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<ul>
<li><a class="reference internal" href="#"><code class="docutils literal"><span class="pre">sklearn.datasets</span></code>.make_sparse_coded_signal</a><ul>
<li><a class="reference internal" href="#examples-using-sklearn-datasets-make-sparse-coded-signal">Examples using <code class="docutils literal"><span class="pre">sklearn.datasets.make_sparse_coded_signal</span></code></a></li>
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<div class="section" id="sklearn-datasets-make-sparse-coded-signal">
<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_coded_signal<a class="headerlink" href="#sklearn-datasets-make-sparse-coded-signal" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="sklearn.datasets.make_sparse_coded_signal">
<code class="descclassname">sklearn.datasets.</code><code class="descname">make_sparse_coded_signal</code><span class="sig-paren">(</span><em>n_samples</em>, <em>n_components</em>, <em>n_features</em>, <em>n_nonzero_coefs</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#L1040"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.datasets.make_sparse_coded_signal" title="Permalink to this definition">¶</a></dt>
<dd><p>Generate a signal as a sparse combination of dictionary elements.</p>
<p>Returns a matrix Y = DX, such as D is (n_features, n_components),
X is (n_components, n_samples) and each column of X has exactly
n_nonzero_coefs non-zero elements.</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>n_samples</strong> : int</p>
<blockquote>
<div><p>number of samples to generate</p>
</div></blockquote>
<p><strong>n_components: int,</strong> :</p>
<blockquote>
<div><p>number of components in the dictionary</p>
</div></blockquote>
<p><strong>n_features</strong> : int</p>
<blockquote>
<div><p>number of features of the dataset to generate</p>
</div></blockquote>
<p><strong>n_nonzero_coefs</strong> : int</p>
<blockquote>
<div><p>number of active (non-zero) coefficients in each sample</p>
</div></blockquote>
<p><strong>random_state: int or RandomState instance, optional (default=None)</strong> :</p>
<blockquote>
<div><p>seed used by the pseudo random number generator</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>data: array of shape [n_features, n_samples]</strong> :</p>
<blockquote>
<div><p>The encoded signal (Y).</p>
</div></blockquote>
<p><strong>dictionary: array of shape [n_features, n_components]</strong> :</p>
<blockquote>
<div><p>The dictionary with normalized components (D).</p>
</div></blockquote>
<p><strong>code: array of shape [n_components, n_samples]</strong> :</p>
<blockquote class="last">
<div><p>The sparse code such that each column of this matrix has exactly
n_nonzero_coefs non-zero items (X).</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<div class="section" id="examples-using-sklearn-datasets-make-sparse-coded-signal">
<h2>Examples using <code class="docutils literal"><span class="pre">sklearn.datasets.make_sparse_coded_signal</span></code><a class="headerlink" href="#examples-using-sklearn-datasets-make-sparse-coded-signal" title="Permalink to this headline">¶</a></h2>
<div class="thumbnailContainer" tooltip="Using orthogonal matching pursuit for recovering a sparse signal from a noisy measurement encod..."><div class="figure" id="id1">
<a class="reference external image-reference" href="./../../auto_examples/linear_model/plot_omp.html"><img alt="../../_images/plot_omp1.png" src="../../_images/plot_omp1.png" /></a>
<p class="caption"><span class="caption-text"><a class="reference internal" href="../../auto_examples/linear_model/plot_omp.html#example-linear-model-plot-omp-py"><span>Orthogonal Matching Pursuit</span></a></span></p>
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