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: |
1.2.0 |
| 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, tidyr, yardstick |
| LinkingTo: |
Rcpp |
| Suggests: |
apcluster, blockcluster, cluster, covr, dbscan, e1071, kernlab, knitr, kohonen, pander, poLCA, progress, RColorBrewer, rlang, rmarkdown, Rtsne, sigclust, testthat |
| Published: |
2022-05-13 |
| 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 |