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.

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Description file content

Type
Package
Package
diceR
Title
Diverse Cluster Ensemble in R
Version
0.5.1
Date
2018-06-10
Description
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.
License
MIT + file LICENSE
URL
BugReports
https://github.com/AlineTalhouk/diceR/issues
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, magrittr, mclust, methods, NMF, progress, purrr (>= 0.2.3), quantable, RankAggreg, RColorBrewer, Rcpp, Rtsne, sigclust, stringr, tibble, tidyr
Suggests
covr, knitr, pander, rmarkdown, testthat
LinkingTo
Rcpp
VignetteBuilder
knitr
Encoding
UTF-8
LazyData
true
RoxygenNote
6.0.1
NeedsCompilation
yes
Packaged
2018-06-11 05:21:30 UTC; Derek
Author
Derek Chiu [aut, cre], Aline Talhouk [aut], Johnson Liu [ctb, com]
Maintainer
Derek Chiu
Repository
CRAN
Date/Publication
2018-06-11 09:29:37 UTC

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