Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
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* [R] better categorical encoding explanation in vignette; fixes #1989

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README.md

eXtreme Gradient Boosting

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Documentation | Resources | Installation | Release Notes | RoadMap

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.

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XGBoost has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone.

License

© Contributors, 2016. Licensed under an Apache-2 license.

Reference