ClusterR: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering

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>.

Version:	1.3.3
Depends:	R (≥ 3.2)
Imports:	Rcpp (≥ 0.12.5), graphics, grDevices, utils, stats, gmp, ggplot2, lifecycle
LinkingTo:	Rcpp, RcppArmadillo (≥ 0.9.1)
Suggests:	OpenImageR, FD, testthat, covr, knitr, rmarkdown
Published:	2024-06-18
DOI:	10.32614/CRAN.package.ClusterR
Author:	Lampros Mouselimis [aut, cre], 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 algorithm (https://github.com/siddharth-agrawal/Mini-Batch-K-Means)), Brendan Frey [cph] (Author of the matlab code of the Affinity propagation algorithm (for commercial use please contact the author of the matlab code)), Delbert Dueck [cph] (Author of the matlab code of the Affinity propagation algorithm), Vitalie Spinu [ctb] (Github Contributor)
Maintainer:	Lampros Mouselimis <mouselimislampros at gmail.com>
BugReports:	https://github.com/mlampros/ClusterR/issues
License:	GPL-3
URL:	https://github.com/mlampros/ClusterR
NeedsCompilation:	yes
SystemRequirements:	libarmadillo: apt-get install -y libarmadillo-dev (deb), libblas: apt-get install -y libblas-dev (deb), liblapack: apt-get install -y liblapack-dev (deb), libarpack++2: apt-get install -y libarpack++2-dev (deb), gfortran: apt-get install -y gfortran (deb), libgmp3: apt-get install -y libgmp3-dev (deb), libfftw3: apt-get install -y libfftw3-dev (deb), libtiff5: apt-get install -y libtiff5-dev (deb)
Citation:	ClusterR citation info
Materials:	README NEWS
In views:	Cluster
CRAN checks:	ClusterR results

Documentation:

Reference manual:	ClusterR.pdf
Vignettes:	Functionality of the ClusterR package

Downloads:

Package source:	ClusterR_1.3.3.tar.gz
Windows binaries:	r-devel: ClusterR_1.3.3.zip, r-release: ClusterR_1.3.3.zip, r-oldrel: ClusterR_1.3.3.zip
macOS binaries:	r-release (arm64): ClusterR_1.3.3.tgz, r-oldrel (arm64): ClusterR_1.3.3.tgz, r-release (x86_64): ClusterR_1.3.3.tgz, r-oldrel (x86_64): ClusterR_1.3.3.tgz
Old sources:	ClusterR archive

Reverse dependencies:

Reverse imports:	bssn, Clustering, clusterMI, ClustImpute, ctpm, demu, DepecheR, jackstraw, mbkmeans, mlmts, moanin, opGMMassessment, patternize, PUGMM, Spectrum, text2map, tidybins
Reverse linking to:	mbkmeans, SuperpixelImageSegmentation
Reverse suggests:	butcher, FCPS, mlr, mlr3cluster, nonet, ScatterDensity, superml, tidyclust

Linking:

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