LightGBM

LightGBM (Light Gradient Boosting Machine) is an open-source, high-performance gradient boosting framework developed by Microsoft. It uses tree-based learning algorithms and is designed for efficiency, scalability, and high accuracy, particularly with large datasets. Key innovations like Gradient-based One-Side Sampling (GOSS) and Exclusive Feature Bundling (EFB) contribute to its faster training speeds and lower memory usage. The library is actively maintained, with frequent releases, and is currently at version 4.6.0.