XGBoost : Reliable Large-scale Tree Boosting System

@inproceedings{Chen2015XGBoostR,
  title={XGBoost : Reliable Large-scale Tree Boosting System},
  author={Tianqi Chen and Carlos Guestrin},
  year={2015}
}
Tree boosting is an important type of machine learning algorithms that is widely used in practice. In this paper, we describe XGBoost, a reliable, distributed machine learning system to scale up tree boosting algorithms. The system is optimized for fast parallel tree construction, and designed to be fault tolerant under the distributed setting. XGBoost can handle tens of millions of samples on a single node, and scales beyond billions of samples with distributed computing. 
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