mboost (2.0-6)
Model-Based Boosting.
http://cran.r-project.org/web/packages/mboost
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.
Maintainer:
Torsten Hothorn
Author(s): Torsten Hothorn, Peter Buehlmann, Thomas Kneib, Matthias Schmid and Benjamin Hofner
License: GPL-2
Uses: lattice, Matrix, survival, ipred, party, multicore, MASS
Reverse depends: expectreg
Reverse suggests: caret, Daim, HSAUR2, multcomp
Released 3 months ago.
7 previous versions
- mboost_2.0-3. Released 6 months ago.
- mboost_2.0-0. Released 7 months ago.
- mboost_1.1-4. Released 10 months ago.
- mboost_1.1-3. Released 11 months ago.
- mboost_1.1-2. Released about 1 year ago.
- mboost_1.1-1. Released over 1 year ago.
- mboost_1.0-1. Released about 3 years ago.
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