Package: ClusterR
Type: Package
Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans and
        K-Medoids Clustering
Version: 1.1.2
Date: 2018-05-03
Author: Lampros Mouselimis <mouselimislampros@gmail.com>
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>
BugReports: https://github.com/mlampros/ClusterR/issues
URL: https://github.com/mlampros/ClusterR
Description: 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>.
License: MIT + file LICENSE
LazyData: TRUE
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
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-05-03 16:53:18 UTC; lampros
Repository: CRAN
Date/Publication: 2018-05-03 22:41:37 UTC
