基于FP-tree最大频繁项集的FP-MFI算法研究

Research on Maximal Frequent Item FP-MFI Algorithm Based on FP-tree

由于基于FP-tree的DMFIA算法在生成最大频繁项目集时会产生大量的候选频繁项集,通过改进传统的FP-tree结构,并提出了一种基于改进FP-tree的最大频繁模式挖掘算法FP-MFI,该算法不需要生成最大频繁候选项目集,改进的FP-tree是单向的,每个节点只保留了指向父节点的指针,可节约树空间。实验结果表明FP-MFI算法在数据库中频繁项目很多,而每一个事务中频繁项目很少的情况下,比同样基于FP-tree的DMFIA算法挖掘最大频繁项目集的效率更高。

Because of generating the candidate ones in the maximal frequent item-sets and it will bring on a batch of the candidate sets, through improving the traditional FP-tree structure and proposes the maximal frequent item-sets mining algorithm based on the improved FP- tree. It needn＇t to generate the candidate maximal frequent item-sets. The improved FP-tree is unilateralist, and each point saves the pointers of the parents＇, which will economize memory. It is shown in our experimental results that the FP-MFI algorithm is more effectively than the DMFIA also based on FP-tree in the mining maximal frequent item-sets when the frequent items are very much in database and they are so few in each transaction.