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"""
Vector Quantization / Kmeans
============================

    Clustering algorithms are useful in information theory, target detection,
    communications, compression, and other areas. The vq module only
    supports vector quantization and the k-means algorithms. Development
    of self-organizing maps (SOM) and other approaches is underway.

Hierarchical Clustering
=======================

    The hierarchy module provides functions for hierarchical and agglomerative
    clustering. Its features include generating hierarchical clusters from
    distance matrices, computing distance matrices from observation vectors,
    calculating statistics on clusters, cutting linkages to generate flat
    clusters, and visualizing clusters with dendrograms.

Distance Computation
====================

    The distance module provides functions for computing distances between
    pairs of vectors from a set of observation vectors.

"""