基于扩展集合操作的频繁项集挖掘算法研究
Frequent Itemset Mining Algorithm Based on Extended Set Operators
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摘要: 对传统集合操作进行了扩展,提出了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算法比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。Abstract: The traditional set operator has been extended firstly,the FIS-ES algorithm has been presented on the basis of extended set operator.The detailed analysis about the complexity of algorithm is done in theory and experiment.It shows 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.
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