Fix the bug report of https://github.com/dmlc/xgboost/issues/4328. I am the beginner of the Git so just try my best to follows the guide, https://xgboost.readthedocs.io/en/latest/contribute.html#r-package. I find there is no `dev` branch, so I pull this fix from my master branch to the original master branch.
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:)