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tqchen 2015-01-18 22:56:29 -08:00
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README.md
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@ -19,6 +19,7 @@ Learning about the model: [Introduction to Boosted Trees](http://homes.cs.washin
What's New
=====
* [Distributed XGBoost](multi-node) is now available to scale to even larger scale problems
* XGBoost wins [Tradeshift Text Classification](https://kaggle2.blob.core.windows.net/forum-message-attachments/60041/1813/TradeshiftTextClassification.pdf?sv=2012-02-12&se=2015-01-02T13%3A55%3A16Z&sr=b&sp=r&sig=5MHvyjCLESLexYcvbSRFumGQXCS7MVmfdBIY3y01tMk%3D)
* XGBoost wins [HEP meets ML Award in Higgs Boson Challenge](http://atlas.ch/news/2014/machine-learning-wins-the-higgs-challenge.html)
* Thanks to Bing Xu, [XGBoost.jl](https://github.com/antinucleon/XGBoost.jl) allows you to use xgboost from Julia

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multi-node/README.md
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@ -10,7 +10,8 @@ This folder contains information of Distributed XGBoost.
Build
=====
* In the root folder, run ```./build.sh```, this will give you xgboost, which uses rabit allreduce
* In the root folder, type ```make```
- If you have C++11 compiler, it is recommended to use ```make cxx11=1```
Notes
====