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: | 1.9.4 |
| Depends: | R (≥ 2.5.0), stats |
| Suggests: | RColorBrewer, MASS |
| Published: | 2022-05-30 |
| 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 |
| Reference manual: | RRF.pdf |
| Package source: | RRF_1.9.4.tar.gz |
| Windows binaries: | r-devel: RRF_1.9.4.zip, r-release: RRF_1.9.4.zip, r-oldrel: RRF_1.9.4.zip |
| macOS binaries: | r-release (arm64): RRF_1.9.4.tgz, r-oldrel (arm64): RRF_1.9.4.tgz, r-release (x86_64): RRF_1.9.4.tgz, r-oldrel (x86_64): RRF_1.9.4.tgz |
| Old sources: | RRF archive |
| Reverse imports: | inTrees, riAFTBART |
| Reverse suggests: | fscaret, mlr |
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