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pre: An R Package for Fitting Prediction Rule Ensembles

07/22/2017
by   Marjolein Fokkema, et al.
0

Prediction rule ensembles (PREs) are sparse collections of rules, offering highly interpretable regression and classification models. This paper presents the R package pre, which derives PREs through the methodology of Friedman and Popescu (2008). The implementation and functionality of package pre is described and illustrated through application on a dataset on the prediction of depression. Furthermore, accuracy and sparsity of PREs is compared with that of single trees, random forest and lasso regression in four benchmark datasets. Results indicate that pre derives ensembles with predictive accuracy comparable to that of random forests, while using a smaller number of variables for prediction.

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Code Repositories

pre

an R package for deriving Prediction Rule Ensembles


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pre

:exclamation: This is a read-only mirror of the CRAN R package repository. pre — Prediction Rule Ensembles. Homepage: https://github.com/marjoleinF/pre Report bugs for this package: https://github.com/marjoleinF/pre/issues


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