Computation times

01:07.310 total execution time for auto_examples_cluster files:

Comparing different clustering algorithms on toy datasets (plot_cluster_comparison.py)	00:22.260	0.0 MB
Empirical evaluation of the impact of k-means initialization (plot_kmeans_stability_low_dim_dense.py)	00:12.481	0.0 MB
Segmenting the picture of greek coins in regions (plot_coin_segmentation.py)	00:06.709	0.0 MB
Compare BIRCH and MiniBatchKMeans (plot_birch_vs_minibatchkmeans.py)	00:03.551	0.0 MB
Various Agglomerative Clustering on a 2D embedding of digits (plot_digits_linkage.py)	00:01.988	0.0 MB
Selecting the number of clusters with silhouette analysis on KMeans clustering (plot_kmeans_silhouette_analysis.py)	00:01.819	0.0 MB
Comparing different hierarchical linkage methods on toy datasets (plot_linkage_comparison.py)	00:01.814	0.0 MB
Vector Quantization Example (plot_face_compress.py)	00:01.704	0.0 MB
Agglomerative clustering with and without structure (plot_agglomerative_clustering.py)	00:01.684	0.0 MB
Inductive Clustering (plot_inductive_clustering.py)	00:01.564	0.0 MB
A demo of K-Means clustering on the handwritten digits data (plot_kmeans_digits.py)	00:01.477	0.0 MB
Spectral clustering for image segmentation (plot_segmentation_toy.py)	00:01.304	0.0 MB
Demonstration of k-means assumptions (plot_kmeans_assumptions.py)	00:01.250	0.0 MB
Comparison of the K-Means and MiniBatchKMeans clustering algorithms (plot_mini_batch_kmeans.py)	00:01.045	0.0 MB
Agglomerative clustering with different metrics (plot_agglomerative_clustering_metrics.py)	00:01.008	0.0 MB
Adjustment for chance in clustering performance evaluation (plot_adjusted_for_chance_measures.py)	00:00.912	0.0 MB
Demo of OPTICS clustering algorithm (plot_optics.py)	00:00.869	0.0 MB
A demo of structured Ward hierarchical clustering on an image of coins (plot_coin_ward_segmentation.py)	00:00.523	0.0 MB
Feature agglomeration vs. univariate selection (plot_feature_agglomeration_vs_univariate_selection.py)	00:00.519	0.0 MB
Color Quantization using K-Means (plot_color_quantization.py)	00:00.496	0.0 MB
K-means Clustering (plot_cluster_iris.py)	00:00.480	0.0 MB
Bisecting K-Means and Regular K-Means Performance Comparison (plot_bisect_kmeans.py)	00:00.407	0.0 MB
A demo of the mean-shift clustering algorithm (plot_mean_shift.py)	00:00.379	0.0 MB
Hierarchical clustering: structured vs unstructured ward (plot_ward_structured_vs_unstructured.py)	00:00.348	0.0 MB
Demo of affinity propagation clustering algorithm (plot_affinity_propagation.py)	00:00.271	0.0 MB
Feature agglomeration (plot_digits_agglomeration.py)	00:00.198	0.0 MB
Demo of DBSCAN clustering algorithm (plot_dbscan.py)	00:00.096	0.0 MB
Plot Hierarchical Clustering Dendrogram (plot_agglomerative_dendrogram.py)	00:00.087	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