Computation times¶
02:23.515 total execution time for auto_examples_cluster files:
Various Agglomerative Clustering on a 2D embedding of digits ( |
00:53.136 |
0.0 MB |
Comparing different clustering algorithms on toy datasets ( |
00:39.138 |
0.0 MB |
Compare BIRCH and MiniBatchKMeans ( |
00:13.271 |
0.0 MB |
Segmenting the picture of greek coins in regions ( |
00:05.869 |
0.0 MB |
Online learning of a dictionary of parts of faces ( |
00:05.075 |
0.0 MB |
Empirical evaluation of the impact of k-means initialization ( |
00:02.984 |
0.0 MB |
Inductive Clustering ( |
00:02.814 |
0.0 MB |
Vector Quantization Example ( |
00:02.564 |
0.0 MB |
Comparing different hierarchical linkage methods on toy datasets ( |
00:02.563 |
0.0 MB |
Agglomerative clustering with and without structure ( |
00:02.462 |
0.0 MB |
Demo of OPTICS clustering algorithm ( |
00:01.557 |
0.0 MB |
Selecting the number of clusters with silhouette analysis on KMeans clustering ( |
00:01.553 |
0.0 MB |
Color Quantization using K-Means ( |
00:01.457 |
0.0 MB |
Agglomerative clustering with different metrics ( |
00:01.343 |
0.0 MB |
Adjustment for chance in clustering performance evaluation ( |
00:01.165 |
0.0 MB |
A demo of K-Means clustering on the handwritten digits data ( |
00:01.099 |
0.0 MB |
Spectral clustering for image segmentation ( |
00:00.730 |
0.0 MB |
Feature agglomeration vs. univariate selection ( |
00:00.638 |
0.0 MB |
A demo of the mean-shift clustering algorithm ( |
00:00.611 |
0.0 MB |
A demo of structured Ward hierarchical clustering on an image of coins ( |
00:00.599 |
0.0 MB |
Demonstration of k-means assumptions ( |
00:00.578 |
0.0 MB |
Hierarchical clustering: structured vs unstructured ward ( |
00:00.474 |
0.0 MB |
K-means Clustering ( |
00:00.463 |
0.0 MB |
Demo of affinity propagation clustering algorithm ( |
00:00.427 |
0.0 MB |
Feature agglomeration ( |
00:00.273 |
0.0 MB |
Comparison of the K-Means and MiniBatchKMeans clustering algorithms ( |
00:00.267 |
0.0 MB |
Plot Hierarchical Clustering Dendrogram ( |
00:00.153 |
0.0 MB |
Demo of DBSCAN clustering algorithm ( |
00:00.153 |
0.0 MB |
An example of K-Means++ initialization ( |
00:00.098 |
0.0 MB |