diceR: Diverse Cluster Ensemble in R

Performs cluster analysis using an ensemble clustering framework, Chiu & Talhouk (2018) <doi:10.1186/s12859-017-1996-y>. 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: 1.0.1
Depends: R (≥ 3.5)
Imports: abind, assertthat, class, clue, clusterCrit, clValid, dplyr (≥ 0.7.5), ggplot2, infotheo, klaR, magrittr, mclust, methods, NMF, purrr (≥ 0.2.3), RankAggreg, Rcpp, stringr, tibble, tidyr, yardstick
LinkingTo: Rcpp
Suggests: apcluster, blockcluster, cluster, covr, dbscan, e1071, kernlab, knitr, kohonen, pander, poLCA, progress, rmarkdown, Rtsne, sigclust, testthat
Published: 2021-01-31
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

Downloads:

Reference manual: diceR.pdf
Vignettes: Cluster Analysis using 'diceR'
Package source: diceR_1.0.1.tar.gz
Windows binaries: r-devel: diceR_1.0.1.zip, r-release: diceR_1.0.1.zip, r-oldrel: diceR_1.0.1.zip
macOS binaries: r-release: diceR_1.0.1.tgz, r-oldrel: diceR_1.0.1.tgz
Old sources: diceR archive

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