sirus: Stable and Interpretable RUle Set
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. (2021), AISTATS, PMLR 130:937-945 <http://proceedings.mlr.press/v130/benard21a>, for regression. This R package is a fork from the project ranger (<https://github.com/imbs-hl/ranger>).
| Version: | 0.3.3 |
| Depends: | R (≥ 3.6) |
| Imports: | Rcpp (≥ 0.11.2),Matrix,ROCR,ggplot2,glmnet |
| LinkingTo: | Rcpp,RcppEigen |
| Suggests: | survival,testthat,ranger |
| Published: | 2022-06-13 |
| DOI: | 10.32614/CRAN.package.sirus |
| 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[issues need fixing before 2026-01-15] |
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