The Classification of Breast Cancer with Machine Learning Techniques

dc.contributor.authorKolay, Nurdan
dc.contributor.authorErdoğmuş, Pakize
dc.date.accessioned2020-04-30T23:32:42Z
dc.date.available2020-04-30T23:32:42Z
dc.date.issued2016
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionElectric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT) -- APR 26-27, 2016 -- Istanbul, TURKEYen_US
dc.descriptionWOS: 000387072000008en_US
dc.description.abstractIn this study, it is aimed to classify breast cancer data attained from UCI(University of California-Irvine), Machine Learning Laboratory with some Machine Learning Techniques. With this aim, clustering performance of some distance measures in Matlab(C) has been compared, using breast cancer data. Later without using any pre-processing, some of the machine learning techniques are used for the clustering breast cancer data, using WEKA data mining software(C). As a result, it has been seen that distance measures effects the clustering performance nearly 12 percentage and the succes of the classification varies from % 45 to % 79, according to the methods.en_US
dc.description.sponsorshipIEEE, EMB, Istanbul Arel Univen_US
dc.identifier.isbn978-1-5090-0876-6
dc.identifier.urihttps://hdl.handle.net/20.500.12684/4792
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2016 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (Ebbt)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMachine Learningen_US
dc.subjectBreast Canceren_US
dc.subjectK-means clusteringen_US
dc.subjectFuzzy C-meansen_US
dc.subjectSupport Vector Machinesen_US
dc.titleThe Classification of Breast Cancer with Machine Learning Techniquesen_US
dc.typeConference Objecten_US

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