FeatureImpCluster: Feature Importance for Partitional Clustering
Oliver Pfaffel · 2020
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: .