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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | geokmeans_0.1.0.tar.gz |
237.0 KiB |
0.1.0 |
rolling linux/noble R-4.5 | geokmeans_0.1.0.tar.gz |
242.0 KiB |
0.1.0 |
rolling source/ R- | geokmeans_0.1.0.tar.gz |
140.4 KiB |
0.1.0 |
latest linux/jammy R-4.5 | geokmeans_0.1.0.tar.gz |
237.0 KiB |
0.1.0 |
latest linux/noble R-4.5 | geokmeans_0.1.0.tar.gz |
242.0 KiB |
0.1.0 |
latest source/ R- | geokmeans_0.1.0.tar.gz |
140.4 KiB |
0.1.0 |
2026-04-23 source/ R- | geokmeans_0.1.0.tar.gz |
0 B |