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:	1.0.5
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
Published:	2022-06-10
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

Documentation:

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 Tuning parameters of function pre

Downloads:

Package source:	pre_1.0.5.tar.gz
Windows binaries:	r-devel: pre_1.0.5.zip, r-release: pre_1.0.5.zip, r-oldrel: pre_1.0.5.zip
macOS binaries:	r-release (arm64): pre_1.0.5.tgz, r-oldrel (arm64): pre_1.0.5.tgz, r-release (x86_64): pre_1.0.5.tgz, r-oldrel (x86_64): pre_1.0.5.tgz
Old sources:	pre archive

Reverse dependencies:

Reverse imports:	FREEtree
Reverse suggests:	plotmo

Linking:

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