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: 1.4-2
Depends: R (≥ 2.14.0), graphics, grid, lattice, modeltools
Imports: methods, parallel, stats, stats4, class
Suggests: ellipse, clue, cluster, seriation, skmeans
Published: 2024-04-27
DOI: 10.32614/CRAN.package.flexclust
Author: Friedrich Leisch ORCID iD [aut] (maintainer up to 2024), Evgenia Dimitriadou [ctb], Bettina Grün ORCID iD [ctb, cre]
Maintainer: Bettina Grün <Bettina.Gruen at R-project.org>
License: GPL-2
NeedsCompilation: yes
Citation: flexclust citation info
Materials: NEWS
In views: Cluster
CRAN checks: flexclust results


Reference manual: flexclust.pdf


Package source: flexclust_1.4-2.tar.gz
Windows binaries: r-devel: flexclust_1.4-2.zip, r-release: flexclust_1.4-2.zip, r-oldrel: flexclust_1.4-2.zip
macOS binaries: r-release (arm64): flexclust_1.4-2.tgz, r-oldrel (arm64): flexclust_1.4-2.tgz, r-release (x86_64): flexclust_1.4-2.tgz, r-oldrel (x86_64): flexclust_1.4-2.tgz
Old sources: flexclust archive

Reverse dependencies:

Reverse depends: clusTransition, mcen, ockc, RSKC
Reverse imports: AurieLSHGaussian, biclust, bnem, bootcluster, dtwclust, miclust, mnem, semiArtificial, tidyclust, TMixClust, Xplortext
Reverse suggests: cola, FCPS, fdm2id, FeatureImpCluster, MVA, OTclust, simplifyEnrichment, wrMisc
Reverse enhances: clue


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