LightGBM, Light Gradient Boosting Machine
==========


LightGBM is a gradient boosting framework that using tree based learning algorithms. It can outperform existing boosting tools on both learning efficiency and accuracy. Our [experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#comparison-experiment) shows that the result of efficiency and accuracy are better than other boosting tools.

LightGBM can leveraging multiple machines to speed-up the training procedure, which can achive linear speed-up in our [experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#parallel-experiment) settings. 

* [**Wiki**](https://github.com/Microsoft/LightGBM/wiki)
* [**Installation**](https://github.com/Microsoft/LightGBM/wiki/Installation-Guide) 
* [**Quick Start**](https://github.com/Microsoft/LightGBM/wiki/Quick-Start)
* [**Feature Highlight**](https://github.com/Microsoft/LightGBM/wiki/Feature-Highlight) 
* [**Parallel Learning Guide**](https://github.com/Microsoft/LightGBM/wiki/Parallel-Learning-Guide) 
* [**Parameters**](https://github.com/Microsoft/LightGBM/wiki/Parameters) 
* [**Examples**](https://github.com/Microsoft/LightGBM/tree/master/examples)