一种基于概率的加权关联规则挖掘算法

Algorithm of mining association rules with weighted items based on probability

针对关联规则数据挖掘在实际应用中出现的问题:不能挖掘小概率事件中的关联规则, 提出了基于概率分布的加权关联规则挖掘算法。该算法同时改进了加权支持度计算方法,保持 Apriori算法的频繁集向下封闭的特性,并在实践中得到了有效的应用。

A algorithm of mining association rules with weighted items base on probability was designed,it solved the problem of the classical Apriori algorithm which can't mine association rules in the little probability items.At the same time the problem of invalidation of the 'downward closure property' in the weighted setting was solved by using an improved model of weighted support measurements. The algorithm is both scalable and efficient in discovering relationships in practical using.