Merge remote-tracking branch 'dmlc/master'

CONTRIBUTORS.md

@@ -0,0 +1,31 @@
+Contributors of DMLC/XGBoost
+=======
+XGBoost has been developed and used by a group of active community. Everyone is more than welcomed to is a great way to make the project better and more accessible to more users.
+
+Comitters
+=======
+Committers are people who have made substantial contribution to the project and granted write access to the project.
+* [Tianqi Chen](https://github.com/tqchen), University of Washington
+  - Tianqi is a PhD working on large-scale machine learning, he is the creator of the project.
+* [Tong He](https://github.com/hetong007), Simon Fraser University
+  - Tong is a master student working on data mining, he is the maintainer of xgboost R package.
+* [Bing Xu](https://github.com/antinucleon)
+  - Bing is the original creator of xgboost python package and currently the maintainer of [XGBoost.jl](https://github.com/antinucleon/XGBoost.jl).
+* [Michael Benesty](https://github.com/pommedeterresautee)
+  - Micheal is a lawyer, data scientist in France, he is the creator of xgboost interactive analysis module in R.
+
+List of Contributors
+=======
+* [Full List of Contributors](https://github.com/dmlc/xgboost/graphs/contributors)
+  - To contributors: please add your name to the list when you submit a patch to the project:)
+* [Kailong Chen](https://github.com/kalenhaha)
+* [Skipper Seabold](https://github.com/jseabold)
+* [Zygmunt Zając](https://github.com/zygmuntz)
+* [Ajinkya Kale](https://github.com/ajkl)
+* [Boliang Chen](https://github.com/cblsjtu)
+* [Vadim Khotilovich](https://github.com/khotilov)
+* [Yangqing Men](https://github.com/yanqingmen)
+* [Engpeng Yao](https://github.com/yepyao)
+* [Giulio](https://github.com/giuliohome)
+* [Jamie Hall](https://github.com/nerdcha)
+* [Yen-Ying Lee](https://github.com/white1033)

README.md

@@ -6,7 +6,7 @@ DMLC/XGBoost
 An optimized general purpose gradient boosting library. The library is parallelized, and also provides an optimized distributed version.
 It implements machine learning algorithms under the [Gradient Boosting](https://en.wikipedia.org/wiki/Gradient_boosting) framework, including [Generalized Linear Model](https://en.wikipedia.org/wiki/Generalized_linear_model) (GLM) and [Gradient Boosted Decision Trees](https://en.wikipedia.org/wiki/Gradient_boosting#Gradient_tree_boosting) (GBDT). XGBoost can also be [distributed](#features) and scale to Terascale data
 
-Contributors: https://github.com/dmlc/xgboost/graphs/contributors
+Checkout our [Comitters and Contributors](CONTRIBUTORS.md) who keep make xgboost better.
 
 Documentations: [Documentation of dmlc/xgboost](doc/README.md)
 
@@ -38,6 +38,7 @@ Contributing to XGBoost
 XGBoost has been developed and used by a group of active community. Everyone is more than welcomed to is a great way to make the project better and more accessible to more users.
 * Checkout [Feature Wish List](https://github.com/dmlc/xgboost/labels/Wish-List) to see what can be improved, or open an issue if you want something.
 * Contribute to the [documents and examples](https://github.com/dmlc/xgboost/blob/master/doc/) to share your experience with other users.
+* Please add your name to [CONTRIBUTORS.md](CONTRIBUTORS.md) after your patch has been merged.
 
 Features
 ========