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flexclust

Flexible Cluster Algorithms

The main function kcca implements a general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further cluster methods include hard competitive learning, neural gas, and QT clustering. There are numerous visualization methods for cluster results (neighborhood graphs, convex cluster hulls, barcharts of centroids, ...), and bootstrap methods for the analysis of cluster stability.

Functions (43)

flexclust

Flexible Cluster Algorithms

v1.4-0
GPL-2
Authors
Friedrich Leisch [aut, cre] (<https://orcid.org/0000-0001-7278-1983>), Evgenia Dimitriadou [ctb], Bettina Gruen [aut] (<https://orcid.org/0000-0001-7265-4773>)
Initial release
2018-09-20

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