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XGBoost Documentation

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##################### XGBoost Documentation #####################

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 <https://en.wikipedia.org/wiki/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.


Contents


.. toctree:: :maxdepth: 2 :titlesonly:

install build get_started tutorials/index faq 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/xgboost-ruby Swift Package https://github.com/kongzii/SwiftXGBoost Julia Package <julia> C Package <c> C++ Interface <c++> contrib/index changes/index