Classical ML
Permutation Importance
The drop in a held-out metric when a feature's values are randomly shuffled.
Why interviewers ask about it
The honest alternative to impurity importance, which is biased toward high-cardinality features and computed on training data. Breaks down with correlated features - use grouped permutation.
Related terms
This term is part of the free AI/ML Engineer interview preparation module - browse the full glossary for every definition.