基于多最小支持度的关联规则挖掘

Based on Multiple Minimum Supports of Association Rules in Data Mining

分析了单最小支持度关联规则挖掘的局限性,提出了基于多最小支持度的关联规则挖掘模型,重点研究了多最小支持度MS-Apriori算法的基本思想,指出了算法的优缺点并通过实例说明发现频繁项集的方法,最后指出该算法的不足及改进算法.

This paper analyzed the limitation of the single minimum support degree of association rule mining. We put forward the model of association rule mining based on multiple minimum support. Our work focus on the multiple minimum support MS - Apriori algorithm the basic idea and points out the advantages and disadvantages of the algorithm with practical examples. Our work found that the method of frequent itemsets, and finally points out the shortage of the algorithm and improved algorithm.