3 citations · 3 across the 4 of their papers we have counts for
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stat.ML2019
Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success
Lucas Mentch, Siyu Zhou
Random forests remain among the most popular off-the-shelf supervised machine learning tools with a well-established track record of predictive accuracy in both regression and clas…
stat.ME2019
Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance
Giles Hooker, Lucas Mentch, Siyu Zhou
This paper reviews and advocates against the use of permute-and-predict (PaP) methods for interpreting black box functions. Methods such as the variable importance measures propose…