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.
Package details |
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Maintainer | |
License | GPL-2 |
Version | 2.9-11 |
URL | https://github.com/boost-R/mboost |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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