%0 Journal Article
%T Design of ensemble classifiers for mining concept drifts from data streams<br>数据流中概念漂移检测的集成分类器设计*
%A SUN Yue
%A MAO Guo-jun
%A LIU Xu
%A <br>孙岳
%A 毛国君
%A 刘旭
%J 计算机应用研究
%D 2008
%I 
%X A new mining algorithm called ICEA was proposed for mining concept drifts from data streams, which used ensemble multi-classifiers to detect concept changes from the data streams in an incremental way. The experimental results show that ICEA performs higher accuracy and better time efficiency on mining concept drifts from data streams.
%K data mining
%K data stream
%K concept drift<br>数据挖掘
%K 数据流
%K 概念漂移
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=1039B105AC731986BC51F45E7BEF207E&yid=67289AFF6305E306&vid=C5154311167311FE&iid=CA4FD0336C81A37A&sid=F260CE035846B3B8&eid=D5C9DC4EF2F78008&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=16