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modify model doc

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hetong007 2015-08-23 16:56:57 -07:00
parent 5196458305
commit 30c30d3696
2 changed files with 36 additions and 35 deletions
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doc/index.md
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@ -52,6 +52,7 @@ User Guide
----------
* [Frequently Asked Questions](faq.md)
* [Introduction to Boosted Trees](http://homes.cs.washington.edu/~tqchen/pdf/BoostedTree.pdf)
* [Introduction to the Model of XGBoost](model.md)
* [Using XGBoost in Python](python/python_intro.md)
* [Using XGBoost in R](../R-package/vignettes/xgboostPresentation.Rmd)
* [Learning to use XGBoost by Example](../demo)

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doc/model.md
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@ -166,7 +166,7 @@ Specifically we try to split a leaf into two leaves, and the score it gains is
Gain = \frac{1}{2} [\frac{G_L^2}{H_L+\lambda}+\frac{G_R^2}{H_R+\lambda}-\frac{(G_L+G_R)^2}{H_L+H_R+\lambda}] - \gamma
```
This formula can be decomposited as 1) the score on the new left leaf 2) the score on the new right leaf 3) The score on the original leaf 4) regularization on the additional leaf.
This formula can be decomposited as 1) the score on the new left leaf, 2) the score on the new right leaf, 3) The score on the original leaf and 4) regularization on the additional leaf.
The regularization in the end can be seen as the minimum increment from this split. In the end, we will prune out the split with a negative gain.