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: 3.1.0 Depends: R (≥ 4.1) Imports: abind, assertthat, class, clue, clusterCrit, clValid, dplyr (≥ 0.7.5), ggplot2, grDevices, infotheo, klaR, magrittr, mclust, methods, pheatmap, purrr (≥ 0.2.3), RankAggreg, Rcpp, stringr, tidyr, yardstick LinkingTo: Rcpp Suggests: apcluster, blockcluster, cluster, covr, dbscan, e1071, kernlab, knitr, kohonen, NMF, pander, poLCA, progress, RColorBrewer, rlang, rmarkdown, Rtsne, sigclust, testthat (≥ 3.0.0) Published: 2025-06-19 DOI: 10.32614/CRAN.package.diceR 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 Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=diceR to link to this page.
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