CRAN/E | vimpclust

vimpclust

Variable Importance in Clustering

Installation

About

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).

Key Metrics

Version 0.1.0
R ≥ 3.5.0
Published 2021-01-08 1207 days ago
Needs compilation? no
License GPL-3
CRAN checks vimpclust results

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Maintainer

Maintainer

Madalina Olteanu

madalina.olteanu@dauphine.psl.eu

Authors

Alex Mourer

aut

Marie Chavent

aut / ths

Madalina Olteanu

aut / ths / cre

Material

Reference manual
Package source

Vignettes

Group-sparse weighted k-means for numerical data
Sparse weighted k-means for mixed data

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.5.0

Imports

PCAmixdata
ggplot2
Polychrome
mclust
rlang

Suggests

knitr
rmarkdown