c35be9dc40
* [R-package] replace uses of T and F with TRUE and FALSE * enable linting * Remove skip Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
XGBoost R Feature Walkthrough
- Basic walkthrough of wrappers
- Train a xgboost model from caret library
- Cutomize loss function, and evaluation metric
- Boosting from existing prediction
- Predicting using first n trees
- Generalized Linear Model
- Cross validation
- Create a sparse matrix from a dense one
- Use GPU-accelerated tree building algorithms
Benchmarks
Notes
- Contribution of examples, benchmarks is more than welcomed!
- If you like to share how you use xgboost to solve your problem, send a pull request:)