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>.
| Version: | 0.1.5 |
| Depends: | data.table |
| Imports: | ggplot2 |
| Suggests: | flexclust, clustMixType, knitr, rmarkdown, testthat, attempt, ClustImpute, covr |
| Published: | 2021-10-20 |
| Author: | Oliver Pfaffel [aut, cre] |
| Maintainer: | Oliver Pfaffel <opfaffel at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | FeatureImpCluster results |
| Reference manual: | FeatureImpCluster.pdf |
| Package source: | FeatureImpCluster_0.1.5.tar.gz |
| Windows binaries: | r-devel: FeatureImpCluster_0.1.5.zip, r-release: FeatureImpCluster_0.1.5.zip, r-oldrel: FeatureImpCluster_0.1.5.zip |
| macOS binaries: | r-release (arm64): FeatureImpCluster_0.1.5.tgz, r-oldrel (arm64): FeatureImpCluster_0.1.5.tgz, r-release (x86_64): FeatureImpCluster_0.1.5.tgz, r-oldrel (x86_64): FeatureImpCluster_0.1.5.tgz |
| Old sources: | FeatureImpCluster archive |
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