基于矩阵的加权关联规则挖掘算法

关联规则挖掘是数据挖掘中的一个重要模型。传统的关联规则挖掘算法需要多次扫描数据库,生成大量候选项集,并且把数据库中各个项目按平等一致的方法对待,算法复杂且与实际情况不符。为此提出一种基于矩阵的加权关联规则挖掘算法,它只需扫描一次数据库,不生成候选项目集,可以快速挖掘出频率小但重要性高的项目。

Weighted Association Rules Mining Algorithm based on Matrix

Association rules mining is an important model in data mining. Traditional association rules mining algorithms need to scan the database many times and generate a great deal of candidate itemsets, and treat each item as uniformity. The algorithms are complicated and don＇t agree with practical condition. So, a weighted association rules mining algorithm based on matrix is proposed. It only needs to scan the database once, and does not generate candidate itemsets. Meanwhile, the items with low frequency and high importance can he mined quickly.