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<li><a class="reference internal" href="#">Computation times</a></li>
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<div class="section" id="computation-times">
<span id="sphx-glr-auto-examples-neighbors-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
<p><strong>00:45.178</strong> total execution time for <strong>auto_examples_neighbors</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
<col style="width: 8%" />
<col style="width: 7%" />
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<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_nca_classification.html#sphx-glr-auto-examples-neighbors-plot-nca-classification-py"><span class="std std-ref">Comparing Nearest Neighbors with and without Neighborhood Components Analysis</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_nca_classification.py</span></code>)</p></td>
<td><p>00:18.150</p></td>
<td><p>12.1 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_species_kde.html#sphx-glr-auto-examples-neighbors-plot-species-kde-py"><span class="std std-ref">Kernel Density Estimate of Species Distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_species_kde.py</span></code>)</p></td>
<td><p>00:06.553</p></td>
<td><p>59.9 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_caching_nearest_neighbors.html#sphx-glr-auto-examples-neighbors-plot-caching-nearest-neighbors-py"><span class="std std-ref">Caching nearest neighbors</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_caching_nearest_neighbors.py</span></code>)</p></td>
<td><p>00:05.303</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_digits_kde_sampling.html#sphx-glr-auto-examples-neighbors-plot-digits-kde-sampling-py"><span class="std std-ref">Kernel Density Estimation</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_digits_kde_sampling.py</span></code>)</p></td>
<td><p>00:04.927</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_nca_dim_reduction.html#sphx-glr-auto-examples-neighbors-plot-nca-dim-reduction-py"><span class="std std-ref">Dimensionality Reduction with Neighborhood Components Analysis</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_nca_dim_reduction.py</span></code>)</p></td>
<td><p>00:02.726</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_classification.html#sphx-glr-auto-examples-neighbors-plot-classification-py"><span class="std std-ref">Nearest Neighbors Classification</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_classification.py</span></code>)</p></td>
<td><p>00:02.022</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_nca_illustration.html#sphx-glr-auto-examples-neighbors-plot-nca-illustration-py"><span class="std std-ref">Neighborhood Components Analysis Illustration</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_nca_illustration.py</span></code>)</p></td>
<td><p>00:01.758</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_lof_novelty_detection.html#sphx-glr-auto-examples-neighbors-plot-lof-novelty-detection-py"><span class="std std-ref">Novelty detection with Local Outlier Factor (LOF)</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_lof_novelty_detection.py</span></code>)</p></td>
<td><p>00:00.984</p></td>
<td><p>157.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_kde_1d.html#sphx-glr-auto-examples-neighbors-plot-kde-1d-py"><span class="std std-ref">Simple 1D Kernel Density Estimation</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_kde_1d.py</span></code>)</p></td>
<td><p>00:00.880</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_nearest_centroid.html#sphx-glr-auto-examples-neighbors-plot-nearest-centroid-py"><span class="std std-ref">Nearest Centroid Classification</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_nearest_centroid.py</span></code>)</p></td>
<td><p>00:00.690</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_regression.html#sphx-glr-auto-examples-neighbors-plot-regression-py"><span class="std std-ref">Nearest Neighbors regression</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_regression.py</span></code>)</p></td>
<td><p>00:00.610</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_lof_outlier_detection.html#sphx-glr-auto-examples-neighbors-plot-lof-outlier-detection-py"><span class="std std-ref">Outlier detection with Local Outlier Factor (LOF)</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_lof_outlier_detection.py</span></code>)</p></td>
<td><p>00:00.575</p></td>
<td><p>8.3 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="approximate_nearest_neighbors.html#sphx-glr-auto-examples-neighbors-approximate-nearest-neighbors-py"><span class="std std-ref">Approximate nearest neighbors in TSNE</span></a> (<code class="docutils literal notranslate"><span class="pre">approximate_nearest_neighbors.py</span></code>)</p></td>
<td><p>00:00.000</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
</table>
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