Efficient Implementation of K-Means++ Algorithm R package tglkmeans version 0.6.1 Efficient implementation of K-Means++ algorithm. For more information see (1) "kmeans++ the advantages of the k-means++ algorithm" by David Arthur and Sergei Vassilvitskii (2007), Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, pp. 1027-1035, and (2) "The Effectiveness of Lloyd-Type Methods for the k-Means Problem" by Rafail Ostrovsky, Yuval Rabani, Leonard J. Schulman and Chaitanya Swamy <doi:10.1145/2395116.2395117>. Software Depends: R (>= 4.0.0) Imports: cli (>= 3.0.0), doFuture, dplyr (>= 0.5.0), future, magrittr, Matrix, methods, parallel (>= 3.3.2), purrr (>= 0.2.0), Rcpp (>= 0.12.11), RcppParallel, tgstat (>= 1.0.0), tibble (>= 3.1.2) LinkingTo: Rcpp, RcppParallel Suggests: covr, ggplot2 (>= 2.2.0), knitr, rlang, rmarkdown, testthat, withr Aviezer Lifshitz <aviezer.lifshitz@weizmann.ac.il> Comprehensive R Archive Network (CRAN) Aviezer Lifshitz [aut, cre], Amos Tanay [aut], Weizmann Institute of Science [cph] MIT + file LICENSE (https://CRAN.R-project.org/package=tglkmeans/LICENSE) 2026-03-04 application/tgz https://CRAN.R-project.org/package=tglkmeans doi:10.32614/CRAN.package.tglkmeans