doi:10.1198/jasa.2009.tm08622>, Leo Breiman (2001) <doi:10.1023/A:1010933404324>).">

randomForestExplainer: Explaining and Visualizing Random Forests in Terms of Variable Importance (original) (raw)

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>).

Version: 0.10.1
Depends: R (≥ 3.0)
Imports: data.table (≥ 1.10.4), dplyr (≥ 0.7.1), DT (≥ 0.2), GGally (≥ 1.3.0), ggplot2 (≥ 2.2.1), ggrepel (≥ 0.6.5), randomForest (≥ 4.6.12), ranger (≥ 0.9.0), reshape2 (≥ 1.4.2), rmarkdown (≥ 1.5)
Suggests: knitr, MASS (≥ 7.3.47), testthat
Published: 2020-07-11
DOI: 10.32614/CRAN.package.randomForestExplainer
Author: Aleksandra Paluszynska [aut], Przemyslaw Biecek [aut, ths], Yue Jiang ORCID iD [aut, cre]
Maintainer: Yue Jiang
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/ModelOriented/randomForestExplainer
NeedsCompilation: no
Materials: README NEWS
CRAN checks: randomForestExplainer results

Documentation:

Downloads:

Reverse dependencies:

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=randomForestExplainerto link to this page.