Original author(s) | Guolin Ke[1] / Microsoft Research |
---|---|
Developer(s) | Microsoft and LightGBM contributors[2] |
Initial release | 2016 |
Stable release | v4.3.0[3]
/ January 15, 2024 |
Repository | github |
Written in | C++, Python, R, C |
Operating system | Windows, macOS, Linux |
Type | Machine learning, gradient boosting framework |
License | MIT License |
Website | lightgbm |
LightGBM, short for Light Gradient-Boosting Machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft.[4][5] It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and scalability.