NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:4403
Title:A Debiased MDI Feature Importance Measure for Random Forests


		
The paper studies theoretically the bias of the popular MDI importance measures in the presence of noisy features and proposes a very simple practical solution to reduce it. Two reviewers are very enthusiastic about the paper, even more so after reading the authors' response. One reviewer has several valid concerns about missing links between theory and practice but still recommends acceptance. I therefore recommend accepting the paper. The author are asked to take into account the reviewers comments when preparing the final version of their paper and, in particular, to address the specific request of reviewer 2 (to clarify how MDI-oob is computed).