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<li><a class="reference internal" href="#">Computation times</a></li>
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<section id="computation-times">
<span id="sphx-glr-auto-examples-decomposition-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">¶</a></h1>
<p><strong>00:42.776</strong> total execution time for 11 files <strong>from auto_examples/decomposition</strong>:</p>
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<tr class="row-odd"><th class="head"><p>Example</p></th>
<th class="head"><p>Time</p></th>
<th class="head"><p>Mem (MB)</p></th>
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</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="plot_image_denoising.html#sphx-glr-auto-examples-decomposition-plot-image-denoising-py"><span class="std std-ref">Image denoising using dictionary learning</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_image_denoising.py</span></code>)</p></td>
<td><p>00:27.863</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_faces_decomposition.html#sphx-glr-auto-examples-decomposition-plot-faces-decomposition-py"><span class="std std-ref">Faces dataset decompositions</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_faces_decomposition.py</span></code>)</p></td>
<td><p>00:09.027</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_pca_vs_fa_model_selection.html#sphx-glr-auto-examples-decomposition-plot-pca-vs-fa-model-selection-py"><span class="std std-ref">Model selection with Probabilistic PCA and Factor Analysis (FA)</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_pca_vs_fa_model_selection.py</span></code>)</p></td>
<td><p>00:03.284</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_kernel_pca.html#sphx-glr-auto-examples-decomposition-plot-kernel-pca-py"><span class="std std-ref">Kernel PCA</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_kernel_pca.py</span></code>)</p></td>
<td><p>00:00.559</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_varimax_fa.html#sphx-glr-auto-examples-decomposition-plot-varimax-fa-py"><span class="std std-ref">Factor Analysis (with rotation) to visualize patterns</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_varimax_fa.py</span></code>)</p></td>
<td><p>00:00.439</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_ica_blind_source_separation.html#sphx-glr-auto-examples-decomposition-plot-ica-blind-source-separation-py"><span class="std std-ref">Blind source separation using FastICA</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_ica_blind_source_separation.py</span></code>)</p></td>
<td><p>00:00.421</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_ica_vs_pca.html#sphx-glr-auto-examples-decomposition-plot-ica-vs-pca-py"><span class="std std-ref">FastICA on 2D point clouds</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_ica_vs_pca.py</span></code>)</p></td>
<td><p>00:00.381</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_sparse_coding.html#sphx-glr-auto-examples-decomposition-plot-sparse-coding-py"><span class="std std-ref">Sparse coding with a precomputed dictionary</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_sparse_coding.py</span></code>)</p></td>
<td><p>00:00.281</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_incremental_pca.html#sphx-glr-auto-examples-decomposition-plot-incremental-pca-py"><span class="std std-ref">Incremental PCA</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_incremental_pca.py</span></code>)</p></td>
<td><p>00:00.244</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_pca_vs_lda.html#sphx-glr-auto-examples-decomposition-plot-pca-vs-lda-py"><span class="std std-ref">Comparison of LDA and PCA 2D projection of Iris dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_pca_vs_lda.py</span></code>)</p></td>
<td><p>00:00.195</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_pca_iris.html#sphx-glr-auto-examples-decomposition-plot-pca-iris-py"><span class="std std-ref">PCA example with Iris Data-set</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_pca_iris.py</span></code>)</p></td>
<td><p>00:00.079</p></td>
<td><p>0.0</p></td>
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