Xgboost

This open-source software library offers a gradient boosting framework. It is compatible with various programming languages such as C++, Java, Python, R, Julia, Perl, and Scala, and can be used on Linux, Windows, and macOS. Developed by Tianqi Chen and the XGBoost Contributors, it was first introduced on March 27, 2014. Known as Extreme Gradient Boosting, it is a scalable and distributed gradient-boosted decision tree machine learning library.