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)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-21 09:34:04 UTC; root
Config/pak/sysreqs: cmake make libicu-dev
Repository: https://markusloecher.r-universe.dev
Date/Publication: 2022-07-01 13:40:02 UTC
RemoteUrl: https://github.com/cran/rfVarImpOOB
RemoteRef: HEAD
RemoteSha: 60b5b1366bc22750cf609eb6c60f78ecb2b5172a