A Hybrid Method for Fast Finding the Reduct with the Best Classification Accuracy

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dc.contributor.authorHacibeyoglu, Mehmet
dc.contributor.authorArslan, Ahmet
dc.contributor.authorKahramanli, Sirzat
dc.date.accessioned2024-02-23T14:38:24Z
dc.date.available2024-02-23T14:38:24Z
dc.date.issued2013
dc.departmentNEÜen_US
dc.description.abstractUsually a dataset has a lot of reducts finding all of which is known to be an NP hard problem. On the other hand, different reducts of a dataset may provide different classification accuracies. Usually, for every dataset, there is only a reduct with the best classification accuracy to obtain this best one, firstly we obtain the group of attributes that are dominant for the given dataset by using the decision tree algorithm. Secondly we complete this group up to reducts by using discernibility function techniques. Finally, we select only one reduct with the best classification accuracy by using data mining classification algorithms. The experimental results for datasets indicate that the classification accuracy is improved by removing the irrelevant features and using the simplified attribute set which is derived from proposed method.en_US
dc.identifier.doi10.4316/AECE.2013.04010
dc.identifier.endpage64en_US
dc.identifier.issn1582-7445
dc.identifier.issn1844-7600
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-84890203115en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage57en_US
dc.identifier.urihttps://doi.org/10.4316/AECE.2013.04010
dc.identifier.urihttps://hdl.handle.net/20.500.12452/16513
dc.identifier.volume13en_US
dc.identifier.wosWOS:000331461300010en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherUniv Suceava, Fac Electrical Engen_US
dc.relation.ispartofAdvances In Electrical And Computer Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectClassification Algorithmsen_US
dc.subjectDecision Treesen_US
dc.subjectDiscernibility Functionen_US
dc.subjectFeature Selectionen_US
dc.titleA Hybrid Method for Fast Finding the Reduct with the Best Classification Accuracyen_US
dc.typeArticleen_US

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