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tglkmeans  

Efficient Implementation of K-Means++ Algorithm
View on CRAN: Click here


Download and install tglkmeans package within the R console
Install from CRAN:
install.packages("tglkmeans")

Install from Github:
library("remotes")
install_github("cran/tglkmeans")

Install by package version:
library("remotes")
install_version("tglkmeans", "0.5.8")



Attach the package and use:
library("tglkmeans")
Maintained by
Aviezer Lifshitz
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-04-20
Latest Update: 2024-05-15
Description:
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>.
How to cite:
Aviezer Lifshitz (2022). tglkmeans: Efficient Implementation of K-Means++ Algorithm. R package version 0.5.8, https://cran.r-project.org/web/packages/tglkmeans. Accessed 08 Jun. 2026.
Previous versions and publish date:
0.3.4 (2022-04-20 10:40), 0.3.5 (2022-08-28 20:20), 0.3.8 (2023-03-21 11:30), 0.3.10 (2023-06-26 10:30), 0.3.11 (2023-08-21 11:00), 0.5.4 (2024-01-09 15:10), 0.5.5 (2024-05-15 10:40), 0.5.8 (2026-01-14 09:10)
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Other R packages that tglkmeans depends, imports, suggests or enhances
Complete documentation for tglkmeans
Functions, R codes and Examples using the tglkmeans R package
Some associated functions: TGL_kmeans . TGL_kmeans_tidy . downsample_matrix . pipe . simulate_data . tglkmeans-package . tglkmeans.set_parallel . 
Some associated R codes: RcppExports.R . TGL_kmeans.R . downsample.R . intra_clustering.R . misc.R . tests.R . tglkmeans-package.R . utils-pipe.R . zzz.R .  Full tglkmeans package functions and examples
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