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Genetic algorithms for the optimization of support vector machines in credit risk rating

Zopounidis Konstantinos, Doumpos, Michael, Satsiou, A

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URIhttp://purl.tuc.gr/dl/dias/A2731876-0C57-4AA4-B136-1113EE663F23-
Identifierhttp://www.iti.gr/~satsiou/Files/GAs%20&%20SVMs%20_Thessaloniki%20Conference_.pdf-
Languageen-
Extent10 pagesen
TitleGenetic algorithms for the optimization of support vector machines in credit risk ratingen
CreatorZopounidis Konstantinosen
CreatorΖοπουνιδης Κωνσταντινοςel
CreatorDoumpos, Michaelen
CreatorSatsiou, Aen
Content SummaryThe assessment of credit risk usually involves the development of rating models that classify credit applicants (firms or individuals) into predefined risk groups. A plethora of methodologies have been proposed to develop such rating models. Among them support vector machines (SVMs) have rapidly evolved in statistical learning theory as new modeling technique for developing classification models. However, their application requires the specification of several parameters. This paper proposes the use of genetic algorithms for the determination of optimal parameters for SVM models developed for credit risk assessment. The proposed methodology is applied to three data sets related with the development of credit scoring systems and is compared with discriminant analysis and logistic regression.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-29-
Date of Publication2005-
SubjectCapability, Financial (Financial literacy)en
SubjectFinancial capability (Financial literacy)en
SubjectLiteracy, Financialen
Subjectfinancial literacyen
Subjectcapability financial financial literacyen
Subjectfinancial capability financial literacyen
Subjectliteracy financialen
Bibliographic CitationA. Satsiou, M. Doumpos , C. Zopounidis .(2005). Genetic algorithms for the optimization of support vector machines in credit risk rating,Presented at 2nd International Conference on Enterprise Systems and Accounting. [online].Available: http://www.iti.gr/~satsiou/Files/GAs%20&%20SVMs%20_Thessaloniki%20Conference_.pdfen

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