Model-based Boosting 2.0
Citable Link (URL):http://resolver.sub.uni-goettingen.de/purl?gs-1/7553
First published (peer reviewed)
Journal of Machine Learning Research 2010; 11 p.2109-2113
We describe version 2.0 of the R add-on package mboost. The package implements boosting for optimizing general risk functions using component-wise (penalized) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.