Diverse Cluster Ensemble in R

Performs cluster analysis using an ensemble clustering framework. Results from a diverse set of algorithms are pooled together using methods such as majority voting, K-Modes, LinkCluE, and CSPA. There are options to compare cluster assignments across algorithms using internal and external indices, visualizations such as heatmaps, and significance testing for the existence of clusters.


Reference manual

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0.1.0 by Derek Chiu, 3 months ago


Report a bug at https://github.com/AlineTalhouk/diceR/issues

Browse source code at https://github.com/cran/diceR

Authors: Derek Chiu [aut, cre], Aline Talhouk [aut], Johnson Liu [ctb, com]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports abind, assertthat, dplyr, magrittr, tidyr, purrr, ggplot2, gplots, grDevices, Hmisc, flux, NMF, apcluster, kernlab, mclust, infotheo, blockcluster, caret, class, clue, cluster, clusterCrit, clValid, klaR, RColorBrewer, quantable, RankAggreg, sigclust, methods, Rcpp

Suggests testthat, knitr, rmarkdown, covr

Linking to Rcpp

See at CRAN