Apriori算法[1]是一种最有影响的挖掘布尔关联规则频繁项集的算法。其核心是基于两阶段频集思想的递推算法。该关联规则在分类上属于单维、单层、布尔关联规则。在这里，所有支持度大于最小支持度的项集称为频繁项集，简称频集。-Apriori algorithm [1] is one of the most influential association rule mining algorithm Boolean frequent item sets. Its core is based on a t

支持多最小支持度多层次的关联规则挖掘，数据集为T10I4D100K，多最小支持度阈值为MSchange-Support multiple minimum supports multi-level association rule mining, data set T10I4D100K, more than the minimum support threshold MSchange

支持多最小支持度多层次的关联规则挖掘算法，基于fp-growth方法优化实现-Support multiple minimum supports multi-level association rule mining algorithms, optimization fp-growth-based approach to achieve