Package: randomForestExplainer 0.11.0

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Yue Jiang

randomForestExplainer: Explaining and Visualizing Random Forests in Terms of Variable Importance

A set of tools to help explain which variables are most important in a random forests. Various variable importance measures are calculated and visualized in different settings in order to get an idea on how their importance changes depending on our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran Z. Gorodeski and Andy J. Minn and Michael S. Lauer (2010) <doi:10.1198/jasa.2009.tm08622>, Leo Breiman (2001) <doi:10.1023/A:1010933404324>).

Authors:Aleksandra Paluszynska [aut], Przemyslaw Biecek [aut, ths], Michael Mayer [aut], Olivier Roy [aut], Yue Jiang [aut, cre]

randomForestExplainer_0.11.0.tar.gz
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randomForestExplainer.pdf |randomForestExplainer.html
randomForestExplainer/json (API)
NEWS

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

Bug tracker:https://github.com/modeloriented/randomforestexplainer/issues

Pkgdown/docs site:https://modeloriented.github.io

On CRAN:

Conda:

random-forest

9.38 score 239 stars 290 scripts 802 downloads 20 mentions 11 exports 73 dependencies

Last updated from:c92335e726. Checks:9 OK. Indexed: yes.

TargetResultTotal timeArtifact
linux-devel-x86_64OK212
source / vignettesOK205
linux-release-x86_64OK210
macos-devel-arm64OK174
macos-release-arm64OK154
windows-develOK151
windows-releaseOK152
windows-oldrelOK184
wasm-releaseOK124

Exports:explain_forestimportant_variablesmeasure_importancemin_depth_distributionmin_depth_interactionsplot_importance_ggpairsplot_importance_rankingsplot_min_depth_distributionplot_min_depth_interactionsplot_multi_way_importanceplot_predict_interaction

Dependencies:base64encbslibcachemclicpp11crayoncrosstalkdata.tabledigestdplyrDTevaluatefarverfastmapfontawesomeforcatsfsgenericsGGallyggplot2ggrepelggstatsgluegtablehighrhmshtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMatrixmemoisemimeotelpatchworkpillarpkgconfigprettyunitsprogresspromisespurrrR6randomForestrangerrappdirsRColorBrewerRcppRcppEigenrlangrmarkdownS7sassscalesstringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Understanding random forests with randomForestExplainer

Rendered fromrandomForestExplainer.Rmdusingknitr::rmarkdownon Jan 26 2026.

Last update: 2024-03-22
Started: 2017-07-12

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