Hybrid models based on rough set classifiers for setting credit rating decision rules in the global banking industry

Knowledge-Based Systems

Volumn 39, Issue , 2013, Pages 224-239

  Chen, You Shyang ^a   Cheng, Ching Hsue ^b  

^a HWA HSIA INSTITUTE OF TECHNOLOGY   (Taiwan)

^b NATIONAL YUNLIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Attribute reduction; Credit rating; Factor analysis; Minimum Entropy Principle Approach (MEPA); Rough Set Theory (RST)

Indexed keywords

ATTRIBUTE REDUCTION; COMPLEX DATA; CREDIT RATINGS; DATA SETS; DECISION RULES; DEFAULT PROBABILITIES; ECONOMIC STABILITY; EXPLANATORY POWER; GLOBAL BANKING; HYBRID MODEL; INVESTMENT RISKS; MANAGERIAL IMPLICATIONS; MINIMUM ENTROPY PRINCIPLE; MODEL VERIFICATION; MULTIPLE DIMENSIONS; NUMEROUS MODELS; PRACTICAL PROBLEMS; ROUGH SET; STATISTICAL TECHNIQUES;

ECONOMICS; FACTOR ANALYSIS; ROUGH SET THEORY;

RATING;

EID: 84871923661     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2012.11.004     Document Type: Article

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