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DidacticBoost  

A Simple Implementation and Demonstration of Gradient Boosting
View on CRAN: Click here


Download and install DidacticBoost package within the R console
Install from CRAN:
install.packages("DidacticBoost")

Install from Github:
library("remotes")
install_github("cran/DidacticBoost")

Install by package version:
library("remotes")
install_version("DidacticBoost", "0.1.1")



Attach the package and use:
library("DidacticBoost")
Maintained by
David Shaub
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-04-19
Latest Update: 2016-04-19
Description:
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.
How to cite:
David Shaub (2016). DidacticBoost: A Simple Implementation and Demonstration of Gradient Boosting. R package version 0.1.1, https://cran.r-project.org/web/packages/DidacticBoost. Accessed 18 Sep. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited DidacticBoost R package
View DidacticBoost citation profile
Other R packages that DidacticBoost depends, imports, suggests or enhances
Complete documentation for DidacticBoost
Functions, R codes and Examples using the DidacticBoost R package
Some associated functions: fitBoosted . is.boosted . predict.boosted . 
Some associated R codes: Main.R .  Full DidacticBoost package functions and examples
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