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.
|Author||Torsten Hothorn [aut], Peter Buehlmann [aut], Thomas Kneib [aut], Matthias Schmid [aut], Benjamin Hofner [aut, cre], Fabian Sobotka [ctb], Fabian Scheipl [ctb]|
|Date of publication||2018-01-16 13:41:55|
|Maintainer||Benjamin Hofner <[email protected]>|
|Package repository||View on R-Forge|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.