Attribute weighting via genetic algorithms for attribute weighted artificial immune system (AWAIS) and its application to heart disease and liver disorders problems

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dc.contributor.authorOzsen, Seral
dc.contributor.authorGunes, Salih
dc.date.accessioned2020-03-26T17:37:56Z
dc.date.available2020-03-26T17:37:56Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractAn increasing number of algorithms and applications have coming into scene in the field of artificial immune systems (AIS) day by day. Whereas this increase is bringing successful studies, still, AIS is not an effective problem solver in some problem fields such as classification, regression, pattern recognition, etc. So far, many of the developed AIS algorithms have used a distance or similarity measure as the case in instance based learning (IBL) algorithms. The efficiency of IBL algorithms lies mainly in the weighting scheme they used. This weighting idea was taken as the objective of our study in that we used genetic algorithms to determine the weights of attributes and then used these weights in our previously developed Artificial Immune System (AWAIS). We evaluated the performance of new configuration (GA-AWAIS) on two medical datasets which were Statlog Heart Disease and BUPA Liver Disorders dataset. We also compared it with AWAIS for those problems. The obtained classification accuracy was very good with respect to both AWAIS and other common classifiers in literature. (C) 2007 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipScientific Research Projects of Selcuk UniversitySelcuk University [05401069]en_US
dc.description.sponsorshipThis study is supported by the Scientific Research Projects of Selcuk University (project no. 05401069).en_US
dc.identifier.doi10.1016/j.eswa.2007.09.063en_US
dc.identifier.endpage392en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage386en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2007.09.063
dc.identifier.urihttps://hdl.handle.net/20.500.12395/23310
dc.identifier.volume36en_US
dc.identifier.wosWOS:000264182800039en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial immune systemsen_US
dc.subjectAttribute weightingen_US
dc.subjectGenetic algorithmsen_US
dc.subjectClassification biasen_US
dc.subjectMedical classificationen_US
dc.titleAttribute weighting via genetic algorithms for attribute weighted artificial immune system (AWAIS) and its application to heart disease and liver disorders problemsen_US
dc.typeArticleen_US

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