J4

• 计算机科学 • 上一篇    下一篇

一种关联规则挖掘的裁剪及优化方法

陆楠1,2   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012; 2. 深圳大学 信息工程学院, 广东省 深圳 518060
  • 收稿日期:2006-05-18 修回日期:1900-01-01 出版日期:2006-08-26 发布日期:2006-11-26
  • 通讯作者: 陆楠

An Optimization Method for Association Rules Pruning

LU Nan1,2   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China; 2. College of Information Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, China
  • Received:2006-05-18 Revised:1900-01-01 Online:2006-08-26 Published:2006-11-26
  • Contact: LU Nan

摘要: 采用χ2相关性检验和有趣度量定义了两种可能的“unexpected”规则, 对关联规则挖掘的裁剪与优化问题给出一个比较全面和系统的解决方法, 并结合规则裁剪提出了完整的算法思想, 通过对实验数据的关联挖掘, 挖掘出有效、 新奇和意想不到的规则. 实验结果表明, 该优化方法具有良好的有效性和伸缩性.

关键词: 数据挖掘, 关联规则, 规则裁剪, 模板规则, 有趣度

Abstract: We proposed a method addressing the optimization of the association rules pruning via two kinds of “unexpected” rules defined by the chisquare test and interest. We also provided an algorithm on the associat ion rules pruning. Based on the experiments, the method retrieved some effective and useful new rules which are often ignored by other methods. The experiment results also show that the method has a satisfying flexibility and effectiveness.

Key words: data mining, association rules, rules pruning, rules t emplate, interest measure

中图分类号: 

  • TP391