xgboost/doc/index.md

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
• Python Package Document
• R Package Document
• XGBoost.jl Julia Package

User Guides

This section contains users guides that are general across languages.

• Installation Guide
• Introduction to Boosted Trees
• Distributed Training Tutorial
• Frequently Asked Questions
• External Memory Version
• Learning to use XGBoost by Example
• Parameters
• Text input format
• Notes on Parameter Tunning

Tutorials

This section contains official tutorials of XGBoost package. See Awesome XGBoost for links to mores resources.

• Introduction to XGBoost in R (R package)
  • This is a general presentation about xgboost in R.
• Discover your data with XGBoost in R (R package)
  • This tutorial explaining feature analysis in xgboost.
• Introduction of XGBoost in Python (python)
  • This tutorial introduces the python package of xgboost
• Understanding XGBoost Model on Otto Dataset (R package)
  • This tutorial teaches you how to use xgboost to compete kaggle otto challenge.

Developer Guide

• Contributor Guide

Indices and tables

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