基于FP-tree频集模式的FP-Growth算法对关联规则挖掘的影响

The Effect of FP-Growth Algorithm Based on FP-tree Frequent Set Patterns on Association Rule Mining

通过对两个有代表性的算法Apriori和FP-Growth的剖析,说明频集模式挖掘的过程,比较有候选项集产生和无候选项集产生算法的特点,并给出FP-tree结构的构造方法以及对挖掘关联规则的影响,提出了对算法的改进方法.

An anatomy of two representative arithmetics of the Apriori and the FP Growth explains the mining process of frequent patterns item set. The improved method is put forward by comparing the arithmetic characteristics of candidate item set and non candidate item set. The constructing method of FP tree structure is provided and how it affects association rule mining is discussed.