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.

Version:	1.9.1
Depends:	R (≥ 2.5.0), stats
Suggests:	RColorBrewer, MASS
Published:	2019-07-02
Author:	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.
Maintainer:	ORPHANED
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_1.9.1.tar.gz
Windows binaries:	r-devel: RRF_1.9.1.zip, r-devel-UCRT: RRF_1.9.1.zip, r-release: RRF_1.9.1.zip, r-oldrel: RRF_1.9.1.zip
macOS binaries:	r-release (arm64): RRF_1.9.1.tgz, r-release (x86_64): RRF_1.9.1.tgz, r-oldrel: RRF_1.9.1.tgz
Old sources:	RRF archive

Reverse dependencies:

Reverse imports:	inTrees, KnowGRRF
Reverse suggests:	fscaret, mlr

Linking:

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