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Classification Method for Interval Valued Relational Database

机译:间隔估值关系数据库的分类方法

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Classification and association rules are important research issues and focuses of data mining technology. A classification method of association rules with linguistic variables, which fits for the interval valued relational database, is presented. In this classification method, values of the record in each attribute are partitioned into several linguistic variables by the fuzzy c-medoids algorithm. Then, Apriori algorithm is improved for mining interesting association rules with linguistic variables in the interval valued relational database. Last, we use these interesting association rules with linguistic variables to build classification system. The classification method is implemented on a constructed interval valued relational database. The experiment results show that the classification method has fine accuracy.
机译:分类和关联规则是数据挖掘技术的重要研究问题和焦点。提出了一种与语言变量的关联规则的分类方法,其适用于间隔值关系数据库。在该分类方法中,每个属性中的记录的值被模糊C-METOIDS算法划分为多个语言变量。然后,在间隔值关系数据库中具有语言变量的挖掘有趣关联规则,提高了Apriori算法。最后,我们使用这些有趣的关联规则与语言变量来构建分类系统。分类方法在构造的间隔值关系数据库上实现。实验结果表明,分类方法具有精确度。

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