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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

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

Feature agglomeration vs. univariate selection

Hierarchical clustering: structured vs unstructured ward

Inductive Clustering

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

Vector Quantization Example

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Licensed under the 3-clause BSD License.
https://scikit-learn.org/1.6/auto_examples/cluster/index.html