摘要
关联规则挖掘问题是数据挖掘的一个重要研究领域.对关联规则在相关性方面的不足进行了分析,提出了一种基于线性回归和反向验证的方法,来对关联规则的相关性进行论证.这种方法使对关联规则相关性的认识更加精确,并为关联规则能成为决策提供了支持.
The mining association rules is an important research field in datamining. This paper has analyzed some problems of association rules in the field of correlation and proposed a method that based on linear regression and backward verification to demonstrate the relevance of the association rules. This method has made the understanding of the relevant association rules more precise and supported association rules to be decision-making.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2008年第z1期291-294,共4页
Journal of Computer Research and Development
关键词
线性回归
反向验证
关联规则
相关性
linear regression
backward verification
association rule
correlation
