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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.
Package details |
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Author | David Shaub [aut, cre] |
Maintainer | David Shaub <davidshaub@gmx.com> |
License | GPL-3 |
Version | 0.1.1 |
URL | https://github.com/dashaub/DidacticBoost |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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