Package: ClusterR 1.3.6

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>.

Authors:Lampros Mouselimis [aut, cre], Conrad Sanderson [cph], Ryan Curtin [cph], Siddharth Agrawal [cph], Brendan Frey [cph], Delbert Dueck [cph], Vitalie Spinu [ctb], Frederiek - Maarten Kerckhof [ctb]

ClusterR_1.3.6.tar.gz
ClusterR_1.3.6.zip(r-4.7)ClusterR_1.3.6.zip(r-4.6)ClusterR_1.3.6.zip(r-4.5)
ClusterR_1.3.6.tgz(r-4.6-x86_64)ClusterR_1.3.6.tgz(r-4.6-arm64)ClusterR_1.3.6.tgz(r-4.5-x86_64)ClusterR_1.3.6.tgz(r-4.5-arm64)
ClusterR_1.3.6.tar.gz(r-4.7-arm64)ClusterR_1.3.6.tar.gz(r-4.7-x86_64)ClusterR_1.3.6.tar.gz(r-4.6-arm64)ClusterR_1.3.6.tar.gz(r-4.6-x86_64)
ClusterR_1.3.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ClusterR/json (API)
NEWS

# Install 'ClusterR' in R:
install.packages('ClusterR', repos = c('https://mlampros.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mlampros/clusterr/issues

Pkgdown/docs site:https://mlampros.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • dietary_survey_IBS - Synthetic data using a dietary survey of patients with irritable bowel syndrome
  • mushroom - The mushroom data
  • soybean - The soybean (large) data set from the UCI repository

On CRAN:

Conda:

affinity-propagationcpp11gmmkmeanskmedoids-clusteringmini-batch-kmeansrcpparmadilloopenblascppopenmp

11.76 score 85 stars 25 packages 732 scripts 8.2k downloads 2 mentions 22 exports 20 dependencies

Last updated from:02cef28814. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK175
linux-devel-x86_64OK208
source / vignettesOK292
linux-release-arm64OK193
linux-release-x86_64OK163
macos-release-arm64OK124
macos-release-x86_64OK346
macos-oldrel-arm64OK131
macos-oldrel-x86_64OK299
windows-develOK158
windows-releaseOK167
windows-oldrelOK161
wasm-releaseOK136

Exports:AP_affinity_propagationAP_preferenceRangecenter_scaleClara_MedoidsCluster_Medoidscost_clusters_from_dissim_medoidsdistance_matrixexternal_validationGMMKMeans_armaKMeans_rcppMiniBatchKmeansOptimal_Clusters_GMMOptimal_Clusters_KMeansOptimal_Clusters_Medoidsplot_2dpredict_GMMpredict_KMeanspredict_MBatchKMeanspredict_MedoidsSilhouette_Dissimilarity_Plotsilhouette_of_clusters

Dependencies:clicpp11farverggplot2gluegmpgtableisobandlabelinglifecycleR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr

Functionality of the ClusterR package

Lampros Mouselimis

Rendered fromthe_clusterR_package.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2023-12-05
Started: 2016-09-12

Readme and manuals

Help Manual

Help pageTopics
Affinity propagation clusteringAP_affinity_propagation
Affinity propagation preference rangeAP_preferenceRange
Function to scale and/or center the datacenter_scale
Clustering large applicationsClara_Medoids
Partitioning around medoidsCluster_Medoids
Compute the cost and clusters based on an input dissimilarity matrix and medoidscost_clusters_from_dissim_medoids
Synthetic data using a dietary survey of patients with irritable bowel syndrome (IBS)dietary_survey_IBS
Distance matrix calculationdistance_matrix
external clustering validationexternal_validation
Gaussian Mixture Model clusteringGMM
k-means using the Armadillo libraryKMeans_arma
k-means using RcppArmadilloKMeans_rcpp
Mini-batch-k-means using RcppArmadilloMiniBatchKmeans
The mushroom datamushroom
Optimal number of Clusters for the gaussian mixture modelsOptimal_Clusters_GMM
Optimal number of Clusters for Kmeans or Mini-Batch-KmeansOptimal_Clusters_KMeans
Optimal number of Clusters for the partitioning around Medoids functionsOptimal_Clusters_Medoids
2-dimensional plotsplot_2d
Prediction function for a Gaussian Mixture Model objectpredict.GMMCluster predict_GMM
Prediction function for the k-meanspredict.KMeansCluster predict_KMeans
Prediction function for Mini-Batch-k-meanspredict.MBatchKMeans predict_MBatchKMeans
Predictions for the Medoid functionspredict.MedoidsCluster predict_Medoids
Plot of silhouette widths or dissimilaritiesSilhouette_Dissimilarity_Plot
Silhouette width based on pre-computed clusterssilhouette_of_clusters
The soybean (large) data set from the UCI repositorysoybean