plot.featImpCluster

an object returned from FeatureImpCluster

same data as used for the computation of the feature importance (only relevant for colored plots)

If set to "type", the plot will show different variable types with a different color.

color

showPoints

arguments to be passed to base plot method

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>.

plot.featImpCluster: Feature importance box plot

Description

Usage

Arguments

Value