Covering-based rough set classification system

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dc.authorid0000-0002-2956-3507en_US
dc.authorid0000-0002-7869-6373en_US
dc.authorid0000-0003-1840-9958en_US
dc.authorid0000-0002-8536-3438en_US
dc.contributor.authorKumar, S. Senthil
dc.contributor.authorInbarani, H. Hannah
dc.contributor.authorAzar, Ahmad Taher
dc.contributor.authorPolat, Kemal
dc.date.accessioned2021-06-23T19:45:15Z
dc.date.available2021-06-23T19:45:15Z
dc.date.issued2017
dc.departmentBAİBÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractMedical data classification is applied in intelligent medical decision support system to classify diseases into different categories. Several classification methods are commonly used in various healthcare settings. These techniques are fit for enhancing the nature of prediction, initial identification of sicknesses and disease classification. The categorization complexities in healthcare area are focused around the consequence of healthcare data investigation or depiction of medicine by the healthcare professions. This study concentrates on applying uncertainty (i.e. rough set)-based pattern classification techniques for UCI healthcare data for the diagnosis of diseases from different patients. In this study, covering-based rough set classification (i.e. proposed pattern classification approach) is applied for UCI healthcare data. Proposed CRS gives effective results than delicate pattern classifier model. The results of applying the CRS classification method to UCI healthcare data analysis are based upon a variety of disease diagnoses. The execution of the proposed covering-based rough set classification is contrasted with other approaches, such as rough set (RS)-based classification methods, Kth nearest neighbour, improved bijective soft set, support vector machine, modified soft rough set and back propagation neural network methodologies using different evaluating measures.en_US
dc.identifier.doi10.1007/s00521-016-2412-7
dc.identifier.endpage2888en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue10en_US
dc.identifier.scopus2-s2.0-84974802789en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2879en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-016-2412-7
dc.identifier.urihttps://hdl.handle.net/20.500.12491/9124
dc.identifier.volume28en_US
dc.identifier.wosWOS:000426865100005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kemal
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRough Seten_US
dc.subjectCovering-Based Rough Set (CRS)en_US
dc.subjectUCI Healthcare Dataen_US
dc.subjectClassificationen_US
dc.subjectExperimental Analysisen_US
dc.titleCovering-based rough set classification systemen_US
dc.typeArticleen_US

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