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: 1.5.0 Depends: R (≥ 2.14.0) Imports: graphics, grid, lattice, methods, modeltools, parallel, stats, stats4, class Suggests: ellipse, clue, cluster, seriation, skmeans Published: 2025-02-28 DOI: 10.32614/CRAN.package.flexclust Author: Friedrich Leisch [aut] (maintainer up to 2024), Evgenia Dimitriadou [ctb], Lena Ortega Menjivar [ctb], Dominik Ernst [ctb], Bettina Grün [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 Documentation: Downloads: Reverse dependencies: Reverse depends: clusTransition, mcen, ockc, RSKC Reverse imports: AurieLSHGaussian, biclust, bnem, bootcluster, clustord, dtwclust, flexord, miclust, mnem, S4DM, semiArtificial, spconf, tidyclust, TMixClust, Xplortext Reverse suggests: cola, FCPS, fdm2id, FeatureImpCluster, lionfish, MVA, OTclust, simplifyEnrichment, wrMisc Reverse enhances: clue Linking:Please use the canonical form https://CRAN.R-project.org/package=flexclust to link to this page.
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