Forecasting the insolvency of US banks using Support Vector Machines (SVMs) based on local learning feature selection
Theophilos Papadimitriou, Periklis Gogas, Vasilios Plakandaras and John C. Mourmouris
| Year of publication: |
2013
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|---|---|
| Authors: | Papadimitriou, Theophilos ; Gkonkas, Periklēs ; Plakandaras, Vasilios ; Mourmouris, John C. |
| Published in: |
International journal of computational economics and econometrics. - Genève [u.a.] : Inderscience Enterprises, ISSN 1757-1170, ZDB-ID 2550146-X. - Vol. 3.2013, 1/2, p. 83-90
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| Subject: | bank insolvency | SVM | support vector machine | local learning | feature selection | Mustererkennung | Pattern recognition | Bankinsolvenz | Bank failure | Insolvenz | Insolvency | Lernprozess | Learning process | Theorie | Theory | Künstliche Intelligenz | Artificial intelligence | Kreditwürdigkeit | Credit rating | Prognoseverfahren | Forecasting model |
| Extent: | graph. Darst. |
|---|---|
| Type of publication: | Article |
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10010250320