Package: randomForestExplainer 0.11.0

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]

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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'))

Peer review:

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

On CRAN:

random-forest

10.03 score 230 stars 254 scripts 1.3k downloads 20 mentions 11 exports 79 dependencies

Last updated 8 months agofrom:c92335e726. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

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:base64encbslibcachemclicolorspacecpp11crayoncrosstalkdata.tabledigestdplyrDTevaluatefansifarverfastmapfontawesomeforcatsfsgenericsGGallyggplot2ggrepelggstatsgluegtablehighrhmshtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepatchworkpillarpkgconfigplyrprettyunitsprogresspromisespurrrR6randomForestrangerrappdirsRColorBrewerRcppRcppEigenrlangrmarkdownsassscalesstringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Understanding random forests with randomForestExplainer

Rendered fromrandomForestExplainer.Rmdusingknitr::rmarkdownon Nov 17 2024.

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