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>.
Version: 0.5.5 Depends: R (≥ 4.0.0) Imports: cli, doFuture, doRNG, dplyr (≥ 0.5.0), future, ggplot2 (≥ 2.2.0), magrittr, Matrix, methods, parallel (≥ 3.3.2), plyr (≥ 1.8.4), purrr (≥ 0.2.0), Rcpp (≥ 0.12.11), RcppParallel, tgstat (≥ 1.0.0), tibble (≥ 3.1.2) LinkingTo: Rcpp, RcppParallel Suggests: covr, knitr, rlang, rmarkdown, testthat, withr OS_type: unix Published: 2024-05-15 DOI: 10.32614/CRAN.package.tglkmeans Author: Aviezer Lifshitz [aut, cre], Amos Tanay [aut], Weizmann Institute of Science [cph] Maintainer: Aviezer Lifshitz <aviezer.lifshitz at weizmann.ac.il> BugReports: https://github.com/tanaylab/tglkmeans/issues License: MIT + file LICENSE URL: https://tanaylab.github.io/tglkmeans/, https://github.com/tanaylab/tglkmeans NeedsCompilation: yes SystemRequirements: GNU make Materials: README NEWS CRAN checks: tglkmeans results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=tglkmeans to link to this page.
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