Overview
XGBoost is an optimized distributed gradient boosting library, highly efficient, flexible, and portable. It implements machine learning algorithms under the Gradient Boosting framework, providing a parallel tree boosting approach (GBDT, GBM) to solve data science problems. It supports regression, classification, ranking, and user-defined objectives. XGBoost runs on various platforms, including Windows, Linux, OS X, AWS, GCE, Azure, and Yarn clusters, and integrates with Flink and Spark. The system is optimized for performance with limited resources, solving problems beyond billions of examples with the same code.
Common tasks