Package: sirus 0.3.3

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>).

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

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sirus/json (API)

Peer review:

Bug tracker:https://gitlab.com/drti/sirus

On CRAN:

5 exports 0.51 score 42 dependencies 12 scripts 189 downloads

Last updated 2 years agofrom:5ff41ba564. Checks:OK: 1 NOTE: 8. Indexed: yes.

Exports:sirus.cvsirus.fitsirus.plot.cvsirus.predictsirus.print

Dependencies:bitopscaToolsclicodetoolscolorspacefansifarverforeachggplot2glmnetgluegplotsgtablegtoolsisobanditeratorsKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppEigenrlangROCRscalesshapesurvivaltibbleutf8vctrsviridisLitewithr