A regression and classification algorithm based on random forests, which takes the form of a short list of rules. SIRUS combines the simplicity of decision trees with a predictivity close to random forests. The core aggregation principle of random forests is kept, but instead of aggregating predictions, SIRUS aggregates the forest structure: the most frequent nodes of the forest are selected to form a stable rule ensemble model. The algorithm is fully described in the following articles: Benard C., Biau G., da Veiga S., Scornet E. (2021), Electron. J. Statist., 15:427-505 <doi:10.1214/20-EJS1792> for classification, and Benard C., Biau G., da Veiga S., Scornet E. (2020) <arXiv:2004.14841> for regression. This R package is a fork from the project ranger (<https://github.com/imbs-hl/ranger>).
| Version: | 0.3.2 |
| Depends: | R (≥ 3.1) |
| Imports: | Rcpp (≥ 0.11.2), Matrix, ROCR, ggplot2, glmnet |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | survival, testthat |
| Published: | 2021-02-22 |
| Author: | Clement Benard [aut, cre], Marvin N. Wright [ctb, cph] |
| Maintainer: | Clement Benard <clement.benard5 at gmail.com> |
| BugReports: | https://gitlab.com/drti/sirus/-/issues |
| License: | GPL-3 |
| URL: | https://gitlab.com/drti/sirus |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | sirus results |
| Reference manual: | sirus.pdf |
| Package source: | sirus_0.3.2.tar.gz |
| Windows binaries: | r-devel: sirus_0.3.2.zip, r-devel-UCRT: sirus_0.3.2.zip, r-release: sirus_0.3.2.zip, r-oldrel: sirus_0.3.2.zip |
| macOS binaries: | r-release (arm64): sirus_0.3.2.tgz, r-release (x86_64): sirus_0.3.2.tgz, r-oldrel: sirus_0.3.2.tgz |
| Old sources: | sirus archive |
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