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<section id="computation-times">
<span id="sphx-glr-auto-examples-cluster-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">¶</a></h1>
<p><strong>00:56.144</strong> total execution time for 31 files <strong>from auto_examples/cluster</strong>:</p>
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<thead>
<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>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="plot_hdbscan.html#sphx-glr-auto-examples-cluster-plot-hdbscan-py"><span class="std std-ref">Demo of HDBSCAN clustering algorithm</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_hdbscan.py</span></code>)</p></td>
<td><p>00:15.242</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_cluster_comparison.html#sphx-glr-auto-examples-cluster-plot-cluster-comparison-py"><span class="std std-ref">Comparing different clustering algorithms on toy datasets</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_cluster_comparison.py</span></code>)</p></td>
<td><p>00:06.252</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_coin_segmentation.html#sphx-glr-auto-examples-cluster-plot-coin-segmentation-py"><span class="std std-ref">Segmenting the picture of greek coins in regions</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_coin_segmentation.py</span></code>)</p></td>
<td><p>00:04.996</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_birch_vs_minibatchkmeans.html#sphx-glr-auto-examples-cluster-plot-birch-vs-minibatchkmeans-py"><span class="std std-ref">Compare BIRCH and MiniBatchKMeans</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_birch_vs_minibatchkmeans.py</span></code>)</p></td>
<td><p>00:03.642</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_dict_face_patches.html#sphx-glr-auto-examples-cluster-plot-dict-face-patches-py"><span class="std std-ref">Online learning of a dictionary of parts of faces</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_dict_face_patches.py</span></code>)</p></td>
<td><p>00:03.550</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_face_compress.html#sphx-glr-auto-examples-cluster-plot-face-compress-py"><span class="std std-ref">Vector Quantization Example</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_face_compress.py</span></code>)</p></td>
<td><p>00:02.095</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_inductive_clustering.html#sphx-glr-auto-examples-cluster-plot-inductive-clustering-py"><span class="std std-ref">Inductive Clustering</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_inductive_clustering.py</span></code>)</p></td>
<td><p>00:01.989</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_agglomerative_clustering.html#sphx-glr-auto-examples-cluster-plot-agglomerative-clustering-py"><span class="std std-ref">Agglomerative clustering with and without structure</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_agglomerative_clustering.py</span></code>)</p></td>
<td><p>00:01.933</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_linkage_comparison.html#sphx-glr-auto-examples-cluster-plot-linkage-comparison-py"><span class="std std-ref">Comparing different hierarchical linkage methods on toy datasets</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_linkage_comparison.py</span></code>)</p></td>
<td><p>00:01.835</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_optics.html#sphx-glr-auto-examples-cluster-plot-optics-py"><span class="std std-ref">Demo of OPTICS clustering algorithm</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_optics.py</span></code>)</p></td>
<td><p>00:01.639</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_digits_linkage.html#sphx-glr-auto-examples-cluster-plot-digits-linkage-py"><span class="std std-ref">Various Agglomerative Clustering on a 2D embedding of digits</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_digits_linkage.py</span></code>)</p></td>
<td><p>00:01.559</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_kmeans_stability_low_dim_dense.html#sphx-glr-auto-examples-cluster-plot-kmeans-stability-low-dim-dense-py"><span class="std std-ref">Empirical evaluation of the impact of k-means initialization</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_kmeans_stability_low_dim_dense.py</span></code>)</p></td>
<td><p>00:01.370</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_kmeans_silhouette_analysis.html#sphx-glr-auto-examples-cluster-plot-kmeans-silhouette-analysis-py"><span class="std std-ref">Selecting the number of clusters with silhouette analysis on KMeans clustering</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_kmeans_silhouette_analysis.py</span></code>)</p></td>
<td><p>00:01.140</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_kmeans_assumptions.html#sphx-glr-auto-examples-cluster-plot-kmeans-assumptions-py"><span class="std std-ref">Demonstration of k-means assumptions</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_kmeans_assumptions.py</span></code>)</p></td>
<td><p>00:01.087</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_agglomerative_clustering_metrics.html#sphx-glr-auto-examples-cluster-plot-agglomerative-clustering-metrics-py"><span class="std std-ref">Agglomerative clustering with different metrics</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_agglomerative_clustering_metrics.py</span></code>)</p></td>
<td><p>00:01.077</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_adjusted_for_chance_measures.html#sphx-glr-auto-examples-cluster-plot-adjusted-for-chance-measures-py"><span class="std std-ref">Adjustment for chance in clustering performance evaluation</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_adjusted_for_chance_measures.py</span></code>)</p></td>
<td><p>00:01.045</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_bisect_kmeans.html#sphx-glr-auto-examples-cluster-plot-bisect-kmeans-py"><span class="std std-ref">Bisecting K-Means and Regular K-Means Performance Comparison</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_bisect_kmeans.py</span></code>)</p></td>
<td><p>00:01.008</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_kmeans_digits.html#sphx-glr-auto-examples-cluster-plot-kmeans-digits-py"><span class="std std-ref">A demo of K-Means clustering on the handwritten digits data</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_kmeans_digits.py</span></code>)</p></td>
<td><p>00:00.724</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_color_quantization.html#sphx-glr-auto-examples-cluster-plot-color-quantization-py"><span class="std std-ref">Color Quantization using K-Means</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_color_quantization.py</span></code>)</p></td>
<td><p>00:00.531</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_segmentation_toy.html#sphx-glr-auto-examples-cluster-plot-segmentation-toy-py"><span class="std std-ref">Spectral clustering for image segmentation</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_segmentation_toy.py</span></code>)</p></td>
<td><p>00:00.514</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_feature_agglomeration_vs_univariate_selection.html#sphx-glr-auto-examples-cluster-plot-feature-agglomeration-vs-univariate-selection-py"><span class="std std-ref">Feature agglomeration vs. univariate selection</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_feature_agglomeration_vs_univariate_selection.py</span></code>)</p></td>
<td><p>00:00.499</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_mean_shift.html#sphx-glr-auto-examples-cluster-plot-mean-shift-py"><span class="std std-ref">A demo of the mean-shift clustering algorithm</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_mean_shift.py</span></code>)</p></td>
<td><p>00:00.404</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_coin_ward_segmentation.html#sphx-glr-auto-examples-cluster-plot-coin-ward-segmentation-py"><span class="std std-ref">A demo of structured Ward hierarchical clustering on an image of coins</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_coin_ward_segmentation.py</span></code>)</p></td>
<td><p>00:00.389</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_ward_structured_vs_unstructured.html#sphx-glr-auto-examples-cluster-plot-ward-structured-vs-unstructured-py"><span class="std std-ref">Hierarchical clustering: structured vs unstructured ward</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_ward_structured_vs_unstructured.py</span></code>)</p></td>
<td><p>00:00.363</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_affinity_propagation.html#sphx-glr-auto-examples-cluster-plot-affinity-propagation-py"><span class="std std-ref">Demo of affinity propagation clustering algorithm</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_affinity_propagation.py</span></code>)</p></td>
<td><p>00:00.314</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_cluster_iris.html#sphx-glr-auto-examples-cluster-plot-cluster-iris-py"><span class="std std-ref">K-means Clustering</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_cluster_iris.py</span></code>)</p></td>
<td><p>00:00.303</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_mini_batch_kmeans.html#sphx-glr-auto-examples-cluster-plot-mini-batch-kmeans-py"><span class="std std-ref">Comparison of the K-Means and MiniBatchKMeans clustering algorithms</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_mini_batch_kmeans.py</span></code>)</p></td>
<td><p>00:00.180</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_dbscan.html#sphx-glr-auto-examples-cluster-plot-dbscan-py"><span class="std std-ref">Demo of DBSCAN clustering algorithm</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_dbscan.py</span></code>)</p></td>
<td><p>00:00.167</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_digits_agglomeration.html#sphx-glr-auto-examples-cluster-plot-digits-agglomeration-py"><span class="std std-ref">Feature agglomeration</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_digits_agglomeration.py</span></code>)</p></td>
<td><p>00:00.135</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_agglomerative_dendrogram.html#sphx-glr-auto-examples-cluster-plot-agglomerative-dendrogram-py"><span class="std std-ref">Plot Hierarchical Clustering Dendrogram</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_agglomerative_dendrogram.py</span></code>)</p></td>
<td><p>00:00.104</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_kmeans_plusplus.html#sphx-glr-auto-examples-cluster-plot-kmeans-plusplus-py"><span class="std std-ref">An example of K-Means++ initialization</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_kmeans_plusplus.py</span></code>)</p></td>
<td><p>00:00.061</p></td>
<td><p>0.0</p></td>
</tr>
</tbody>
</table>
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