DESCRIPTION

Type: Package
Package: diceR
Title: Diverse Cluster Ensemble in R
Version: 2.2.0
Authors@R: c(
    person("Derek", "Chiu", , "dchiu@bccrc.ca", role = c("aut", "cre")),
    person("Aline", "Talhouk", , "a.talhouk@ubc.ca", role = "aut"),
    person("Johnson", "Liu", , "gliu@bccrc.ca", role = c("ctb", "com"))
  )
Description: 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.
License: MIT + file LICENSE
URL: https://github.com/AlineTalhouk/diceR/,
    https://alinetalhouk.github.io/diceR/
BugReports: https://github.com/AlineTalhouk/diceR/issues
Depends: 
    R (>= 3.5)
Imports: 
    abind,
    assertthat,
    class,
    clue,
    clusterSim,
    clv,
    clValid,
    dplyr (>= 0.7.5),
    ggplot2,
    infotheo,
    klaR,
    magrittr,
    mclust,
    methods,
    NMF,
    purrr (>= 0.2.3),
    RankAggreg,
    Rcpp,
    stringr,
    tidyr,
    yardstick
Suggests: 
    apcluster,
    blockcluster,
    cluster,
    covr,
    dbscan,
    e1071,
    kernlab,
    knitr,
    kohonen,
    pander,
    poLCA,
    progress,
    RColorBrewer,
    rlang,
    rmarkdown,
    Rtsne,
    sigclust,
    testthat
LinkingTo: 
    Rcpp
VignetteBuilder: 
    knitr
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.0