A Classification Algorithm based on an Association Rule of Multiple Frequent Item-sets

摘要：

It is necessary to discrete datasets firstly if you want to data mining an association rule of datasets consisting of many categorical and numeric attributes by a traditional algorithm. However, in view of the versatility, the applications of the traditional algorithm are limited. This paper propose a new algorithm called ARMFI(Association Rule of Multiple Frequent Item-sets) which can data mining an Association Rule from datasets consisting of many categorical and numeric attributes directly and completely, and overcome disadvantage of the traditional algorithm. The result has been proofed that the ARMFI shows better performances than the traditional algorithm.

关键词： Data mining ARMFI Frequent Item-sets Frequent Regions Classification

作者: ZhiHeng Liang

作者单位: Software College Shenyang Normal University Shenyang, China

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-5

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）