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. (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

Downloads:

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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