Flexible Cluster Algorithms R package flexclust version 1.5.0 CRAN Task View: Cluster (https://CRAN.R-project.org/view=Cluster) 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. Software Depends: R (>= 2.14.0) Imports: graphics, grid, lattice, methods, modeltools, parallel, stats, stats4, class Suggests: ellipse, clue, cluster, seriation, skmeans Bettina Grün <Bettina.Gruen@R-project.org> Comprehensive R Archive Network (CRAN) Friedrich Leisch [aut] (ORCID: <https://orcid.org/0000-0001-7278-1983>, maintainer up to 2024), Evgenia Dimitriadou [ctb], Lena Ortega Menjivar [ctb] (ORCID: <https://orcid.org/0000-0001-5785-4021>), Dominik Ernst [ctb] (ORCID: <https://orcid.org/0009-0005-5579-2636>), Bettina Grün [ctb, cre] (ORCID: <https://orcid.org/0000-0001-7265-4773>) GPL-2 2025-02-28 application/tgz https://CRAN.R-project.org/package=flexclust doi:10.32614/CRAN.package.flexclust