A Novel Method for Classification of Bank Customers Based on the Rough Set and Rules Extraction
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Abstract
In recent years, credit scoring studies have been considered by researchers. In this paper, with a new approach based on statistical methods and rough set theory, the rules are extracted for classification. To this aim, the credit scoring data set of UCI University, Australia has been used. The proposed algorithm is very simple and comprehensible and is very efficient for the problem under study, in comparison to other known methods.
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Keywords: credit scoring; classification; rough set; statistics
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