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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 + fileLICENSE
NeedsCompilation:yes
SystemRequirements:C++17
Materials:README,NEWS
CRAN checks:banditpam results

Documentation:

Reference manual:banditpam.html ,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:

Please use the canonical formhttps://CRAN.R-project.org/package=banditpamto link to this page.


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