Computation times

01:08.988 total execution time for auto_examples_cluster files:

Online learning of a dictionary of parts of faces (plot_dict_face_patches.py)	00:29.199	0.0 MB
Demo of HDBSCAN clustering algorithm (plot_hdbscan.py)	00:09.491	0.0 MB
Segmenting the picture of greek coins in regions (plot_coin_segmentation.py)	00:06.290	0.0 MB
Comparing different clustering algorithms on toy datasets (plot_cluster_comparison.py)	00:04.017	0.0 MB
Compare BIRCH and MiniBatchKMeans (plot_birch_vs_minibatchkmeans.py)	00:02.935	0.0 MB
Various Agglomerative Clustering on a 2D embedding of digits (plot_digits_linkage.py)	00:01.611	0.0 MB
Vector Quantization Example (plot_face_compress.py)	00:01.380	0.0 MB
Bisecting K-Means and Regular K-Means Performance Comparison (plot_bisect_kmeans.py)	00:01.317	0.0 MB
Inductive Clustering (plot_inductive_clustering.py)	00:01.302	0.0 MB
Agglomerative clustering with and without structure (plot_agglomerative_clustering.py)	00:01.230	0.0 MB
Comparing different hierarchical linkage methods on toy datasets (plot_linkage_comparison.py)	00:01.191	0.0 MB
Spectral clustering for image segmentation (plot_segmentation_toy.py)	00:01.148	0.0 MB
Empirical evaluation of the impact of k-means initialization (plot_kmeans_stability_low_dim_dense.py)	00:00.994	0.0 MB
Selecting the number of clusters with silhouette analysis on KMeans clustering (plot_kmeans_silhouette_analysis.py)	00:00.975	0.0 MB
Demonstration of k-means assumptions (plot_kmeans_assumptions.py)	00:00.766	0.0 MB
Agglomerative clustering with different metrics (plot_agglomerative_clustering_metrics.py)	00:00.746	0.0 MB
Demo of OPTICS clustering algorithm (plot_optics.py)	00:00.729	0.0 MB
A demo of K-Means clustering on the handwritten digits data (plot_kmeans_digits.py)	00:00.682	0.0 MB
Adjustment for chance in clustering performance evaluation (plot_adjusted_for_chance_measures.py)	00:00.650	0.0 MB
Feature agglomeration vs. univariate selection (plot_feature_agglomeration_vs_univariate_selection.py)	00:00.460	0.0 MB
Color Quantization using K-Means (plot_color_quantization.py)	00:00.306	0.0 MB
A demo of the mean-shift clustering algorithm (plot_mean_shift.py)	00:00.263	0.0 MB
Hierarchical clustering: structured vs unstructured ward (plot_ward_structured_vs_unstructured.py)	00:00.242	0.0 MB
A demo of structured Ward hierarchical clustering on an image of coins (plot_coin_ward_segmentation.py)	00:00.217	0.0 MB
K-means Clustering (plot_cluster_iris.py)	00:00.200	0.0 MB
Demo of affinity propagation clustering algorithm (plot_affinity_propagation.py)	00:00.194	0.0 MB
Demo of DBSCAN clustering algorithm (plot_dbscan.py)	00:00.129	0.0 MB
Comparison of the K-Means and MiniBatchKMeans clustering algorithms (plot_mini_batch_kmeans.py)	00:00.126	0.0 MB
Feature agglomeration (plot_digits_agglomeration.py)	00:00.090	0.0 MB
Plot Hierarchical Clustering Dendrogram (plot_agglomerative_dendrogram.py)	00:00.065	0.0 MB
An example of K-Means++ initialization (plot_kmeans_plusplus.py)	00:00.044	0.0 MB