Package: DidacticBoost 0.1.1
DidacticBoost: 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.
Authors:
DidacticBoost_0.1.1.tar.gz
DidacticBoost_0.1.1.zip(r-4.5)DidacticBoost_0.1.1.zip(r-4.4)DidacticBoost_0.1.1.zip(r-4.3)
DidacticBoost_0.1.1.tgz(r-4.4-any)DidacticBoost_0.1.1.tgz(r-4.3-any)
DidacticBoost_0.1.1.tar.gz(r-4.5-noble)DidacticBoost_0.1.1.tar.gz(r-4.4-noble)
DidacticBoost_0.1.1.tgz(r-4.4-emscripten)DidacticBoost_0.1.1.tgz(r-4.3-emscripten)
DidacticBoost.pdf |DidacticBoost.html✨
DidacticBoost/json (API)
# Install 'DidacticBoost' in R: |
install.packages('DidacticBoost', repos = c('https://dashaub.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dashaub/didacticboost/issues
Last updated 9 years agofrom:b24338489a. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 22 2024 |
R-4.5-win | WARNING | Nov 22 2024 |
R-4.5-linux | WARNING | Nov 22 2024 |
R-4.4-win | WARNING | Nov 22 2024 |
R-4.4-mac | WARNING | Nov 22 2024 |
R-4.3-win | WARNING | Nov 22 2024 |
R-4.3-mac | WARNING | Nov 22 2024 |
Exports:fitBoostedis.boostedpredict.boosted
Dependencies:rpart
Readme and manuals
Help Manual
Help page | Topics |
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