Type: Package
Package: diceR
Title: Diverse Cluster Ensemble in R
Version: 2.0.0
Authors@R: 
    c(person(given = "Derek",
             family = "Chiu",
             role = c("aut", "cre"),
             email = "dchiu@bccrc.ca"),
      person(given = "Aline",
             family = "Talhouk",
             role = "aut",
             email = "a.talhouk@ubc.ca"),
      person(given = "Johnson",
             family = "Liu",
             role = c("ctb", "com"),
             email = "gliu@bccrc.ca"))
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,
    cluster,
    covr,
    dbscan,
    e1071,
    kernlab,
    knitr,
    kohonen,
    mixedClust,
    pander,
    poLCA,
    progress,
    RColorBrewer,
    rlang,
    rmarkdown,
    Rtsne,
    sigclust,
    testthat
LinkingTo: 
    Rcpp
VignetteBuilder: 
    knitr
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
