Bankruptcy prediction using a data envelopment analysis

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2289

Title:	Bankruptcy prediction using a data envelopment analysis
Authors:	CIELEN, Agnes PEETERS, Ludo VANHOOF, Koen
Issue Date:	2004
Publisher:	ELSEVIER SCIENCE BV
Source:	European Journal of Operational Research, 154 (2), p. 526-532
Abstract:	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. (C) 2003 Elsevier B.V. All rights reserved.
Notes:	Univ Limburg, Dept Appl Econ, B-3590 Diepenbeek, Belgium.Vanhoof, K, Univ Limburg, Dept Appl Econ, Univ Campus, B-3590 Diepenbeek, Belgium.
Keywords:	data envelopment analysis;Data envelopment analysis;risk analysis;Risk analysis;decision support systems;Decision support systems;banking;Banking
Document URI:	http://hdl.handle.net/1942/2289
ISSN:	0377-2217
e-ISSN:	1872-6860
DOI:	10.1016/S0377-2217(03)00186-3
ISI #:	000187779600014
Rights:	2003 Elsevier B.V. All rights reserved.
Category:	A1
Type:	Journal Contribution
Validations:	ecoom 2005
Appears in Collections:	Research publications

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