一种改进的关联规则挖掘算法研究

Hongfei Xu, Xuesong Liang, Wei Cui, Wei Liu
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引用次数: 3

摘要

数据挖掘关联规则是数据挖掘中的一个重要角色,它通过表达有形产品和服务之间的相互关系以及如何倾向于组合在一起,在市场分析中具有广泛的适用性。提出了谜语压缩的Apriori算法。并进行了仿真,结果表明Apriori算法可以大大提高谜语压缩的效率。它可以大大减少候选频繁项集,保持频繁项集的完备性,降低计算成本,提高算法效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on an Improved Association Rule Mining Algorithm
Data mining association rules is an important role of data mining because of its wide applicability in market analysis by expressing how tangible products and services relate to each other and how rend to group together. The paper proposed Apriori algorithm of riddling compression. And has carried on the simulation, the result demonstrated the Apriori algorithm of riddling compression can improve the efficiency greatly. It can greatly reduce the candidate frequent itemsets, keeps the completion of frequent itemsets, reduces the cost of computing, and improve the efficiency of algorithm.
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