* Change DefaultEvalMetric of classification from error to logloss * Change default binary metric in plugin/example/custom_obj.cc * Set old error metric in python tests * Set old error metric in R tests * Fix missed eval metrics and typos in R tests * Fix setting eval_metric twice in R tests * Add warning for empty eval_metric for classification * Fix Dask tests Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
XGBoost R Package for Scalable GBM
Resources
- XGBoost R Package Online Documentation
- Check this out for detailed documents, examples and tutorials.
Installation
We are on CRAN now. For stable/pre-compiled(for Windows and OS X) version, please install from CRAN:
install.packages('xgboost')
For more detailed installation instructions, please see here.
Examples
- Please visit walk through example.
- See also the example scripts for Kaggle Higgs Challenge, including speedtest script on this dataset and the one related to Otto challenge, including a RMarkdown documentation.
Development
- See the R Package section of the contributors guide.