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Application of support vector machines on the basis of the first Hungarian bankruptcy model

Virág, Miklós and Nyitrai, Tamás (2013) Application of support vector machines on the basis of the first Hungarian bankruptcy model. Society and Economy, 35 (2). pp. 227-248. DOI 10.1556/SocEc.35.2013.2.6

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Official URL: http://www.akademiai.com/content/w459170887q183u5/


Abstract

In our study we rely on a data mining procedure known as support vector machine (SVM) on the database of the first Hungarian bankruptcy model. The models constructed are then contrasted with the results of earlier bankruptcy models with the use of classification accuracy and the area under the ROC curve. In using the SVM technique, in addition to conventional kernel functions, we also examine the possibilities of applying the ANOVA kernel function and take a detailed look at data preparation tasks recommended in using the SVM method (handling of outliers). The results of the models assembled suggest that a significant improvement of classification accuracy can be achieved on the database of the first Hungarian bankruptcy model when using the SVM method as opposed to neural networks.

Item Type:Article
Uncontrolled Keywords:bankruptcy prediction, classification, data preparation, outliers, support vector machines (SVM), ROC curve analysis, JEL codes: C33, C45, C51, C52, C53, G33
Subjects:Mathematics, Econometrics
DOI:10.1556/SocEc.35.2013.2.6
ID Code:1306
Deposited By: Ádám Hoffmann
Deposited On:16 Jul 2013 08:08
Last Modified:16 Jul 2013 08:08

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