Genetic programming for feature selection in business failure prediction. Comparison of the use of financial variables and economic environment variables

UDC.coleccionInvestigaciónes_ES
UDC.conferenceTitleInternational Conference on INnovations in Intelligent SysTems and Applications (INISTA), Craiova, Romaniaes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.departamentoEmpresaes_ES
UDC.grupoInvDirección Financeira e Sistemas de Información para a Xestión (FYSIG)es_ES
UDC.grupoInvInformation Retrieval Lab (IRlab)es_ES
UDC.institutoCentroCITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicaciónes_ES
dc.contributor.authorBeade, Angel
dc.contributor.authorRodríguez López, Manuel
dc.contributor.authorSantos Reyes, José
dc.date.accessioned2025-04-21T08:20:54Z
dc.date.embargoEndDate9999-12-31es_ES
dc.date.embargoLift9999-12-31
dc.date.issued2024
dc.description.abstract[Abstract]: In this work we have experimented with the use of genetic programming as a feature selection method as well as a classifier to obtain business failure prediction models with different prediction temporal horizons. In the prediction models, a wide set of explanatory variables has been used, all of them based on the annual accounts of the company. In addition, an extended set of explanatory variables incorporating variables from the economic environment has been considered. Comparison of the prediction results between these alternatives shows a trend towards better results using the feature selection process, while there is no trend towards better results using economic environment variables.es_ES
dc.description.sponsorshipThis study was funded by the Spanish Ministry of Science and Innovation (projects PID2020-116201GB-I00 and PID2023-148531NB-I00), the European Union (Galicia 2014-2020 Program - European Regional Development Fund) and Xunta de Galicia, grant GPC ED431B 2022/33. Moreover, CITIC, as a center accredited for excellence within the Galician University System and a member of the CIGUS Network, receives subsidies from the Department of Education, Science, Universities, and Vocational Training of the Xunta de Galicia. Additionally, it is co-financed by the EU through the FEDER Galicia 2021-27 operational program (Ref. ED431G 2023/01)es_ES
dc.description.sponsorshipXunta de Galicia; ED431B 2022/33es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2023/01es_ES
dc.identifier.citationBeade, A. Rodríguez López, M. & Santos, J. (2024). Genetic programming for feature selection in business failure prediction. Comparison of the use of financial variables and economic environment variables. International Conference on INnovations in Intelligent SysTems and Applications (INISTA), Craiova, Romania, 2024, pp. 1-6. DOI:0.1109/INISTA62901.2024.10683824.es_ES
dc.identifier.doiDOI:0.1109/INISTA62901.2024.10683824
dc.identifier.urihttp://hdl.handle.net/2183/41795
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116201GB-I00/ES/RAZONAMIENTO AUTOMATICO Y APRENDIZAJE CON INDUCCION DE CONOCIMIENTOes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-148531NB-I00/ES/GENERACION DE EXPLICACIONES EN SISTEMAS INTELIGENTES HIBRIDOS PARA ASEGURAR LA FIABILIDADes_ES
dc.relation.uriDOI:0.1109/INISTA62901.2024.10683824es_ES
dc.rights.accessRightsembargoed accesses_ES
dc.subjectFeature selectiones_ES
dc.subjectGenetic programminges_ES
dc.subjectBusiness failurees_ES
dc.titleGenetic programming for feature selection in business failure prediction. Comparison of the use of financial variables and economic environment variableses_ES
dc.typeconference outputes_ES
dc.type.hasVersionVoRes_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationc85b6a48-b6d1-41c9-af79-3f6a2ee2e82d
relation.isAuthorOfPublicationf5e23200-9174-4def-9fde-e3ce6c3c26d5
relation.isAuthorOfPublication.latestForDiscoveryc85b6a48-b6d1-41c9-af79-3f6a2ee2e82d

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