Tree boosting is a highly effective and widely used machine learning method. In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges. We propose a nov...
XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. San Francisco California USA:ACM; 2016. p. 785-94. doi: 10.1145/2939672.2939785 . 返回引文位置Google Scholar 百度学术 万方数据 [19] Cawley GC , ...
XGBoost: A Scalable Tree Boosting System Tree boosting is a highly effective and widely used machine learning method. In this paper, we describe a scalable end-to-end tree boosting system called X... T Chen,C Guestrin - ACM 被引量: 1336发表: 2016年 Lithological Classification by ...
自此从代码角度交代了前文《xgboost: A Scalable Tree Boosting System论文及源码》的作者的具体实现思路,希望能够进一步加深对boosting方法的理解。目前最新的进展为XGBoost4J-Spark发布进一步融入Spark的应用场景中(2016/10/26)见附录[3],后续的发展会继续跟进。PS. TreeRefresher 代码中未见引用这里不做进一步介绍。
Tree boosting is a highly effective and widely used machine learning method. In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges. We propose a nove...