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SEARCHING OPTIMAL SIGMA PARAMETER IN RADIAL BASIS KERNEL SUPPORT VECTOR MACHINE FOR CLASSIFICATION OF HIV SUB-TYPE VIRUSES

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dc.contributor.authorKurt, Zeyneb
dc.contributor.authorYavuz, Oguzhan
dc.date.accessioned2026-06-27T12:51:07Z
dc.date.issued2010
dc.description.abstractWe propose intelligent methods to classify two different HIV virus types, i.e., R5X4 and R5 or X4 with low computational complexity. Since R5X5 virus has same the features of R5 and X4 viruses, diagnosis of R5X4 can not be determined easily. In this study, the statistical data of R5X4, R5 and X4 was obtained by accessible residues and modelled by Auto-regressive (AR) model. After that the pre-processed data was used for determining the optimal sigma value in Radial Basis Kernel of Support Vector Machine (SVM).en
dc.identifier.endpage166
dc.identifier.isbn978-989-8425-19-5
dc.identifier.startpage163
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47399
dc.identifier.wos000392903400025
dc.language.isoeng
dc.publisherINSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION
dc.relation.conferenceInternational Conference on Signal Processing and Multimedia Application (SIGMAP 2010)
dc.relation.ispartofSIGMAP 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND MULTIMEDIA APPLICATION
dc.subjectAuto-regressive Model
dc.subjectHIV
dc.subjectSupport Vector Machine
dc.subjectROC Analysis
dc.subjectComputer Science
dc.subjectEngineering
dc.titleSEARCHING OPTIMAL SIGMA PARAMETER IN RADIAL BASIS KERNEL SUPPORT VECTOR MACHINE FOR CLASSIFICATION OF HIV SUB-TYPE VIRUSES
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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