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.

Documentation

Manual: ClusterR.pdf
Vignette: Functionality of the ClusterR package

Maintainer: Lampros Mouselimis <mouselimislampros at gmail.com>

Author(s): Lampros Mouselimis <mouselimislampros at gmail.com>

Install package and any missing dependencies by running this line in your R console:

install.packages("ClusterR")

Depends R(>= 3.2.3), gtools
Imports Rcpp(>=0.12.5), OpenImageR, graphics, grDevices, utils, gmp, FD, stats, ggplot2
Suggests testthat, covr, knitr, rmarkdown
Enhances
Linking to Rcpp, RcppArmadillo(>=0.7.2)
Reverse
depends
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imports
CensMixReg
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suggests
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enhances
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linking to

Package ClusterR
Materials
URL https://github.com/mlampros/ClusterR
Task Views
Version 1.0.7
Published 2017-10-13
License MIT + file LICENSE
BugReports https://github.com/mlampros/ClusterR/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks ClusterR check results
Package source ClusterR_1.0.7.tar.gz