dmlc / xgboost

What it does

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.