ClusterR (1.1.4)

Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans and K-Medoids Clustering.

Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, ; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, ; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, .

Maintainer: Lampros Mouselimis
Author(s): Lampros Mouselimis <>

License: MIT + file LICENSE

Uses: FD, ggplot2, gmp, gtools, OpenImageR, Rcpp, testthat, knitr, rmarkdown, covr
Reverse suggests: nonet

Released 6 months ago.