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dc.contributor.authorDağ, Hasan
dc.contributor.authorSayın, Kamran Emre
dc.contributor.authorYenidoğan, Işıl
dc.contributor.authorAlbayrak, Songül Varli
dc.contributor.authorAcar, Can
dc.date.accessioned2019-06-28T11:11:07Z
dc.date.available2019-06-28T11:11:07Z
dc.date.issued2012
dc.identifier.isbn9781467314466
dc.identifier.urihttps://hdl.handle.net/20.500.12469/1468
dc.identifier.urihttps://doi.org/10.1109/INISTA.2012.6247011
dc.description.abstractData mining application areas widen day by day. Among those areas medical area has been receiving quite a big attention. However working with very large data sets with many attributes is hard. Experts in this field use heavily advanced statistical analysis. The use of data mining techniques is fairly new. This paper compares three feature selection algorithms on medical data sets and comments on the importance of discretization of attributes. © 2012 IEEE.en_US]
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCorrelation Based Feature Selection (CFS)en_US
dc.subjectData miningen_US
dc.subjectDiscretizationen_US
dc.subjectFeature selection algorithmsen_US
dc.subjectGain ratioen_US
dc.subjectInformation gainen_US
dc.titleComparison of feature selection algorithms for medical dataen_US
dc.typeconferenceObjecten_US
dc.relation.journal2012 International Symposium on Innovations in Intelligent Systems and Applicationsen_US
dc.departmentFakülteler, İşletme Fakültesi, Yönetim Bilişim Sistemleri Bölümüen_US
dc.identifier.doi10.1109/INISTA.2012.6247011en_US
dc.identifier.scopus2-s2.0-84866605750en_US
dc.institutionauthorDağ, Hasanen_US
dc.institutionauthorSayın, Kamran Emreen_US
dc.institutionauthorYenidoğan, Işılen_US
dc.institutionauthorAcar, Canen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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