sklearn.cluster#

Popular unsupervised clustering algorithms.

User guide. See the Clustering and Biclustering sections for further details.

AffinityPropagation

Perform Affinity Propagation Clustering of data.

AgglomerativeClustering

Agglomerative Clustering.

Birch

Implements the BIRCH clustering algorithm.

BisectingKMeans

Bisecting K-Means clustering.

DBSCAN

Perform DBSCAN clustering from vector array or distance matrix.

FeatureAgglomeration

Agglomerate features.

HDBSCAN

Cluster data using hierarchical density-based clustering.

KMeans

K-Means clustering.

MeanShift

Mean shift clustering using a flat kernel.

MiniBatchKMeans

Mini-Batch K-Means clustering.

OPTICS

Estimate clustering structure from vector array.

SpectralBiclustering

Spectral biclustering (Kluger, 2003).

SpectralClustering

Apply clustering to a projection of the normalized Laplacian.

SpectralCoclustering

Spectral Co-Clustering algorithm (Dhillon, 2001).

affinity_propagation

Perform Affinity Propagation Clustering of data.

cluster_optics_dbscan

Perform DBSCAN extraction for an arbitrary epsilon.

cluster_optics_xi

Automatically extract clusters according to the Xi-steep method.

compute_optics_graph

Compute the OPTICS reachability graph.

dbscan

Perform DBSCAN clustering from vector array or distance matrix.

estimate_bandwidth

Estimate the bandwidth to use with the mean-shift algorithm.

k_means

Perform K-means clustering algorithm.

kmeans_plusplus

Init n_clusters seeds according to k-means++.

mean_shift

Perform mean shift clustering of data using a flat kernel.

spectral_clustering

Apply clustering to a projection of the normalized Laplacian.

ward_tree

Ward clustering based on a Feature matrix.