Publication:
Computational Intelligence Approach for Classification of Diabetes Mellitus Using Decision Tree

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dc.authorscopusid57021597800
dc.authorscopusid57214331952
dc.contributor.authorPekel, E.
dc.contributor.authorPekel Ozmen, E.P.
dc.date.accessioned2025-12-11T00:22:33Z
dc.date.issued2020
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Pekel] Engin, Hitit University, Corum, Corum, Turkey; [Pekel Ozmen] Ebru, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractDiabetes mellitus (DM) is a group of metabolic disorders with one common manifestation: elevated blood sugar or hyperglycemia. The diagnosis of diabetes is the most crucial point due to chronic hyperglycemia. This chapter improves the performance of the Classification and Regression Trees (CART) algorithm because the accurate classification of diabetes depends on the algorithm efficiency. Authors use the accuracy rate for the objective function in the prediction process by Genetic Algorithm (GA). The proposed GA-CART algorithm provides the best performance at 96.05%. © 2020, IGI Global. All rights reserved.en_US
dc.identifier.doi10.4018/978-1-7998-2581-4.ch005
dc.identifier.endpage103en_US
dc.identifier.isbn9781799825814
dc.identifier.isbn9781799825821
dc.identifier.scopus2-s2.0-85136987140
dc.identifier.startpage87en_US
dc.identifier.urihttps://doi.org/10.4018/978-1-7998-2581-4.ch005
dc.identifier.urihttps://hdl.handle.net/20.500.12712/36228
dc.language.isoenen_US
dc.publisherIGI Globalen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleComputational Intelligence Approach for Classification of Diabetes Mellitus Using Decision Treeen_US
dc.typeBook Parten_US
dspace.entity.typePublication

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