Bankruptcy prediction using a data envelopment analysis

There is a growing recognition that a variety of machine learning problems can be approached advantageously by tools from the field of optimization. In this paper we compare the classification performance of a linear programming model, a data envelopment (DEA) model and a rule induction (C5.0) model...

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Bibliographic Details
Published in:European journal of operational research 2004-04, Vol.154 (2), p.526-532
Main Authors: Cielen, Anja, Peeters, Ludo, Vanhoof, Koen
Format: Article
Language:English
Subjects:
Banking
Data envelopment analysis
Decision support systems
Decision theory
Linear programming
Risk analysis
Risk assessment
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Summary:There is a growing recognition that a variety of machine learning problems can be approached advantageously by tools from the field of optimization. In this paper we compare the classification performance of a linear programming model, a data envelopment (DEA) model and a rule induction (C5.0) model. In terms of accuracy and employment the DEA model outperforms the other models.
ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(03)00186-3