RRF: Regularized Random Forest

Feature Selection with Regularized Random Forest. This package is based on the 'randomForest' package by Andy Liaw. The key difference is the RRF() function that builds a regularized random forest. Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener, Regularized random forest for classification by Houtao Deng, Regularized random forest for regression by Xin Guan. Reference: Houtao Deng (2013) <arXiv:1306.0237>.

Version: 1.9.3
Depends: R (≥ 2.5.0), stats
Suggests: RColorBrewer, MASS
Published: 2022-02-24
Author: Houtao Deng [aut, cre], Xin Guan [aut], Andy Liaw [aut], Leo Breiman [aut], Adele Cutler [aut]
Maintainer: Houtao Deng <softwaredeng at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://sites.google.com/site/houtaodeng/rrf
NeedsCompilation: yes
Citation: RRF citation info
Materials: NEWS
CRAN checks: RRF results

Documentation:

Reference manual: RRF.pdf

Downloads:

Package source: RRF_1.9.3.tar.gz
Windows binaries: r-devel: RRF_1.9.3.zip, r-release: RRF_1.9.3.zip, r-oldrel: RRF_1.9.3.zip
macOS binaries: r-release (arm64): RRF_1.9.3.tgz, r-oldrel (arm64): RRF_1.9.3.tgz, r-release (x86_64): RRF_1.9.3.tgz, r-oldrel (x86_64): RRF_1.9.3.tgz
Old sources: RRF archive

Reverse dependencies:

Reverse imports: riAFTBART
Reverse suggests: fscaret, mlr

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RRF to link to this page.