eXtreme Gradient Boosting =========== [](https://travis-ci.org/dmlc/xgboost) [](https://xgboost.readthedocs.org) [](./LICENSE) [](http://cran.r-project.org/web/packages/xgboost) [](https://pypi.python.org/pypi/xgboost/) [](https://gitter.im/dmlc/xgboost?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) 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. XGBoost is part of [DMLC](http://dmlc.github.io/) projects. Contents -------- * [Documentation and Tutorials](https://xgboost.readthedocs.org) * [Code Examples](demo) * [Installation](doc/build.md) * [Contribute to XGBoost](http://xgboost.readthedocs.org/en/latest/dev-guide/contribute.html) What's New ---------- * [XGBoost brick](NEWS.md) Release Features -------- * Easily accessible through CLI, [python](https://github.com/dmlc/xgboost/blob/master/demo/guide-python/basic_walkthrough.py), [R](https://github.com/dmlc/xgboost/blob/master/R-package/demo/basic_walkthrough.R), [Julia](https://github.com/antinucleon/XGBoost.jl/blob/master/demo/basic_walkthrough.jl) * Its fast! Benchmark numbers comparing xgboost, H20, Spark, R - [benchm-ml numbers](https://github.com/szilard/benchm-ml) * Memory efficient - Handles sparse matrices, supports external memory * Accurate prediction, and used extensively by data scientists and kagglers - [highlight links](https://github.com/dmlc/xgboost/blob/master/doc/README.md#highlight-links) * Distributed version runs on Hadoop (YARN), MPI, SGE etc., scales to billions of examples. Bug Reporting ------------- * For reporting bugs please use the [xgboost/issues](https://github.com/dmlc/xgboost/issues) page. * For generic questions or to share your experience using xgboost please use the [XGBoost User Group](https://groups.google.com/forum/#!forum/xgboost-user/) Contributing to XGBoost ----------------------- XGBoost has been developed and used by a group of active community members. Everyone is more than welcome to contribute. It is a way to make the project better and more accessible to more users. * Check out [Feature Wish List](https://github.com/dmlc/xgboost/labels/Wish-List) to see what can be improved, or open an issue if you want something. * Contribute to the [documents and examples](https://github.com/dmlc/xgboost/blob/master/doc/) to share your experience with other users. * Please add your name to [CONTRIBUTORS.md](CONTRIBUTORS.md) and after your patch has been merged. - Please also update [NEWS.md](NEWS.md) on changes and improvements in API and docs. License ------- © Contributors, 2015. Licensed under an [Apache-2](https://github.com/dmlc/xgboost/blob/master/LICENSE) license.