Variable selection and oversampling in the use of smooth support vector machines for predicting the default risk of companies

Journal of Forecasting

Volumn 28, Issue 6, 2009, Pages 512-534

  Härdle, Wolfgang ^a   Lee, Yuh Jye ^a   Schäfer, Dorothea ^b   Yeh, Yi Ren ^c  

^a HUMBOLDT UNIVERSITY   (Germany)

^b DIW BERLIN   (Germany)

^c NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Insolvency prognosis; Non parametric classifi cation; Statistical learning theory; Support vector machines

Indexed keywords

DECISION MAKING; DISCRIMINANT ANALYSIS; ECONOMIC AND SOCIAL EFFECTS; ERRORS;

BASEL II; DEFAULT RISK; INSOLVENCY PROGNOSE; NON-PARAMETRIC CLASSIFI CATION; NONPARAMETRICS; OVER SAMPLING; SMOOTH SUPPORT VECTOR MACHINE; STATISTICAL LEARNING THEORY; SUPPORT VECTORS MACHINE; VARIABLES SELECTIONS;

SUPPORT VECTOR MACHINES;

EID: 70349171833     PISSN: 02776693     EISSN: 1099131X     Source Type: Journal    
DOI: 10.1002/for.1109     Document Type: Article

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