【摘要】 关联规则挖掘是数据挖掘中重要的研究课题.为了减少关联规则挖掘中的无效关联规则,我们分析了其原因,提出了二种改进方法,即在衡量标准中增加影响度或相对置信度.根据它们的大小,我们将强关联规则分为正关联规则、无效关联规则、负关联规则.我们给出了用新衡量标准挖掘关联规则的改进算法,并用VisualFoxPro进行了试验.实验表明:新方法能明显减少无效关联规则的数目.更多还原

【Abstract】 Mining association rules is an important topic of data mining research. To reduce invalid rules in mining association rules, we have analyzed the reasons and presented to add the effect or the relative confidence in the judgment criteria. Based on the value of effect or relative confidence, we classify strong association rules into positive, invalid and negative association rules. We offer improving algorithms of mining association rules with new judgment criterion and make tests with Visual FoxPro. The tests indicate that the new methods stated in this paper can obviously reduce invalid association rules.更多还原