@@ -10,9 +10,9 @@ LightGBM is a gradient boosting framework that is using tree based learning algo
- Parallel learning supported
- Deal with large scale of data
For the details, please refer to [Features](https://github.com/Microsoft/LightGBM/wiki/Features).
For more details, please refer to [Features](https://github.com/Microsoft/LightGBM/wiki/Features).
The [experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#comparison-experiment) on the public data also shows that LightGBM can outperform other existing boosting tools on both learning efficiency and accuracy, with significant lower memory consumption. What's more, the [experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#parallel-experiment) shows that LightGBM can achieve linear speed-up by using multiple machines for training in specific settings.
The [experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#comparison-experiment) on public dataset show that LightGBM outperform other existing boosting tools on both efficiency and accuracy, with significant lower memory consumption. What's more, the [experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#parallel-experiment) show that LightGBM can achieve linear speed-up by using multiple machines for training in specific settings.
