A Simple Implementation and Demonstration of Gradient Boosting

A basic, clear implementation of tree-based gradient boosting designed to illustrate the core operation of boosting models. Tuning parameters (such as stochastic subsampling, modified learning rate, or regularization) are not implemented. The only adjustable parameter is the number of training rounds. If you are looking for a high performance boosting implementation with tuning parameters, consider the 'xgboost' package.


Reference manual

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0.1.1 by David Shaub, 5 years ago


Report a bug at https://github.com/dashaub/DidacticBoost/issues

Browse source code at https://github.com/cran/DidacticBoost

Authors: David Shaub [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Depends on rpart

Suggests testthat

See at CRAN