XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Hadoop, SGE, MPI) and can solve problems beyond billions of examples.
install build get_started tutorials/index faq XGBoost User Forum <https://discuss.xgboost.ai> GPU Support <gpu/index> parameter prediction treemethod Python Package <python/index> R Package <R-package/index> JVM Package <jvm/index> Ruby Package <https://github.com/ankane/xgb> Swift Package <https://github.com/kongzii/SwiftXGBoost> Julia Package <julia> C Package <c> C++ Interface <c++> CLI Interface <cli> contrib/index