vimpclust (version 0.1.0)
Variable Importance in Clustering
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).