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Fix broken links. (#6455)

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Co-authored-by: Hao Ziyu <haoziyu@qiyi.com>
Co-authored-by: fis <jm.yuan@outlook.com>
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2020-12-02 17:39:12 +08:00
committed by Hyunsu Cho
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commit 3efc4ea0d1
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doc/tutorials/model.rst
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Introduction to Boosted Trees
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XGBoost stands for "Extreme Gradient Boosting", where the term "Gradient Boosting" originates from the paper *Greedy Function Approximation: A Gradient Boosting Machine*, by Friedman.
This is a tutorial on gradient boosted trees, and most of the content is based on `these slides <http://homes.cs.washington.edu/~tqchen/pdf/BoostedTree.pdf>`_ by Tianqi Chen, the original author of XGBoost.
The **gradient boosted trees** has been around for a while, and there are a lot of materials on the topic.
This tutorial will explain boosted trees in a self-contained and principled way using the elements of supervised learning.