diceR: 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.

Version: 0.4.0
Depends: R (≥ 3.1)
Imports: abind, apcluster, assertthat, blockcluster, caret, class, cli, clue, cluster, clusterCrit, clValid, dbscan, dplyr, e1071, flux, ggplot2, gplots, grDevices, Hmisc, infotheo, kernlab, klaR, kohonen, largeVis, magrittr, mclust, methods, NNLM, pheatmap, progress, purrr (≥ 0.2.3), quantable, RankAggreg, RColorBrewer, Rcpp, Rtsne, sigclust, stringr, tibble, tidyr
LinkingTo: Rcpp
Suggests: covr, knitr, pander, rmarkdown, testthat
Published: 2018-02-22
Author: Derek Chiu [aut, cre], Aline Talhouk [aut], Johnson Liu [ctb, com]
Maintainer: Derek Chiu <dchiu at bccrc.ca>
BugReports: https://github.com/AlineTalhouk/diceR/issues
License: MIT + file LICENSE
URL: https://github.com/AlineTalhouk/diceR, https://alinetalhouk.github.io/diceR
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: diceR results


Reference manual: diceR.pdf
Vignettes: Cluster Analysis using 'diceR'
Package source: diceR_0.4.0.tar.gz
Windows binaries: r-devel: diceR_0.4.0.zip, r-release: diceR_0.3.2.zip, r-oldrel: diceR_0.3.2.zip
OS X El Capitan binaries: r-release: diceR_0.4.0.tgz
OS X Mavericks binaries: r-oldrel: diceR_0.3.1.tgz
Old sources: diceR archive


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