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>.
Package details |
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Maintainer | |
License | GPL-3 |
Version | 0.1.5 |
Package repository | View on GitHub |
Installation |
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