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guolinke authored Oct 11, 2016
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Expand Up @@ -9,7 +9,7 @@ LightGBM is a gradient boosting framework that using tree based learning algorit
- Parallel learning supported
- Deal with large scale of data

For the details, please refer to [Feature Highlights](https://github.com/Microsoft/LightGBM/wiki/Feature-Highlight).
For the 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.

Expand All @@ -20,12 +20,12 @@ For a quick start, please follow the [Installation Guide](https://github.com/Mi
Documents
------------
* [**Wiki**](https://github.com/Microsoft/LightGBM/wiki)
* [**Installation**](https://github.com/Microsoft/LightGBM/wiki/Installation-Guide)
* [**Installation Guide**](https://github.com/Microsoft/LightGBM/wiki/Installation-Guide)
* [**Quick Start**](https://github.com/Microsoft/LightGBM/wiki/Quick-Start)
* [**Examples**](https://github.com/Microsoft/LightGBM/tree/master/examples)
* [**Feature Highlight**](https://github.com/Microsoft/LightGBM/wiki/Feature-Highlight)
* [**Features**](https://github.com/Microsoft/LightGBM/wiki/Features)
* [**Parallel Learning Guide**](https://github.com/Microsoft/LightGBM/wiki/Parallel-Learning-Guide)
* [**Parameters**](https://github.com/Microsoft/LightGBM/wiki/Parameters)
* [**Configuration**](https://github.com/Microsoft/LightGBM/wiki/Configuration)


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