mboost (version 2.9-9)

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 , a hands-on tutorial is available from . The package allows user-specified loss functions and base-learners.

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Install

install.packages('mboost')

Monthly Downloads

4,436

Version

2.9-9

License

GPL-2

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Last Published

December 7th, 2023

Functions in mboost (2.9-9)