XGBoost Documentation
=====================
This is document of xgboost library.
XGBoost is short for eXtreme gradient boosting. This is a library that is designed, and optimized for boosted (tree) algorithms.
The goal of this library is to push the extreme of the computation limits of machines to provide a ***scalable***, ***portable*** and ***accurate***
for large scale tree boosting.

This document is hosted at http://xgboost.readthedocs.org/. You can also browse most of the documents in github directly.


Package Documents
-----------------
This section contains language specific package guide.
* [XGBoost Command Line Usage Walkthrough](../demo/binary_classification/README.md)
* [Python Package Document](python/index.md)
* [R Package Document](R-package/index.md)
* [XGBoost.jl Julia Package](https://github.com/dmlc/XGBoost.jl)

User Guides
-----------
This section contains users guides that are general across languages.
* [Installation Guide](build.md)
* [Introduction to Boosted Trees](model.md)
* [Distributed Training Tutorial](tutorial/aws_yarn.md)
* [Frequently Asked Questions](faq.md)
* [External Memory Version](external_memory.md)
* [Learning to use XGBoost by Example](../demo)
* [Parameters](parameter.md)
* [Text input format](input_format.md)
* [Notes on Parameter Tunning](param_tuning.md)


Tutorials
---------
This section contains official tutorials of XGBoost package.
See [Awesome XGBoost](https://github.com/dmlc/xgboost/tree/master/demo) for links to mores resources.
* [Introduction to XGBoost in R](R-package/xgboostPresentation.md) (R package)
  - This is a general presentation about xgboost in R.
* [Discover your data with XGBoost in R](R-package/discoverYourData.md) (R package)
  - This tutorial explaining feature analysis in xgboost.
* [Introduction of XGBoost in Python](python/python_intro.md) (python)
  - This tutorial introduces the python package of xgboost
* [Understanding XGBoost Model on Otto Dataset](../demo/kaggle-otto/understandingXGBoostModel.Rmd) (R package)
  - This tutorial teaches you how to use xgboost to compete kaggle otto challenge.

Developer Guide
---------------
* [Contributor Guide](dev-guide/contribute.md)


Indices and tables
------------------

```eval_rst
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
```