Rules Mining From Large Datasets Based on Rough Set

摘要：

The existing rough set based methods are not applicable for large data sets because of the high time and space complexity. In this paper, a new algorithm, called R_Apriori, is presented by which large data sets are divided into several parts, in combination with Apriori algorithm, implicated rules are derived in liner relation to size of data set. At last, this result is proved by experiments based on three classical UCI repositories.

作者: Hong Xiang-gong Wang Zhiyan Guo Sen Wang ping

作者单位: School of information engineering, NanChang University, School of computer science and engineering, South China University of Technology, GuangZhou,GuangDon School of information engineering, NanChang University, NanChang,JiangXi,China,330029

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 2119-2123

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）