geokmeans: A Collection of Fast, Exact and Eco-Friendly k-Means Clustering Algorithms

A collection of fast k-means clustering algorithms under a single, uniform interface. The core method is Geometric-k-means, a bound-free algorithm of Sharma et al. (2026) <doi:10.1007/s10994-025-06891-1> that uses geometry to restrict computation to the data points able to change clusters, substantially reducing distance computations and runtime while returning the same result as standard k-means. Also included are Lloyd's algorithm, Elkan, Hamerly, Annulus, Exponion, and Ball k-means. All algorithms are implemented in 'C++' via 'Rcpp' and 'RcppEigen' and return the final centroids, optional per-point cluster assignments, and computational statistics.

Version:	0.1.0
Imports:	Rcpp
LinkingTo:	Rcpp, RcppEigen
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-06-22
DOI:	10.32614/CRAN.package.geokmeans
Author:	Parichit Sharma [aut, cre, cph], Hasan Kurban [aut]
Maintainer:	Parichit Sharma <parishar at iu.edu>
BugReports:	https://github.com/parichit/Geometric-k-means/issues
License:	GPL-3
URL:	https://github.com/parichit/Geometric-k-means
NeedsCompilation:	yes
SystemRequirements:	C++17
Citation:	geokmeans citation info
Materials:	README, NEWS
CRAN checks:	geokmeans results

Documentation:

Reference manual:	geokmeans.html , geokmeans.pdf
Vignettes:	Getting started with geokmeans (source, R code)

Downloads:

Package source:	geokmeans_0.1.0.tar.gz
Windows binaries:	r-devel: geokmeans_0.1.0.zip, r-release: geokmeans_0.1.0.zip, r-oldrel: geokmeans_0.1.0.zip
macOS binaries:	r-release (arm64): geokmeans_0.1.0.tgz, r-oldrel (arm64): geokmeans_0.1.0.tgz, r-release (x86_64): geokmeans_0.1.0.tgz, r-oldrel (x86_64): geokmeans_0.1.0.tgz

Linking:

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