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Logic Forest is an ensemble machine learning method that identifies important and interpretable combinations of binary predictors using logic regression trees to model complex relationships with an outcome. Wolf, B.J., Slate, E.H., Hill, E.G. (2010) <doi:10.1093/bioinformatics/btq354>.
| Version: | 2.1.2 |
| Depends: | R (≥ 2.10) |
| Imports: | LogicReg, methods, survival |
| Suggests: | data.table |
| Published: | 2025-07-14 |
| DOI: | 10.32614/CRAN.package.LogicForest |
| Author: | Bethany Wolf [aut], Melica Nikahd [ctb, cre], Andrew Gothard [ctb], Madison Hyer [ctb] |
| Maintainer: | Melica Nikahd <melica.nikahd at osumc.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | LogicForest results |
| Reference manual: | LogicForest.pdf |
| Package source: | LogicForest_2.1.2.tar.gz |
| Windows binaries: | r-devel: LogicForest_2.1.2.zip, r-release: LogicForest_2.1.2.zip, r-oldrel: LogicForest_2.1.2.zip |
| macOS binaries: | r-release (arm64): LogicForest_2.1.2.tgz, r-oldrel (arm64): LogicForest_2.1.2.tgz, r-release (x86_64): LogicForest_2.1.2.tgz, r-oldrel (x86_64): LogicForest_2.1.2.tgz |
| Old sources: | LogicForest archive |
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