- XGBoost R Package Online Documentation
- Check this out for detailed documents, examples and tutorials.
We are on CRAN now. For stable/pre-compiled(for Windows and OS X) version, please install from CRAN:
install.packages('xgboost')
For up-to-date version, please install from github. Windows user will need to install RTools first.
devtools::install_git('git://github.com/dmlc/xgboost',subdir='R-package')
You can also install from our weekly updated drat repo:
install.packages("drat", repos="https://cran.rstudio.com")
drat:::addRepo("dmlc")
install.packages("xgboost", repos="http://dmlc.ml/drat/", type="source")
For more detailed installation instructions, please see here.
- 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.