一种关联规则挖掘的优化算法

An Algorithm for Mining Optimized Association Rules

基于chi square检验、有趣度及信息增益理论,给出一种挖掘优化关联规则的算法.该算法将冗余的规则分为:一规则缺乏统计相关性,二规则不满足"新奇"的要求.实验结果表明,该算法可有效去除冗余规则,提高挖掘效率.

Based on theory of chisquare test, interest measure and information gain, an algorithm for mining optimized association rules is presented in this paper. In this algorithm,the redundant rules are divided into two parts: rules lacking statistical correlation and rules without 'novelty'. The experiment results show that the algorithm can prune the redundant rules effectively and improve the mining efficiency.