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[![PyPI version](https://badge.fury.io/py/xgboost.svg)](https://pypi.python.org/pypi/xgboost/) [![PyPI version](https://badge.fury.io/py/xgboost.svg)](https://pypi.python.org/pypi/xgboost/)
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|[Documentation](https://xgboost.readthedocs.org)| [Resources](demo/README.md) | [Installation](https://xgboost.readthedocs.org/en/latest/build.html)| [Documentation](https://xgboost.readthedocs.org) |
[Resources](demo/README.md) |
[Installation](https://xgboost.readthedocs.org/en/latest/build.html) |
[Release Notes](NEWS.md)| [Release Notes](NEWS.md)|
[RoadMap](https://github.com/dmlc/xgboost/issues/873)
XGBoost is an optimized distributed gradient boosting library designed to be highly *efficient*, *flexible* and *portable*. 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. 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. 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. 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.
What's New What's New
---------- ----------
* [XGBoost brick](NEWS.md) Release * [XGBoost brick](NEWS.md) Release
Features Ask a Question
-------- --------------
* 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 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/) * For generic questions for to share your experience using xgboost please use the [XGBoost User Group](https://groups.google.com/forum/#!forum/xgboost-user/)
Contributing to XGBoost 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. 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. * Check out [call for contributions](https://github.com/dmlc/xgboost/issues?q=is%3Aissue+is%3Aclosed+label%3Acall-for-contribution) and [Roadmap](https://github.com/dmlc/xgboost/issues/873) 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. * 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 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. - Please also update [NEWS.md](NEWS.md) on changes and improvements in API and docs.