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mboost (version 2.9-5)
Model-Based Boosting
Description
Functional gradient descent algorithm
(boosting) for optimizing general risk functions utilizing
component-wise (penalised) least squares estimates or regression
trees as base-learners for fitting generalized linear, additive
and interaction models to potentially high-dimensional data.
Models and algorithms are described in \doi{10.1214/07-STS242},
a hands-on tutorial is available from \doi{10.1007/s00180-012-0382-5}.
The package allows user-specified loss functions and base-learners.