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    加权关联规则挖掘算法的研究

    RESEARCH ON ALGORITHMS OF MINING ASSOCIATION RULES WITH WEIGHTED ITEMS

    • 摘要: 讨论了加权关联规则的挖掘算法 .对布尔型属性 ,在挖掘算法 MINWAL ( O)和 MINWAL ( W)的基础上给出一种改进的加权关联规则挖掘算法 ,此算法能有效地考虑布尔型属性的重要性和规则中所含属性的个数 .对数量型属性 ,应用竞争聚集算法将数量型属性划分成若干个模糊集 ,并系统地提出加权模糊关联规则的挖掘算法 .此算法能有效地考虑数量型属性的重要性和规则中所含属性的个数 ,并适用于大型数据库

       

      Abstract: Algorithms for mining the weighted association rules are discussed in this paper. As far as Boolean attributes are concerned, an improved algorithm for mining the weighted association rules is provided based on the mining algorithms of MINWAL(O) and MINWAL(W). This algorithm can effectively consider the importance of Boolean attributes and the amount of attributes in the rule. As for quantitative attributes, they are divided into several fuzzy sets by the competitive agglomeration algorithm, and then the algorithm for mining weighted fuzzy association rules is provided. This algorithm can effectively consider the importance of quantitative attributes and the amount of attributes in the rule, and can be fit for large database.

       

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