Francesco Cappelli

1paper

1 Paper

7.5MLApr 13
Trustworthy Feature Importance Avoids Unrestricted Permutations

Emanuele Borgonovo, Francesco Cappelli, Xuefei Lu et al.

Feature importance methods using unrestricted permutations are flawed due to extrapolation errors; such errors appear in all non-trivial variable importance approaches. We propose three new approaches: conditional model reliance and Knockoffs with Gaussian transformation, and restricted ALE plot designs. Theoretical and numerical results show our strategies reduce/eliminate extrapolation.