, RandomState instance or None, optional (default=None)</p>
<blockquote>
<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>
<p><strong>largest_coef</strong> : float between 0 and 1, optional (default=0.9)</p>
<blockquote>
<div><p>The value of the largest coefficient.</p>
</div></blockquote>
<p><strong>smallest_coef</strong> : float between 0 and 1, optional (default=0.1)</p>
<blockquote>
<div><p>The value of the smallest coefficient.</p>
</div></blockquote>
<p><strong>norm_diag</strong> : boolean, optional (default=False)</p>
<blockquote>
<div><p>Whether to normalize the output matrix to make the leading diagonal
elements all 1</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>prec</strong> : sparse matrix of shape (dim, dim)</p>
<blockquote class="last">
<div><p>The generated matrix.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="sklearn.datasets.make_spd_matrix.html#sklearn.datasets.make_spd_matrix" title="sklearn.datasets.make_spd_matrix"><code class="xref py py-obj docutils literal"><span class="pre">make_spd_matrix</span></code></a></p>
</div>
<p class="rubric">Notes</p>
<p>The sparsity is actually imposed on the cholesky factor of the matrix.
Thus alpha does not translate directly into the filling fraction of
the matrix itself.</p>
</dd></dl>
<div class="section" id="examples-using-sklearn-datasets-make-sparse-spd-matrix">
<h2>Examples using <code class="docutils literal"><span class="pre">sklearn.datasets.make_sparse_spd_matrix</span></code><a class="headerlink" href="#examples-using-sklearn-datasets-make-sparse-spd-matrix" title="Permalink to this headline">¶</a></h2>
<div class="thumbnailContainer" tooltip="Using the GraphLasso estimator to learn a covariance and sparse precision from a small number o..."><div class="figure" id="id1">
<a class="reference external image-reference" href="./../../auto_examples/covariance/plot_sparse_cov.html"><img alt="../../_images/plot_sparse_cov1.png" src="../../_images/plot_sparse_cov1.png" /></a>
<p class="caption"><span class="caption-text"><a class="reference internal" href="../../auto_examples/covariance/plot_sparse_cov.html#example-covariance-plot-sparse-cov-py"><span>Sparse inverse covariance estimation</span></a></span></p>
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