xgboost

XGBoost (eXtreme Gradient Boosting) 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 and provides parallel tree boosting (also known as GBDT, GBM) that solves many data science problems in a fast and accurate way. The same code runs on major distributed environments (Kubernetes, Hadoop, SGE, Dask, Spark, PySpark) and can handle problems beyond billions of examples. It supports Python, R, Java, Scala, C, and more. XGBoost is widely used in competitions and industry. The project is licensed under Apache-2.0 and has an active community for contributions.