ClusterR: 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, <doi:10.18637/jss.v001.i04>; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, <doi:10.1145/1772690.1772862>; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, <doi:10.21105/joss.00026>.

Version: 1.1.3
Depends: R (≥ 3.2.3), gtools
Imports: Rcpp (≥ 0.12.5), OpenImageR, graphics, grDevices, utils, gmp, FD, stats, ggplot2
LinkingTo: Rcpp, RcppArmadillo (≥ 0.7.2)
Suggests: testthat, covr, knitr, rmarkdown
Published: 2018-07-21
Author: Lampros Mouselimis
Maintainer: Lampros Mouselimis <mouselimislampros at gmail.com>
BugReports: https://github.com/mlampros/ClusterR/issues
License: MIT + file LICENSE
URL: https://github.com/mlampros/ClusterR
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: ClusterR results

Downloads:

Reference manual: ClusterR.pdf
Vignettes: Functionality of the ClusterR package
Package source: ClusterR_1.1.3.tar.gz
Windows binaries: r-devel: ClusterR_1.1.3.zip, r-release: ClusterR_1.1.3.zip, r-oldrel: ClusterR_1.1.3.zip
OS X binaries: r-release: ClusterR_1.1.3.tgz, r-oldrel: ClusterR_1.1.3.tgz
Old sources: ClusterR archive

Reverse dependencies:

Reverse imports: CensMixReg, demu, jackstraw

Linking:

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