Package: sirus
Type: Package
Title: Stable and Interpretable RUle Set
Version: 0.3.3
Date: 2022-06-10
Author: Clement Benard [aut, cre], Marvin N. Wright [ctb, cph]
Maintainer: Clement Benard <clement.benard5@gmail.com>
Description: 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>). 
License: GPL-3
Imports: Rcpp (>= 0.11.2), Matrix, ROCR, ggplot2, glmnet
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.6)
Suggests: survival, testthat, ranger
RoxygenNote: 7.2.0
URL: https://gitlab.com/drti/sirus
BugReports: https://gitlab.com/drti/sirus/-/issues
NeedsCompilation: yes
Packaged: 2022-06-11 18:30:14 UTC; d584316
Repository: CRAN
Date/Publication: 2022-06-13 09:20:02 UTC
Built: R 4.4.0; x86_64-apple-darwin20; 2024-06-01 09:11:18 UTC; unix
Archs: sirus.so.dSYM
