Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable Importance

7 March 2020

Papers citing "Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable Importance"

5 / 5 papers shown

Title
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests Brian Liu Rahul Mazumder 23 1 0 20 Feb 2024
Sequential Permutation Testing of Random Forest Variable Importance Measures Alexander Hapfelmeier R. Hornung Bernhard Haller 20 15 0 02 Jun 2022
MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA Clément Bénard Sébastien Da Veiga Erwan Scornet 42 49 0 26 Feb 2021
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 90 152 0 02 Mar 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 35 153 0 01 May 2019