57 lines
2.4 KiB
Markdown
57 lines
2.4 KiB
Markdown
XGBoost Documentation
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=====================
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This is document of xgboost library.
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XGBoost is short for eXtreme gradient boosting. This is a library that is designed, and optimized for boosted (tree) algorithms.
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The goal of this library is to push the extreme of the computation limits of machines to provide a ***scalable***, ***portable*** and ***accurate***
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for large scale tree boosting.
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This document is hosted at http://xgboost.readthedocs.org/. You can also browse most of the documents in github directly.
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User Guide
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----------
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* [Installation Guide](build.md)
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* [Introduction to Boosted Trees](model.md)
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* [Python Package Document](python/index.md)
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* [R Package Document](R-package/index.md)
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* [XGBoost.jl Julia Package](https://github.com/dmlc/XGBoost.jl)
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* [Distributed Training](../demo/distributed-training)
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* [Frequently Asked Questions](faq.md)
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* [External Memory Version](external_memory.md)
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* [Learning to use XGBoost by Example](../demo)
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* [Parameters](parameter.md)
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* [Text input format](input_format.md)
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* [Notes on Parameter Tunning](param_tuning.md)
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Developer Guide
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---------------
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* [Contributor Guide](dev-guide/contribute.md)
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Tutorials
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---------
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Tutorials are self contained materials that teaches you how to achieve a complete data science task with xgboost, these
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are great resources to learn xgboost by real examples. If you think you have something that belongs to here, send a pull request.
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* [Binary classification using XGBoost Command Line](../demo/binary_classification/) (CLI)
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- This tutorial introduces the basic usage of CLI version of xgboost
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* [Introduction of XGBoost in Python](python/python_intro.md) (python)
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- This tutorial introduces the python package of xgboost
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* [Introduction to XGBoost in R](R-package/xgboostPresentation.md) (R package)
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- This is a general presentation about xgboost in R.
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* [Discover your data with XGBoost in R](R-package/discoverYourData.md) (R package)
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- This tutorial explaining feature analysis in xgboost.
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* [Understanding XGBoost Model on Otto Dataset](../demo/kaggle-otto/understandingXGBoostModel.Rmd) (R package)
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- This tutorial teaches you how to use xgboost to compete kaggle otto challenge.
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Resources
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---------
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See [awesome xgboost page](https://github.com/dmlc/xgboost/tree/master/demo) for links to other resources.
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Indices and tables
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------------------
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```eval_rst
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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```
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