%0 Journal Article
%T 基于XGBoost的电商优惠券使用情况预测研究<br> Research on Prediction of the Use of Electronic Coupons Based on XGBoost
%A 熊艺华
%J Computer Science and Application
%P 1029-1035
%@ 2161-881X
%D 2019
%I Hans Publishing
%R 10.12677/CSA.2019.95116
%X <div align=\"justify\">
	<span style=\"font-size:14px;\">Boosting是十分有效的序列集成算法，在实践中有着广泛的应用。本文着重研究的XGBoost算法针对快速并行树结构进行了优化，并且在分布环境下容错，这使得它可以精确快速处理亿级数据、给出可靠的结果。本文分别通过模拟分析和实证分析，对比GBDT和RF算法验证了XGBoost的优良特性。</span><span style=\"font-size:14px;\"><br />
Boosting is a very effective sequence
integration algorithm, which has a wide range of applications in practice. This
paper focuses on the XGBoost algorithm, which optimizes the structure of fast
parallel tree and is fault-tolerant in distributed environment. This makes it
possible to process billions of data accurately and quickly and give reliable
results. In this paper, through simulation analysis and empirical analysis,
compared with GBDT and RF algorithm, XGBoost’s excellent characteristics are
verified.</span> 
</div>
%K XGBoost
%K GBDT
%K RF<br> XGBoost
%K GBDT
%K RF
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=30569