From 40f9ba81f427be60da8819820706a8f4a9a9c0b7 Mon Sep 17 00:00:00 2001 From: Nikita Titov Date: Sat, 7 Oct 2017 19:32:42 +0300 Subject: [PATCH] Moved to Read the Docs. --- Home.md | 96 +-------------------------------------------------------- 1 file changed, 1 insertion(+), 95 deletions(-) diff --git a/Home.md b/Home.md index 11d7a21..8117497 100644 --- a/Home.md +++ b/Home.md @@ -1,95 +1 @@ -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/) -[![PyPI version](https://badge.fury.io/py/lightgbm.svg)](https://badge.fury.io/py/lightgbm) - -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 -- Lower memory usage -- Better accuracy -- Parallel and GPU learning supported -- Capable of handling large-scale data - -For more details, please refer to [Features](https://github.com/Microsoft/LightGBM/wiki/Features). - -[Experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#comparison-experiment) on public datasets show that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. What's more, the [experiments](https://github.com/Microsoft/LightGBM/wiki/Experiments#parallel-experiment) show that LightGBM can achieve a linear speed-up by using multiple machines for training in specific settings. - -News ----- - -06/20/2017: Python-package is on PyPI now. - -06/09/2017: [LightGBM Slack team](https://lightgbm.slack.com) is available. - -05/03/2017: LightGBM v2 stable release. - -04/10/2017 : LightGBM now supports GPU-accelerated tree learning. Please read our [GPU Tutorial](./docs/GPU-Tutorial.md) and [Performance Comparison](./docs/GPU-Performance.md). - -02/20/2017 : Update to LightGBM v2. - -02/12/2017: LightGBM v1 stable release. - -01/08/2017 : Release [**R-package**](./R-package) beta version, welcome to have a try and provide feedback. - -12/05/2016 : **Categorical Features as input directly**(without one-hot coding). Experiment on [Expo data](http://stat-computing.org/dataexpo/2009/) shows about 8x speed-up with same accuracy compared with one-hot coding. - -12/02/2016 : Release [**python-package**](./python-package) beta version, welcome to have a try and provide feedback. - - -External (unofficial) Repositories ----------------------------------- - -Julia Package: https://github.com/Allardvm/LightGBM.jl - -JPMML: https://github.com/jpmml/jpmml-lightgbm - - -Get Started And Documents -------------------------- -To get started, please follow the [Installation Guide](https://github.com/Microsoft/LightGBM/wiki/Installation-Guide) and [Quick Start](https://github.com/Microsoft/LightGBM/wiki/Quick-Start). - -* [**Wiki**](https://github.com/Microsoft/LightGBM/wiki) -* [**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) -* [**Features**](https://github.com/Microsoft/LightGBM/wiki/Features) -* [**Parallel Learning Guide**](https://github.com/Microsoft/LightGBM/wiki/Parallel-Learning-Guide) -* [**GPU Learning Tutorial**](https://github.com/Microsoft/LightGBM/blob/master/docs/GPU-Tutorial.md) -* [**Configuration**](https://github.com/Microsoft/LightGBM/wiki/Configuration) -* [**Document Indexer**](https://github.com/Microsoft/LightGBM/blob/master/docs/README.md) - -External Links --------------- -Useful if you are looking for details: - -* [**Read The Docs**](http://lightgbm.readthedocs.io/en/latest/) for an all in one documentation from this repository in a browsable fashion -* [**Laurae++ interactive documentation**](https://sites.google.com/view/lauraepp/parameters) for an interactive and detailed documentation on hyperparameters - -Support -------- - -You can ask questions and join the development discussion on: - -* [LightGBM Slack team](https://lightgbm.slack.com). - * Use [this invite link](https://join.slack.com/lightgbm/shared_invite/MTk1MjM1Mjg2NDA1LTE0OTY5NzMwNDgtYTRiZGQ5YzM3OQ) to join the team. - -You can also create **bug reports and feature requests** (not including questions) in [Github issues](https://github.com/Microsoft/LightGBM/issues). - -How to Contribute ------------------ - -LightGBM has been developed and used by many active community members. Your help is very valuable to make it better for everyone. - -- Check out [call for contributions](https://github.com/Microsoft/LightGBM/issues?q=is%3Aissue+is%3Aopen+label%3Acall-for-contribution) to see what can be improved, or open an issue if you want something. -- Contribute to the [tests](https://github.com/Microsoft/LightGBM/tree/master/tests) to make it more reliable. -- Contribute to the [documents](https://github.com/Microsoft/LightGBM/tree/master/docs) to make it clearer for everyone. -- Contribute to the [examples](https://github.com/Microsoft/LightGBM/tree/master/examples) to share your experience with other users. -- Check out [Development Guide](./docs/development.md). -- Open issue if you met problems during development. - -Microsoft Open Source Code of Conduct ------------- -This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. \ No newline at end of file +All documentation is located at https://lightgbm.readthedocs.io/en/latest/index.html. \ No newline at end of file