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 described in
Fokkema (2020; <doi:10.18637/jss.v092.i12>) and Fokkema & Strobl
(2020; <doi:10.1037/met0000256>). The main function pre() derives
prediction rule ensembles consisting of rules and/or linear terms for
continuous, binary, count, multinomial, survival and multivariate
continuous responses. Function gpe() derives generalized prediction
ensembles, consisting of rules, hinge and linear functions of the
predictor variables.
| Version: |
1.0.8 |
| Depends: |
R (≥ 4.1.0) |
| 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, randomForest |
| Published: |
2025-09-06 |
| DOI: |
10.32614/CRAN.package.pre |
| Author: |
Marjolein Fokkema [aut, cre],
Benjamin Christoffersen [aut] |
| Maintainer: |
Marjolein Fokkema <m.fokkema at fsw.leidenuniv.nl> |
| BugReports: |
https://github.com/marjoleinF/pre/issues |
| License: |
GPL-2 | GPL-3 |
| URL: |
https://github.com/marjoleinF/pre |
| NeedsCompilation: |
no |
| Citation: |
pre citation info |
| Materials: |
README, NEWS |
| In views: |
MachineLearning |
| CRAN checks: |
pre results |