pre: Prediction Rule Ensembles

Derives prediction rule ensembles (PREs). Largely follows the procedure for deriving PREs as described in Friedman & Popescu (2008; <doi:10.1214/07-AOAS148>), with adjustments and improvements. The main function pre() derives prediction rule ensembles consisting of rules and/or linear terms for continuous, binary, count, multinomial, and multivariate continuous responses. Function gpe() derives generalized prediction ensembles, consisting of rules, hinge and linear functions of the predictor variables.

Version: 1.0.7
Depends: R (≥ 3.5.0)
Imports: earth, Formula, glmnet, graphics, methods, partykit (≥ 1.2-0), rpart, stringr, survival, Matrix, MatrixModels
Suggests: interp, datasets, doParallel, foreach, glmertree, grid, mlbench, testthat, mboost, ggplot2, caret, pROC, knitr, rmarkdown, mice, shape
Published: 2024-01-12
DOI: 10.32614/CRAN.package.pre
Author: Marjolein Fokkema [aut, cre], Benjamin Christoffersen [aut]
Maintainer: Marjolein Fokkema <m.fokkema at>
License: GPL-2 | GPL-3
NeedsCompilation: no
Citation: pre citation info
Materials: README NEWS
In views: MachineLearning
CRAN checks: pre results


Reference manual: pre.pdf
Vignettes: Dealing with missing data in fitting prediction rule ensembles
More sparse and relaxed: Fitting rule ensembles with the relaxed lasso
Faster computation
Tuning parameters of function pre


Package source: pre_1.0.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): pre_1.0.7.tgz, r-oldrel (arm64): pre_1.0.7.tgz, r-release (x86_64): pre_1.0.7.tgz, r-oldrel (x86_64): pre_1.0.7.tgz
Old sources: pre archive

Reverse dependencies:

Reverse imports: FREEtree
Reverse suggests: plotmo


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