Random Forest (RF) and Regularized Random Forest can be used for feature selection. Moreover, by Guided Regularized Random Forest, statistical-based weights are used to guide the regularization of random forest and further used for feature selection. This package can integrate prior information from multiple domains (statistical based and knowledge domain) to guide the regularization of random forest and feature selection. For more details, see reference: Guan X., Liu L. (2018) <doi:10.1007/978-3-319-78759-6_1>.
| Version: | 1.0 |
| Imports: | randomForest, RRF, PRROC, MASS |
| Published: | 2019-03-06 |
| Author: | Original code developed by Xin Guan, modified and added functions developed by Li Liu |
| Maintainer: | Xin Guan <xinguan at asu.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | KnowGRRF results |
| Reference manual: | KnowGRRF.pdf |
| Package source: | KnowGRRF_1.0.tar.gz |
| Windows binaries: | r-devel: KnowGRRF_1.0.zip, r-release: KnowGRRF_1.0.zip, r-oldrel: KnowGRRF_1.0.zip |
| macOS binaries: | r-release: KnowGRRF_1.0.tgz, r-oldrel: KnowGRRF_1.0.tgz |
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