CRAN/E | DidacticBoost

DidacticBoost

A Simple Implementation and Demonstration of Gradient Boosting

Installation

About

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.

github.com/dashaub/DidacticBoost
Bug report File report

Key Metrics

Version 0.1.1
R ≥ 3.1.1
Published 2016-04-19 2920 days ago
Needs compilation? no
License GPL-3
CRAN checks DidacticBoost results

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Maintainer

Maintainer

David Shaub

davidshaub@gmx.com

Authors

David Shaub

aut / cre

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.1.1
rpart ≥ 4.1-10

Suggests

testthat