Fuzzy Correlation Rules Mining

نویسندگان

  • NANCY P. LIN
  • HAO-EN CHUEH
چکیده

General fuzzy association rules mining focuses on finding out the fuzzy itemsets or fuzzy attributes which frequently occur together. But two fuzzy itemsets which frequently occur together can not imply that there is always an interesting relationship between them. In this paper, we develop an alternative framework for mining interesting relationship between fuzzy itemsets based on fuzzy correlation analysis, and the discovered rules are called fuzzy correlation rules. The analysis of fuzzy correlation can show us the strength and the type of the linear relationship between two fuzzy itemsets, and hence can prevent generating the misleading rules. Key-Words: Fuzzy association rules, Fuzzy itemsets, Fuzzy correlation rules, Fuzzy correlation analysis, Linear relationship, Misleading rules

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تاریخ انتشار 2007