Probabilistic and discriminative group-wise feature selection methods for credit risk analysis

Expert Systems with Applications

Volumn 39, Issue 14, 2012, Pages 11709-11717

  Bozkurt Gönen, Gülefşan ^a   Gönen, Mehmet ^b   Gürgen, Fikret ^a  

^a BOGAZICI UNIVERSITY   (Turkey)

^b AALTO UNIVERSITY   (Finland)

Author keywords

Credit risk analysis; Feature selection; Multiple kernel learning; Probit classifier; Sparsity

Indexed keywords

BINARY CLASSIFICATION; BINARY CLASSIFIERS; BINARY FEATURES; CATEGORICAL VARIABLES; CREDIT RISK ANALYSIS; DATA COLLECTION; DATA SETS; DECISION PROCESS; FEATURE SELECTION ALGORITHM; FEATURE SELECTION METHODS; FINANCIAL CRISIS; FINANCIAL ORGANIZATIONS; INTERPRETABILITY; KERNEL CONSTRUCTION; MULTIPLE KERNEL LEARNING; OPERATIONAL RISKS; REAL-LIFE APPLICATIONS; SPARSITY;

DATA ACQUISITION; FEATURE EXTRACTION; LEARNING ALGORITHMS; RISK ASSESSMENT;

FINANCE;

EID: 84861809465     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.04.050     Document Type: Article

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