一种基于集合的频繁项目集挖掘算法

A frequent itemsets mining algorithm based on set

频繁项目集挖掘是数据挖掘应用研究的一个重要研究内容。文章在FP-Growth算法的基础上,提出了一种基于集合的频繁项目集挖掘算法,该算法直接对FP-tree进行挖掘,不需要产生节点的条件模式基,因此在挖掘频繁模式集时节省了空间和时间,提高了算法的执行效率。最后对该算法进行了实例分析。

Frequem itemsets mining is one of important research contents about data mining applied research. After analyzing the FP- Growth algorithm, a frequent itemsets mining algorithm based on set is put forward, it does not need to produce condition pattern library for each node in the FP- tree, then use condition pattern library to construct correspondence condition FP- tree. This has saved the space and the time. at final some examples are also analysed for the algorithm.