This is a two-in-one package which provides interfaces to both R and 'Python'. It implements fast hierarchical, agglomerative clustering routines. Part of the functionality is designed as drop-in replacement for existing routines: linkage() in the 'SciPy' package 'scipy.cluster.hierarchy', hclust() in R's 'stats' package, and the 'flashClust' package. It provides the same functionality with the benefit of a much faster implementation. Moreover, there are memory-saving routines for clustering of vector data, which go beyond what the existing packages provide. For information on how to install the 'Python' files, see the file INSTALL in the source distribution. Based on the present package, Christoph Dalitz also wrote a pure 'C++' interface to 'fastcluster': <https://lionel.kr.hs-niederrhein.de/~dalitz/data/hclust/>.
Documentation: Downloads: Reverse dependencies: Reverse depends: bahc, cummeRbund, ICGE, PropClust, WGCNA Reverse imports: adductomicsR, bioregion, CEMiTool, ClustAssess, cogena, cstab, disto, funMoDisco, FuseSOM, geva, heatmap3, hierGWAS, HierPortfolios, hypervolume, iheatmapr, ILoReg, infercnv, Linnorm, maotai, mappeR, MetaCyto, MetProc, MLGL, mousetrap, MRPC, msPurity, NPflow, pagoda2, PhyloProfile, RAFS, scGPS, SPARTAAS, SpatialVx, visxhclust, VoxR, WeightedCluster Reverse suggests: bluster, ComplexHeatmap, familiar, FCPS, hyperSpec, IncDTW, MapperAlgo, MSCA, scde, TRexSelector Linking:Please use the canonical form https://CRAN.R-project.org/package=fastcluster to link to this page.
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