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banditpam: Almost Linear-Time k-Medoids Clustering

Interface to a high-performance implementation of k-medoids clustering described in Tiwari, Zhang, Mayclin, Thrun, Piech and Shomorony (2020) "BanditPAM: Almost Linear Time k-medoids Clustering via Multi-Armed Bandits" <https://proceedings.neurips.cc/paper/2020/file/73b817090081cef1bca77232f4532c5d-Paper.pdf>.

Version: 1.0-2 Depends: R (≥ 3.5.0) Imports: R6, Rcpp LinkingTo: Rcpp, RcppArmadillo Suggests: ggplot2, knitr, MASS, rmarkdown, tinytest Published: 2025-06-02 DOI: 10.32614/CRAN.package.banditpam Author: Balasubramanian Narasimhan [aut, cre], Mo Tiwari [aut] (https://motiwari.com) Maintainer: Balasubramanian Narasimhan <naras at stanford.edu> BugReports: https://github.com/motiwari/BanditPAM/issues License: MIT + file LICENSE NeedsCompilation: yes SystemRequirements: C++17 Materials: README NEWS CRAN checks: banditpam results Documentation: Reference manual: banditpam.pdf Vignettes: Almost Linear-Time k-Medoids Clustering (source, R code)
Downloads: Package source: banditpam_1.0-2.tar.gz Windows binaries: r-devel: banditpam_1.0-2.zip, r-release: banditpam_1.0-2.zip, r-oldrel: banditpam_1.0-2.zip macOS binaries: r-release (arm64): banditpam_1.0-2.tgz, r-oldrel (arm64): banditpam_1.0-2.tgz, r-release (x86_64): banditpam_1.0-2.tgz, r-oldrel (x86_64): banditpam_1.0-2.tgz Old sources: banditpam archive Linking:

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