Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2289
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dc.contributor.authorCIELEN, Agnes-
dc.contributor.authorPEETERS, Ludo-
dc.contributor.authorVANHOOF, Koen-
dc.date.accessioned2007-11-13T15:02:43Z-
dc.date.available2007-11-13T15:02:43Z-
dc.date.issued2004-
dc.identifier.citationEuropean Journal of Operational Research, 154 (2), p. 526-532-
dc.identifier.issn0377-2217-
dc.identifier.urihttp://hdl.handle.net/1942/2289-
dc.description.abstractThere 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.-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.rights2003 Elsevier B.V. All rights reserved.-
dc.subject.otherdata envelopment analysis-
dc.subject.otherData envelopment analysis-
dc.subject.otherrisk analysis-
dc.subject.otherRisk analysis-
dc.subject.otherdecision support systems-
dc.subject.otherDecision support systems-
dc.subject.otherbanking-
dc.subject.otherBanking-
dc.titleBankruptcy prediction using a data envelopment analysis-
dc.typeJournal Contribution-
dc.identifier.epage532-
dc.identifier.issue2-
dc.identifier.spage526-
dc.identifier.volume154-
local.format.pages7-
local.bibliographicCitation.jcatA1-
dc.description.notesUniv Limburg, Dept Appl Econ, B-3590 Diepenbeek, Belgium.Vanhoof, K, Univ Limburg, Dept Appl Econ, Univ Campus, B-3590 Diepenbeek, Belgium.-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1016/S0377-2217(03)00186-3-
dc.identifier.isi000187779600014-
dc.identifier.eissn1872-6860-
local.provider.typeWeb of Science-
local.uhasselt.internationalno-
item.fullcitationCIELEN, Agnes; PEETERS, Ludo & VANHOOF, Koen (2004) Bankruptcy prediction using a data envelopment analysis. In: European Journal of Operational Research, 154 (2), p. 526-532.-
item.fulltextWith Fulltext-
item.accessRightsRestricted Access-
item.contributorCIELEN, Agnes-
item.contributorPEETERS, Ludo-
item.contributorVANHOOF, Koen-
item.validationecoom 2005-
crisitem.journal.issn0377-2217-
crisitem.journal.eissn1872-6860-
Appears in Collections:Research publications
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