一种新的频繁项集挖掘算法

Novel Frequent Itemset Mining Algorithm

首先对传统集合操作进行了扩展,提出基于扩展集合操作的最大频繁项集生成算法FIS-ES,并从理论和实验上对算法的复杂度进行了详细的分析。实验表明,在最小支持度较小的情况下,FIS-ES比Apriori算法具有更快的挖掘速度、更少的空间占用等优点,与Apriori有很好的互补性。

The traditional set operator has been extended, and then the FIS-ES algorithm is proposed on the basis of extended set operators. Experiments show that the new algorithm has advantages such as more efficient and less space used in the lower minimum support condition. It is a good complementarity for Apriori algorithm.