Package: rfVarImpOOB 1.0.3

rfVarImpOOB: Unbiased Variable Importance for Random Forests

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.

Authors:Markus Loecher <[email protected]>

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rfVarImpOOB.pdf |rfVarImpOOB.html
rfVarImpOOB/json (API)

# Install 'rfVarImpOOB' in R:
install.packages('rfVarImpOOB', repos = c('https://markusloecher.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 5 scripts 187 downloads 13 exports 74 dependencies

Last updated 3 years agofrom:60b5b1366b. Checks:1 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 21 2025
R-4.5-winNOTEFeb 21 2025
R-4.5-macNOTEFeb 21 2025
R-4.5-linuxNOTEFeb 21 2025
R-4.4-winNOTEFeb 21 2025
R-4.4-macNOTEFeb 21 2025
R-4.3-winNOTEFeb 21 2025
R-4.3-macNOTEFeb 21 2025

Exports:Accuracygini_indexgini_processGiniImportanceForestGiniImportanceTreeInOutBagslpnormmloglossModeplotVIplotVI2preorder2rfTitanic

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6randomForestrangerrbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselecttitanicutf8vctrsviridisLitewithr

Variable Importance based on reduction of Gini on OOB

Rendered fromrfVarImpOOB-vignette.Rmdusingknitr::rmarkdownon Feb 21 2025.

Last update: 2020-10-18
Started: 2019-04-05