About Anaconda Help Download Anaconda

r / packages / r-didacticboost

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.

Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/r/r-didacticboost/badges/version.svg
badge
https://anaconda.org/r/r-didacticboost/badges/latest_release_date.svg
badge
https://anaconda.org/r/r-didacticboost/badges/latest_release_relative_date.svg
badge
https://anaconda.org/r/r-didacticboost/badges/platforms.svg
badge
https://anaconda.org/r/r-didacticboost/badges/license.svg
badge
https://anaconda.org/r/r-didacticboost/badges/downloads.svg

© 2025 Anaconda, Inc. All Rights Reserved. (v4.0.6) Legal | Privacy Policy