Stable and Interpretable RUle Set

A classification algorithm based on random forests, which takes the form of a short list of rules. SIRUS combines the simplicity of decision trees with the predictivity of random forests for problems with low order interactions. The core aggregation principle of random forests is kept, but instead of aggregating predictions, SIRUS selects the most frequent nodes of the forest to form a stable rule ensemble model. The algorithm is fully described in the following article: Benard C., Biau G., da Veiga S., Scornet E. (2019) . This R package is a fork from the project ranger (< https://github.com/imbs-hl/ranger>).


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Reference manual

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install.packages("sirus")

0.1.2 by Clement Benard, 15 days ago


https://gitlab.com/safrandrti/sirus


Report a bug at https://gitlab.com/safrandrti/sirus/issues


Browse source code at https://github.com/cran/sirus


Authors: Clement Benard [aut, cre] , Marvin N. Wright [ctb, cph]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, Matrix, ROCR, ggplot2

Suggests survival, testthat

Linking to Rcpp


See at CRAN