Package: vimpclust
Type: Package
Title: Variable Importance in Clustering
Version: 0.1.0
Authors@R: c(person(given = "Alex",
           family = "Mourer",
           role = "aut",
           email = "mourer.alex@gmail.com"),
    person(given = "Marie",
           family = "Chavent",
           role = c("aut", "ths"),
           email = "marie.chavent@u-bordeaux.fr"),
    person(given = "Madalina",
           family = "Olteanu",
           role = c("aut", "ths", "cre"),
           email = "madalina.olteanu@dauphine.psl.eu"))
Description: An implementation of methods related to sparse clustering and variable importance 
    in clustering. The package currently allows to perform sparse k-means clustering with a group 
    penalty, so that it automatically selects groups of numerical features. It also allows to 
    perform sparse clustering and variable selection on mixed data (categorical and numerical 
    features), by preprocessing each categorical feature as a group of numerical features.
    Several methods for visualizing and exploring the results are also provided. 
    M. Chavent, J. Lacaille, A. Mourer and M. Olteanu (2020)<https://www.esann.org/sites/default/files/proceedings/2020/ES2020-103.pdf>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: PCAmixdata, ggplot2, Polychrome, mclust, rlang
Suggests: knitr, rmarkdown
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-12-18 13:36:56 UTC; administrateur
Author: Alex Mourer [aut],
  Marie Chavent [aut, ths],
  Madalina Olteanu [aut, ths, cre]
Maintainer: Madalina Olteanu <madalina.olteanu@dauphine.psl.eu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-01-08 09:30:03 UTC
Built: R 4.4.3; ; 2026-02-13 04:23:47 UTC; windows
