Statistically Valid Variable Importance Assessment through Conditional Permutations

14 September 2023

Papers citing "Statistically Valid Variable Importance Assessment through Conditional Permutations"

6 / 6 papers shown

Title
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 85 248 0 21 Nov 2020
A general framework for inference on algorithm-agnostic variable importance B. Williamson P. Gilbert N. Simon M. Carone FAtt CML 18 67 0 07 Apr 2020
Aggregation of Multiple Knockoffs Tuan-Binh Nguyen Jérôme-Alexis Chevalier Bertrand Thirion Sylvain Arlot 70 21 0 21 Feb 2020
Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance Giles Hooker L. Mentch Siyu Zhou 66 157 0 01 May 2019
Visualizing the Feature Importance for Black Box Models Giuseppe Casalicchio Christoph Molnar B. Bischl FAtt 38 183 0 18 Apr 2018
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.1K 16,931 0 16 Feb 2016