dmlc / xgboost
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, Dask, Flink and DataFlow
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Repository Summary (README)
Preview<img src="https://xgboost.ai/images/logo/xgboost-logo-trimmed.png" width=200/> eXtreme Gradient Boosting
Community | Documentation | Resources | Contributors | Release Notes
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 (Kubernetes, Hadoop, SGE, Dask, Spark, PySpark) and can solve problems beyond billions of examples.
License
© Contributors, 2021. Licensed under an Apache-2 license.
Contribute to XGBoost
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. Checkout the Community Page.
Reference
- Tianqi Chen and Carlos Guestrin. XGBoost: A Scalable Tree Boosting System. In 22nd SIGKDD Conference on Knowledge Discovery and Data Mining, 2016
- XGBoost originates from research project at University of Washington.
Sponsors
Become a sponsor and get a logo here. See details at Sponsoring the XGBoost Project. The funds are used to defray the cost of continuous integration and testing infrastructure (https://xgboost-ci.net).
Open Source Collective sponsors
Sponsors
<a href="https://www.nvidia.com/en-us/" target="_blank"><img src="https://raw.githubusercontent.com/xgboost-ai/xgboost-ai.github.io/master/images/sponsors/nvidia.jpg" alt="NVIDIA" width="72" height="72"></a> <a href="https://www.comet.com/site/?utm_source=xgboost&utm_medium=github&utm_content=readme" target="_blank"><img src="https://cdn.comet.ml/img/notebook_logo.png" height="72"></a> <a href="https://opencollective.com/tomislav1" target="_blank"><img src="https://images.opencollective.com/tomislav1/avatar/256.png" height="72"></a> <a href="https://databento.com/?utm_source=xgboost&utm_medium=sponsor&utm_content=display"><img src="https://raw.githubusercontent.com/xgboost-ai/xgboost-ai.github.io/refs/heads/master/images/sponsors/databento.png" height="72"></a> <a href="https://www.intel.com/" target="_blank"><img src="https://images.opencollective.com/intel-corporation/2fa85c1/logo/256.png" width="72" height="72"></a>
Backers
<a href="https://opencollective.com/xgboost#backers" target="_blank"><img src="https://opencollective.com/xgboost/backers.svg?width=890"></a>