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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
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

Documentation:

Reference manual: sirus.pdf

Downloads:

Package source: sirus_0.3.3.tar.gz
Windows binaries: r-devel: sirus_0.3.3.zip, r-release: sirus_0.3.3.zip, r-oldrel: sirus_0.3.3.zip
macOS binaries: r-release (arm64): sirus_0.3.3.tgz, r-oldrel (arm64): sirus_0.3.3.tgz, r-release (x86_64): sirus_0.3.3.tgz, r-oldrel (x86_64): sirus_0.3.3.tgz
Old sources: sirus archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=sirus to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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