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>).

Version: 0.9
Depends: R (≥ 3.0)
Imports: data.table (≥ 1.10.4), dplyr (≥ 0.7.1), dtplyr (≥ 0.0.2), DT (≥ 0.2), GGally (≥ 1.3.0), ggplot2 (≥ 2.2.1), ggrepel (≥ 0.6.5), MASS (≥ 7.3.47), randomForest (≥ 4.6.12), reshape2 (≥ 1.4.2), rmarkdown (≥ 1.5)
Suggests: knitr
Published: 2017-07-15
Author: Aleksandra Paluszynska [aut, cre], Przemyslaw Biecek [aut, ths]
Maintainer: Aleksandra Paluszynska <ola.paluszynska at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/MI2DataLab/randomForestExplainer
NeedsCompilation: no
Materials: README
CRAN checks: randomForestExplainer results

Downloads:

Reference manual: randomForestExplainer.pdf
Vignettes: Understanding random forests with randomForestExplainer
Package source: randomForestExplainer_0.9.tar.gz
Windows binaries: r-devel: randomForestExplainer_0.9.zip, r-release: randomForestExplainer_0.9.zip, r-oldrel: randomForestExplainer_0.9.zip
OS X El Capitan binaries: r-release: not available
OS X Mavericks binaries: r-oldrel: randomForestExplainer_0.9.tgz

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