Package: rfVarImpOOB
Title: Unbiased Variable Importance for Random Forests
Version: 1.0.3
Date: 2022-06-30
Depends: R (>= 3.2.2), stats, randomForest
Imports: ggplot2, ggpubr, dplyr,titanic,magrittr,ranger
Suggests: knitr,rmarkdown
Author: Markus Loecher <Markus.Loecher@gmail.com>
Maintainer: Markus Loecher <Markus.Loecher@gmail.com>
Description: Computes a novel variable importance for random forests: Impurity reduction importance scores for out-of-bag (OOB) data complementing the existing inbag Gini importance, see also <doi: 10.1080/03610926.2020.1764042>. 
    The Gini impurities for inbag and OOB data are combined in three different ways, after which the information gain is computed at each split.
    This gain is aggregated for each split variable in a tree and averaged across trees.
License: GPL (>= 2)
Repository: CRAN
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-07-01 08:16:57 UTC; loecherm
Date/Publication: 2022-07-01 14:40:02 UTC
Built: R 4.6.0; ; 2026-05-01 05:01:00 UTC; unix
