ClusterR: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans and K-Medoids Clustering
Version 1.1.2

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, .

Package details

AuthorLampros Mouselimis <[email protected]>
Date of publication2018-05-03 22:41:37 UTC
MaintainerLampros Mouselimis <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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ClusterR documentation built on May 4, 2018, 1:04 a.m.