Data weighting method on the basis of binary encoded output to solve multi-class pattern classification problems

dc.authorid0000-0003-1840-9958en_US
dc.contributor.authorPolat, Kemal
dc.date.accessioned2021-06-23T19:34:20Z
dc.date.available2021-06-23T19:34:20Z
dc.date.issued2013
dc.departmentBAİBÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractData weighting is of paramount importance with respect to classification performance in pattern recognition applications. In this paper, the output labels of datasets have been encoded using binary codes (numbers) and by this way provided a novel data weighting method called binary encoded output based data weighting (BEOBDW). In the proposed data weighting method, first of all, the output labels of datasets have been encoded with binary codes and then obtained two encoded output labels. Depending to these encoded outputs, the data points in datasets have been weighted using the relationships between features of datasets and two encoded output labels. To generalize the proposed data weighting method, five datasets have been used. These datasets are chain link (2 classes), two spiral (2 classes), iris (3 classes), wine (3 classes), and dermatology (6 classes). After applied BEOBDW to five datasets, the kappa-NN (nearest neighbor) classifier has been used to classify the weighted datasets. A set of experiments on used real world datasets demonstrated that the proposed data weighting method is a very efficient and has robust discrimination ability in the classification of datasets. BEOBDW method could be confidently used before many classification algorithms. (C) 2013 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.eswa.2013.02.004
dc.identifier.endpage4647en_US
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.issue11en_US
dc.identifier.scopus2-s2.0-84876031645en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage4637en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2013.02.004
dc.identifier.urihttps://hdl.handle.net/20.500.12491/7473
dc.identifier.volume40en_US
dc.identifier.wosWOS:000318052300034en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kemal
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectData Weightingen_US
dc.subjectBinary Encoded Output Based Data Weighting (BEOBDW)en_US
dc.subjectk-NN Classifieren_US
dc.subjectMulti-class Data Classificationen_US
dc.titleData weighting method on the basis of binary encoded output to solve multi-class pattern classification problemsen_US
dc.typeArticleen_US

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