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Scalable and Efficient Hypothesis Testing with Random Forests
16 April 2019
T. Coleman
Wei Peng
L. Mentch
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Papers citing
"Scalable and Efficient Hypothesis Testing with Random Forests"
6 / 6 papers shown
Title
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression
Ricardo Baptista
Eliza O'Reilly
Yangxinyu Xie
94
2
0
13 Jul 2024
Sequential Permutation Testing of Random Forest Variable Importance Measures
Alexander Hapfelmeier
R. Hornung
Bernhard Haller
59
15
0
02 Jun 2022
Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable Importance
L. Mentch
Siyu Zhou
102
14
0
07 Mar 2020
Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success
L. Mentch
Siyu Zhou
87
72
0
01 Nov 2019
Asymptotic Distributions and Rates of Convergence for Random Forests via Generalized U-statistics
Weiguang Peng
T. Coleman
L. Mentch
104
41
0
25 May 2019
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
93
159
0
01 May 2019
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