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Gender identification using support vector machines

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dc.contributor.affiliationen_US
dc.contributor.authorNur Ayuni Binti Jalaluddinen_US
dc.date.accessioned2023-05-03T15:34:01Z
dc.date.available2023-05-03T15:34:01Z
dc.date.issued2010
dc.description.abstractThis research study discusses about the gender identification and it is using support vector machines to meet the objective. Support vector machine (SVM) is a popular technique for classification. It is one of the recent methods for statistical learning and also addresses classification and regression problems. It can be considered as an alternative to neural networks. This thesis is introduces SVM theory application and its algorithmic implementations.en_US
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/20913
dc.language.isoenen_US
dc.subjectSystem identificationen_US
dc.subjectIdentity (Psychology)en_US
dc.titleGender identification using support vector machinesen_US
dc.typeResource Types::text::Thesisen_US
dspace.entity.typePublication
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