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
- Version0.3.3
- R version≥ 3.6
- LicenseGPL-3
- Needs compilation?Yes
- Last release06/13/2022
Documentation
Team
Clement Benard
Marvin N. Wright
Show author detailsRolesContributor, Copyright holder
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- Depends1 package
- Imports5 packages
- Suggests3 packages
- Linking To2 packages