Decision rule extraction method based on rough set theory and fuzzy set theory
Mingchun Wang, Wang Zheng-ou, Ming Zhang, Peng Yan
Abstract
Mingchun Wang, Wang Zheng-ou, Ming Zhang, Peng Yan
Abstract
A quantitative decision table can be transformed into a qualitative decision one by using the fuzzy set theory. This paper develops the definition of membership function mentioned in the literature, and proposes transforming rules from the quantitative decision table to the qualitative decision table with the properties of membership function. The rules can change an n-dimension quantitative decision table into an n-dimension qualitative decision table instead of a 3n-dimension one. So it greatly decreases afterward computing complexity of rule extraction using rough set theory, while increases the quality of extracted rules.
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A quantitative decision table can be transformed into a qualitative decision one by using the fuzzy set theory. This paper develops the definition of membership function mentioned in the literature, and proposes transforming rules from the quantitative decision table to the qualitative decision table with the properties of membership function. The rules can change an n-dimension quantitative decision table into an n-dimension qualitative decision table instead of a 3n-dimension one. So it greatly decreases afterward computing complexity of rule extraction using rough set theory, while increases the quality of extracted rules.
Key concepts: Decision table, Rough set, Decision rule, Fuzzy set, Dominance-based rough set approach, Membership function, Dimension (graph theory), Table (database)