基于分辨矩阵的含负属性项关联规则挖掘

Mining Association Rules Including Negative Items Based on Recognizable Matrix

Apriori算法存在候选集、频繁集产生效率低,丢失有趣强关联规则等问题,提出一种基于分辨矩阵可以采掘含负属性项强关联规则的改进算法,最后给出一个实际例子实现该算法.

Recognizable matrix, association rules including negative items and submit an xmprovea Apriori algorithm, aim at low efficiency of mining candidate itemsets, frequent itemsets and losing useful rules is presented. The implementation of algorithm by introducing an example is described.