Feature Importance for Partitional Clustering R package FeatureImpCluster version 0.1.5 Implements a novel approach for measuring feature importance in k-means clustering. Importance of a feature is measured by the misclassification rate relative to the baseline cluster assignment due to a random permutation of feature values. An explanation of permutation feature importance in general can be found here: <https://christophm.github.io/interpretable-ml-book/feature-importance.html>. Software Depends: data.table Imports: ggplot2 Suggests: flexclust, clustMixType, knitr, rmarkdown, testthat, attempt, ClustImpute, covr Oliver Pfaffel <opfaffel@gmail.com> Comprehensive R Archive Network (CRAN) Oliver Pfaffel [aut, cre] GPL-3 2021-10-20 application/tgz https://CRAN.R-project.org/package=FeatureImpCluster doi:10.32614/CRAN.package.FeatureImpCluster