holdoutRF: Hold-out random forests

In ranger: A Fast Implementation of Random Forests

Hold-out random forests

Description

Grow two random forests on two cross-validation folds. Instead of out-of-bag data, the other fold is used to compute permutation importance. Related to the novel permutation variable importance by Janitza et al. (2015).

Usage

holdoutRF(...)

Arguments

...	All arguments are passed to ranger() (except importance, case.weights, replace and holdout.).

Value

Hold-out random forests with variable importance.

Author(s)

Marvin N. Wright

References

Janitza, S., Celik, E. & Boulesteix, A.-L., (2015). A computationally fast variable importance test for random forests for high-dimensional data. Adv Data Anal Classif \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s11634-016-0276-4")}.

See Also

ranger

ranger documentation built on Nov. 13, 2023, 1:09 a.m.