Use of Kernel Functions in Artificial Immune Systems for the Nonlinear Classification Problems

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dc.contributor.authorÖzşen, Seral
dc.contributor.authorGüneş, Salih
dc.contributor.authorKara, Sadık
dc.contributor.authorLatifoğlu, Fatma
dc.date.accessioned2020-03-26T17:41:06Z
dc.date.available2020-03-26T17:41:06Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description5th IEEE International Special Topic Conference on Information Technology in Biomedicine -- OCT, 2006 -- Ioannina, GREECEen_US
dc.description.abstractDue to the fact that there exist only a small number of complex systems in artificial immune systems (AISs) that solve nonlinear problems, there is a need to develop nonlinear AIS approaches that would be among the well-known solution methods. In this study, we developed a kernel-based AIS to compensate for this deficiency by providing a nonlinear structure via transformation of distance calculations in the clonal selection models of classical AIS to kernel space. Applications of the developed system were conducted on Statlog heart disease dataset, which was taken from the University of California, Irvine Machine-Learning Repository, and on Doppler sonograms to diagnose atherosclerosis disease. The system obtained a classification accuracy of 85.93% for the Statlog heart disease dataset, while it achieved a 99.09% classification success for the Doppler dataset. With these results, our system seems to be a potential solution method, and it may be considered as a suitable method for hard nonlinear classification problems.en_US
dc.description.sponsorshipIEEE Engn Med & Biol Soc, Univ Ioannina, Natl Tech Univ Athensen_US
dc.identifier.citationLatifoğlu, F., Kara, S., Güneş, S., Özşen, S., (2009). Use of Kernel Functions in Artificial Immune Systems for the Nonlinear Classification Problems. Ieee Transactions on Information Technology in Biomedicine, 13(4), 621-628.
dc.identifier.doi10.1109/TITB.2009.2019637en_US
dc.identifier.endpage628en_US
dc.identifier.issn1089-7771en_US
dc.identifier.issn1558-0032en_US
dc.identifier.issue4en_US
dc.identifier.pmid19369167en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage621en_US
dc.identifier.urihttps://dx.doi.org/10.1109/TITB.2009.2019637
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24009
dc.identifier.volume13en_US
dc.identifier.wosWOS:000267835800026en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorÖzşen, Seral
dc.institutionauthorGüneş, Salih
dc.language.isoenen_US
dc.publisherIeee-inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Transactions on Information Technology in Biomedicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial immune systems (AISs)en_US
dc.subjectclassificationen_US
dc.subjectDoppler sonogramsen_US
dc.subjectnonlinear classificationen_US
dc.subjectStatlog heart diseaseen_US
dc.titleUse of Kernel Functions in Artificial Immune Systems for the Nonlinear Classification Problemsen_US
dc.typeArticleen_US

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