Publication:
Diagnosis of Diabetes by Using Adaptive SVM

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dc.authorscopusid43261304900
dc.authorscopusid22953804000
dc.contributor.authorGürbüz, E.
dc.contributor.authorKilic, E.
dc.date.accessioned2020-06-21T09:36:51Z
dc.date.available2020-06-21T09:36:51Z
dc.date.issued2011
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Gürbüz] Emre, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Kilic] Erdal, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractIn this study, a new Support Vector Machine (SVM) based method for diagnosis of diabetes is proposed. In the proposed method, feature of adaptibility is added to the support vector machine. Thus, a new kind of SVM named "Adaptive SVM" is proposed, and smartly diagnosis of diseases is aimed. During the training and testing of this newly designed smart system, diabetes data set which is obtained from the medical database of University of California is used. It is observed that the classification rate of this newly proposed method on the diabetes data set is 100%. © 2011 IEEE.en_US
dc.identifier.doi10.1109/SIU.2011.5929584
dc.identifier.endpage49en_US
dc.identifier.isbn9781457704635
dc.identifier.scopus2-s2.0-79960408211
dc.identifier.startpage46en_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2011.5929584
dc.language.isotren_US
dc.relation.ispartof-- 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011en_US
dc.relation.journal2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleDiagnosis of Diabetes by Using Adaptive SVMen_US
dc.title.alternativeUyarlanabilir DVM Yöntemi Kullanılarak Şeker Hastalığının Teşhis Edilmesi?en_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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