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sirus
View on CRAN: Click
here
Download and install sirus package within the R console
Install from CRAN:
install.packages("sirus")
Install from Github:
library("remotes")
install_github("cran/sirus")
Install by package version:
library("remotes")
install_version("sirus", "0.3.3")
Attach the package and use:
library("sirus")
Maintained by
Clement Benard
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-28
Latest Update: 2022-06-13
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>).
How to cite:
Clement Benard (2019). sirus: Stable and Interpretable RUle Set. R package version 0.3.3, https://cran.r-project.org/web/packages/sirus
Previous versions and publish date:
Other packages that cited sirus R package
View sirus citation profile
Other R packages that sirus depends,
imports, suggests or enhances
Functions, R codes and Examples using
the sirus R package
Some associated functions: sirus.cv . sirus.fit . sirus.plot.cv . sirus.predict . sirus.print .
Some associated R codes: RcppExports.R . formula.R . ranger.R . sirus.R . sirus_utility.R . utility.R . Full sirus package functions and examples
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