Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans and
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.
Imports: Rcpp (>= 0.12.5), OpenImageR, graphics, grDevices, utils, gmp,
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.2)
Suggests: testthat, covr, knitr, rmarkdown

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>.

Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids
Authors@R: c( person("Lampros", "Mouselimis", email = "mouselimislampros@gmail.com", role = c("aut", "cre")), person("Conrad", "Sanderson", role = "cph", comment = "Author of the C++ Armadillo library"), person("Ryan", "Curtin", role = "cph", comment = "Author of the C++ Armadillo library"), person("Siddharth", "Agrawal", role = "cph", comment = "Author of the C code of the Mini-Batch-Kmeans algorithm (https://github.com/siddharth-agrawal/Mini-Batch-K-Means)"), person("Brendan", "Frey", email = "frey@psi.toronto.edu", role = "cph", comment = "Author of the matlab code of the Affinity propagation algorithm (for commercial use please contact the author)"), person("Delbert", "Dueck", role = "cph", comment = "Author of the matlab code of the Affinity propagation algorithm") )
Description: Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation 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>; (iv) "Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, <doi:10.1126/science.1136800>.
LinkingTo: Rcpp, RcppArmadillo (>= 0.9.1)
Conrad Sanderson [cph] (Author of the C++ Armadillo library),
Ryan Curtin [cph] (Author of the C++ Armadillo library),
Siddharth Agrawal [cph] (Author of the C code of the Mini-Batch-Kmeans
Brendan Frey [cph] (Author of the matlab code of the Affinity
propagation algorithm (for commercial use please contact the
Delbert Dueck [cph] (Author of the matlab code of the Affinity