Comparison of Open Source Data Mining Tools: Naive Bayes Algorithm Example

dc.contributor.authorÖzkan, Sibel Barın
dc.contributor.authorApaydın, Sultan Muhammed Fatih
dc.contributor.authorÖzkan, Yasin
dc.contributor.authorArgun, İrem Düzdar
dc.date.accessioned2020-04-30T22:41:22Z
dc.date.available2020-04-30T22:41:22Z
dc.date.issued2019
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.descriptionInternational Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science (EBBT) -- APR 24-26, 2019 -- Istanbul Arel Univ, Kemal Gozukara Campus, Istanbul, TURKEYen_US
dc.descriptionWOS: 000491430200014en_US
dc.description.abstractData Mining is a set of processes that use many disciplines together in the process of analyzing large data. It is the concept of data mining that combines computer technologies, statistical analysis techniques, database technologies and many disciplines. There are many commercial and open source programs to implement Data Mining applications. In this study, open source data mining programs WEKA, Orange, Knime is described. A sample is analyzed with the classification algorithm in all of these programs. In this study, it was aimed to determine the difference between these 3 open source Data Mining programs with Naive Bayes classification algorithm by taking Bay iris, breast cancer, wine, monk, balance es data sets from UCI Machine Learning Repository database. With this study, there are suggestions for making comparisons according to the outputs from the programs.en_US
dc.description.sponsorshipIEEE Turkey Sect, IEEE EMB, Erasmus+, Europassen_US
dc.identifier.isbn978-1-7281-1013-4
dc.identifier.urihttps://hdl.handle.net/20.500.12684/3175
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2019 Scientific Meeting On Electrical-Electronics & Biomedical Engineering And Computer Science (Ebbt)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectData Miningen_US
dc.subjectClassification Analysisen_US
dc.subjectNaive Bayesen_US
dc.titleComparison of Open Source Data Mining Tools: Naive Bayes Algorithm Exampleen_US
dc.typeConference Objecten_US

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