关联规则中FP-tree的最大频繁模式非检验挖掘算法

基于FP-tree的最大频繁模式挖掘算法是目前较为高效的频繁模式挖掘算法，针对这些算法需要递归生成条件FP-tree、做超集检验等问题，在分析DMFIA-1算法的基础上，提出了最大频繁模式的非检验挖掘算法NCMFP。该算法改进了FP-tree的结构，使挖掘过程中不需要生成条件频繁模式树也不需要超集检验。算法采用的预测剪枝策略减少了挖掘的次数，采用的求取公共交集的方式保证了挖掘结果的完整性。实验结果表明在支持度相对较小情况下，NCMFP的效率是同类算法的2~5倍。

Non-check mining algorithm of maximum frequent patterns in association rules based on FP-tree

The algorithms based on FP-tree, for mining maximal frequent patterns, have high performance but with many drawbacks. For example, they must recursively generate conditional FP trees, have to do the process of superset checking. In order to overcome these drawbacks of the existing algorithms, an algorithm Non Check Mining algorithm of Maximum Frequent Pattern (NCMFP）for mining maximal frequent patterns was put forward after the analysis of DMFIA-1 algorithm. In the algorithm, neither constructing conditional frequent pattern tree recursively nor superset checking was needed through modifying the structure of FP-tree. This algorithm reduced the number of mining through early prediction before mining. The application of a method to get the public intersection sets could obtain a complete result. The experiment shows that the efficiency of NCMFP is two to five times as much as that of the similar algorithms in the case of a relatively small support.