A NEW ACCURATE AND EFFICIENT APPROACH TO EXTRACT CLASSIFICATION RULES

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dc.contributor.authorKoklu, Murat
dc.contributor.authorKahramanli, Humar
dc.contributor.authorAllahverdi, Novruz
dc.date.accessioned2020-03-26T18:49:11Z
dc.date.available2020-03-26T18:49:11Z
dc.date.issued2014
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractA new method for extracting rules from multi-class datasets was proposed in this study. The proposed method was applied to 4 different data set. Discrete and real attributes were decoded in different ways. Discrete attributes were coded as binary whereas real attributes were coded by using two real values These values indicate the midpoint and the expansion of intervals of the attributes that form the rules. Classification success was used as fitness function of rule extraction. CLONALG which is Artificial Immune Systems (AIS) algorithm was used to optimize the fitness function. To apply the proposed method Iris, Wine, Glass and Abalone datasets were used. The datasets were obtained from machine learning repository of University of California at Irvine (UCI). The proposed method achieved prediction accuracy ratios of 100%, 99,44%, 77,10%, and 62,59% for Iris, Wine, Glass and Abalone datasets, respectively. When it is compared with the previous studies it has been seen that the proposed method achieved more successful results and has advantage in terms of complexity.en_US
dc.identifier.endpage486en_US
dc.identifier.issn1300-1884en_US
dc.identifier.issn1304-4915en_US
dc.identifier.issue3en_US
dc.identifier.startpage477en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/30550
dc.identifier.volume29en_US
dc.identifier.wosWOS:000343887100005en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isotren_US
dc.publisherGAZI UNIV, FAC ENGINEERING ARCHITECTUREen_US
dc.relation.ispartofJOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITYen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectRules extractionen_US
dc.subjectReal value codingen_US
dc.subjectMulti-class problemsen_US
dc.titleA NEW ACCURATE AND EFFICIENT APPROACH TO EXTRACT CLASSIFICATION RULESen_US
dc.typeArticleen_US

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