mboost (version 2.9-7)

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.packages('mboost')

Monthly Downloads

7,087

Version

2.9-7

License

GPL-2

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Last Published

April 26th, 2022

Functions in mboost (2.9-7)