Computation times

00:43.484 total execution time for auto_examples_cluster files:

Segmenting the picture of greek coins in regions (plot_coin_segmentation.py)	00:07.722	0.0 MB
Comparing different clustering algorithms on toy datasets (plot_cluster_comparison.py)	00:06.290	0.0 MB
Compare BIRCH and MiniBatchKMeans (plot_birch_vs_minibatchkmeans.py)	00:03.526	0.0 MB
Empirical evaluation of the impact of k-means initialization (plot_kmeans_stability_low_dim_dense.py)	00:03.497	0.0 MB
Various Agglomerative Clustering on a 2D embedding of digits (plot_digits_linkage.py)	00:02.095	0.0 MB
A demo of K-Means clustering on the handwritten digits data (plot_kmeans_digits.py)	00:01.906	0.0 MB
Selecting the number of clusters with silhouette analysis on KMeans clustering (plot_kmeans_silhouette_analysis.py)	00:01.894	0.0 MB
Comparing different hierarchical linkage methods on toy datasets (plot_linkage_comparison.py)	00:01.826	0.0 MB
Vector Quantization Example (plot_face_compress.py)	00:01.731	0.0 MB
Spectral clustering for image segmentation (plot_segmentation_toy.py)	00:01.695	0.0 MB
Agglomerative clustering with and without structure (plot_agglomerative_clustering.py)	00:01.693	0.0 MB
Inductive Clustering (plot_inductive_clustering.py)	00:01.574	0.0 MB
Agglomerative clustering with different metrics (plot_agglomerative_clustering_metrics.py)	00:01.005	0.0 MB
Adjustment for chance in clustering performance evaluation (plot_adjusted_for_chance_measures.py)	00:00.912	0.0 MB
Feature agglomeration vs. univariate selection (plot_feature_agglomeration_vs_univariate_selection.py)	00:00.900	0.0 MB
Demo of OPTICS clustering algorithm (plot_optics.py)	00:00.861	0.0 MB
Hierarchical clustering: structured vs unstructured ward (plot_ward_structured_vs_unstructured.py)	00:00.610	0.0 MB
A demo of structured Ward hierarchical clustering on an image of coins (plot_coin_ward_segmentation.py)	00:00.557	0.0 MB
K-means Clustering (plot_cluster_iris.py)	00:00.547	0.0 MB
Color Quantization using K-Means (plot_color_quantization.py)	00:00.495	0.0 MB
Bisecting K-Means and Regular K-Means Performance Comparison (plot_bisect_kmeans.py)	00:00.405	0.0 MB
A demo of the mean-shift clustering algorithm (plot_mean_shift.py)	00:00.380	0.0 MB
Demonstration of k-means assumptions (plot_kmeans_assumptions.py)	00:00.379	0.0 MB
Demo of affinity propagation clustering algorithm (plot_affinity_propagation.py)	00:00.268	0.0 MB
Feature agglomeration (plot_digits_agglomeration.py)	00:00.211	0.0 MB
Comparison of the K-Means and MiniBatchKMeans clustering algorithms (plot_mini_batch_kmeans.py)	00:00.190	0.0 MB
Plot Hierarchical Clustering Dendrogram (plot_agglomerative_dendrogram.py)	00:00.154	0.0 MB
Demo of DBSCAN clustering algorithm (plot_dbscan.py)	00:00.094	0.0 MB
An example of K-Means++ initialization (plot_kmeans_plusplus.py)	00:00.064	0.0 MB
Online learning of a dictionary of parts of faces (plot_dict_face_patches.py)	00:00.002	0.0 MB