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 solves many data science problems quickly and accurately. The same code runs on significant distributed environments (Hadoop, SGE, MPI) and can solve problems beyond billions of examples.