This is an R implementation of the method proposed in "Scalable and Efficient Hypothesis Tests for Random Forests". Intended to function like an F-test for ensemble learners, that is both computationally efficient and provably valid in the sense of Type I error control. See also http://arxiv.org/abs/1904.07830.
The DESCRIPTION file:
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Most of the functionality comes in the MSE_Test
file, which will conduct an F-test for a certain subset of variables. To run marginal F-tests for each variable, f_holdoutRF
(efficient) or permtestImp
(brute force) should be used.
Tim Coleman
Maintainer: Tim Coleman <tsc35@pitt.edu>
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