Clustering#
Examples concerning the sklearn.cluster
module.
A demo of K-Means clustering on the handwritten digits data
A demo of structured Ward hierarchical clustering on an image of coins
A demo of the mean-shift clustering algorithm
Adjustment for chance in clustering performance evaluation
Agglomerative clustering with and without structure
Agglomerative clustering with different metrics
An example of K-Means++ initialization
Bisecting K-Means and Regular K-Means Performance Comparison
Color Quantization using K-Means
Compare BIRCH and MiniBatchKMeans
Comparing different clustering algorithms on toy datasets
Comparing different hierarchical linkage methods on toy datasets
Comparison of the K-Means and MiniBatchKMeans clustering algorithms
Demo of DBSCAN clustering algorithm
Demo of HDBSCAN clustering algorithm
Demo of OPTICS clustering algorithm
Demo of affinity propagation clustering algorithm
Demonstration of k-means assumptions
Empirical evaluation of the impact of k-means initialization
Feature agglomeration vs. univariate selection
Hierarchical clustering: structured vs unstructured ward
Online learning of a dictionary of parts of faces
Plot Hierarchical Clustering Dendrogram
Segmenting the picture of greek coins in regions
Selecting the number of clusters with silhouette analysis on KMeans clustering
Spectral clustering for image segmentation
Various Agglomerative Clustering on a 2D embedding of digits