LightGBM is a gradient boosting framework that is using tree based learning algorithms. It is designed to be distributed and efficient with following advantages:
- Fast training efficiency
- Low memory usage
- Fast training speed and high efficiency
- Lower memory usage
- Better accuracy
- Parallel learning supported
-Deal with large scale of data
-Capacity of handeling large scale data
For more details, please refer to [Features](https://github.com/Microsoft/LightGBM/wiki/Features).
