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: 1.4-0
Depends: R (≥ 2.14.0), graphics, grid, lattice, modeltools
Imports: methods, parallel, stats, stats4, class
Suggests: ellipse, clue, cluster, seriation, skmeans
Published: 2018-09-24
Author: Friedrich Leisch ORCID iD [aut, cre], Evgenia Dimitriadou [ctb], Bettina Gruen ORCID iD [aut]
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_1.4-0.tar.gz
Windows binaries: r-devel: flexclust_1.4-0.zip, r-release: flexclust_1.4-0.zip, r-oldrel: flexclust_1.4-0.zip
macOS binaries: r-release: flexclust_1.4-0.tgz, r-oldrel: flexclust_1.4-0.tgz
Old sources: flexclust archive

Reverse dependencies:

Reverse depends: mcen, ockc, RSKC
Reverse imports: AurieLSHGaussian, BCA, biclust, bootcluster, dtwclust, expands, fdm2id, mnem, semiArtificial, TMixClust, Xplortext
Reverse suggests: aurelius, FCPS, FeatureImpCluster, MVA, OTclust, wrMisc
Reverse enhances: clue

Linking:

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