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mboost: Model-Based Boosting
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.
Getting started
Browse package contents
Package details |
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| Author | Torsten Hothorn [aut], Peter Buehlmann [aut], Thomas Kneib [aut], Matthias Schmid [aut], Benjamin Hofner [aut, cre], Fabian Sobotka [ctb], Fabian Scheipl [ctb] |
| Maintainer | Benjamin Hofner <benjamin.hofner@fau.de> |
| License | GPL-2 |
| Version | 2.5-1 |
| URL | http://mboost.r-forge.r-project.org/ https://github.com/hofnerb/mboost |
| Package repository | View on R-Forge |
| Installation |
Install the latest version of this package by entering the following in R:
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