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.
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Oliver Pfaffel, a year ago
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Oliver Pfaffel [aut, cre]
Depends on data.table
Suggests flexclust, clustMixType, knitr, rmarkdown, testthat, attempt, ClustImpute, covr
See at CRAN