Usage of Class Dependency Based Feature Selection and Fuzzy Weighted Pre-Processing Methods on Classification of Macular Disease

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dc.contributor.authorPolat, Kemal
dc.contributor.authorKara, Sadık
dc.contributor.authorGüven, Aysegül
dc.contributor.authorGüneş, Salih
dc.date.accessioned2020-03-26T17:41:06Z
dc.date.available2020-03-26T17:41:06Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this paper, we propose a new feature selection method called class dependency based feature selection for dimensionality reduction of the macular disease dataset from pattern electroretinography (PERG) signals. in order to diagnosis of macular disease, we have used class dependency based feature selection as feature selection process. fuzzy weighted pre-processing as weighted process and decision tree classifier as decision making. The proposed system consists of three parts. First, we have reduced to 9 features number of features of macular disease dataset that has 63 features using class dependency based feature selection, which is first developed by ours. Second, the macular disease dataset that has 9 features is weighted by using fuzzy weighted pre-processing. And finally, decision tree classifier was applied to PERG signals to distinguish between healthy eye and diseased eye (macula diseases). The employed class dependency based feature selection, fuzzy weighted pre-processing and decision tree classifier have reached to 96.22%, 96.27% and 96.30% classification accuracies using 5-10-15-fold cross-validation, respectively. The results confirmed that the medical decision making system based on the class dependency based feature selection, fuzzy weighted pre-processing and decision tree classifier has potential in detecting the macular disease. The stated results show that the proposed method could point out the ability of design of a new intelligent assistance diagnosis system.en_US
dc.description.sponsorshipSelcuk UniversitySelcuk University [05401069]en_US
dc.description.sponsorshipThis study is supported by the Scientific Research Projects of Selcuk University (Project No. 05401069).en_US
dc.identifier.citationGüneş, S., Güven, A., Kara, S., Polat, K., (2009). Usage of Class Dependency Based Feature Selection and Fuzzy Weighted Pre-Processing Methods on Classification of Macular Disease. Expert Systems With Applications, 36(2), 2584-2591. Doi: 10.1016/j.eswa.2008.02.035
dc.identifier.doi10.1016/j.eswa.2008.02.035en_US
dc.identifier.endpage2591en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2584en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2008.02.035
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24008
dc.identifier.volume36en_US
dc.identifier.wosWOS:000262178100002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorGüneş, Salih
dc.institutionauthorPolat, Kemal
dc.language.isoenen_US
dc.publisherPergamon-elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryDiğeren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectMacular diseaseen_US
dc.subjectPattern electroretinographyen_US
dc.subjectClass dependency based feature selectionen_US
dc.subjectFuzzy weighted pre-processingen_US
dc.subjectDecision tree classifieren_US
dc.titleUsage of Class Dependency Based Feature Selection and Fuzzy Weighted Pre-Processing Methods on Classification of Macular Diseaseen_US
dc.typeReviewen_US

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