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.

Version: 1.3-4
Depends: R (≥ 2.14.0), graphics, grid, lattice, modeltools
Imports: methods, parallel, stats, stats4
Suggests: ellipse, clue, cluster, seriation
Published: 2013-07-02
Author: Friedrich Leisch [aut, cre], Evgenia Dimitriadou [ctb]
Maintainer: Friedrich Leisch <Friedrich.Leisch at R-project.org>
License: GPL-2
NeedsCompilation: yes
Citation: flexclust citation info
Materials: NEWS
In views: Cluster
CRAN checks: flexclust results

Downloads:

Reference manual: flexclust.pdf
Package source: flexclust_1.3-4.tar.gz
Windows binaries: r-devel: flexclust_1.3-4.zip, r-release: flexclust_1.3-4.zip, r-oldrel: flexclust_1.3-4.zip
OS X Snow Leopard binaries: r-release: flexclust_1.3-4.tgz, r-oldrel: flexclust_1.3-4.tgz
OS X Mavericks binaries: r-release: flexclust_1.3-4.tgz
Old sources: flexclust archive

Reverse dependencies:

Reverse depends: BCA, CONOR, CONORData, gcExplorer, RSKC
Reverse imports: gcExplorer
Reverse suggests: biclust, MVA
Reverse enhances: clue