Commit 5c3dd8e5 authored by Qiwei Ye's avatar Qiwei Ye Committed by GitHub
Browse files

revert multiple badge for Travis

parent 49cd3d31
LightGBM, Light Gradient Boosting Machine LightGBM, Light Gradient Boosting Machine
========================================= =========================================
[![Build Status](https://travis-ci.org/Microsoft/LightGBM.svg?branch=master)](https://travis-ci.org/Microsoft/LightGBM)
[![Windows Build status](https://ci.appveyor.com/api/projects/status/1ys5ot401m0fep6l/branch/master?svg=true)](https://ci.appveyor.com/project/guolinke/lightgbm/branch/master)
[![Documentation Status](https://readthedocs.org/projects/lightgbm/badge/?version=latest)](http://lightgbm.readthedocs.io/) [![Documentation Status](https://readthedocs.org/projects/lightgbm/badge/?version=latest)](http://lightgbm.readthedocs.io/)
[![PyPI version](https://badge.fury.io/py/lightgbm.svg)](https://badge.fury.io/py/lightgbm) [![PyPI version](https://badge.fury.io/py/lightgbm.svg)](https://badge.fury.io/py/lightgbm)
|| Linux           | Windows           | macOS           |
|-----|----------------|----------------|----------------|
|CPU| [![CPU][1]][5] | [![CPU][4]][6] | [![CPU][7]][5] |
|GPU| [![GPU][2]][5] | [![CPU][4]][6] | |
|Pip| [![Pip][3]][5] | [![CPU][4]][6] | [![Pip][8]][5] |
[1]: https://travis-matrix-badges.herokuapp.com/repos/Microsoft/LightGBM/branches/master/1
[2]: https://travis-matrix-badges.herokuapp.com/repos/Microsoft/LightGBM/branches/master/3
[3]: https://travis-matrix-badges.herokuapp.com/repos/Microsoft/LightGBM/branches/master/4
[4]: https://ci.appveyor.com/api/projects/status/1ys5ot401m0fep6l/branch/master?svg=true
[5]: https://travis-ci.org/Microsoft/LightGBM
[6]: https://ci.appveyor.com/project/guolinke/lightgbm/branch/master
[7]: https://travis-matrix-badges.herokuapp.com/repos/Microsoft/LightGBM/branches/master/7
[8]: https://travis-matrix-badges.herokuapp.com/repos/Microsoft/LightGBM/branches/master/9
LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient with the following advantages: LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient with the following advantages:
- Faster training speed and higher efficiency - Faster training speed and higher efficiency
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