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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
Citation: 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.
URI: http://hdl.handle.net/1942/2289
DOI:  Bankruptcy prediction using a data envelopment analysis
ISI #: 000187779600014
ISSN: 0377-2217
Category: A1
Type: Journal Contribution
Validation: ecoom, 2005
Appears in Collections: Research publications

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