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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.
Getting started
Browse package contents
Package details |
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| Author | Friedrich Leisch [aut, cre] (<https://orcid.org/0000-0001-7278-1983>), Evgenia Dimitriadou [ctb], Bettina Gruen [ctb] (<https://orcid.org/0000-0001-7265-4773>) |
| Maintainer | Friedrich Leisch <Friedrich.Leisch@R-project.org> |
| License | GPL-2 |
| Version | 1.4-1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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