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Gender identification using support vector machines

This 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 regressi...

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Main Author: Nur Ayuni Binti Jalaluddin
Format: text::Thesis
Language:English
Published: 2023
Subjects:
System identification
Identity (Psychology)
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id my.uniten.dspace-20913
record_format dspace
spelling my.uniten.dspace-209132023-05-04T22:25:16Z Gender identification using support vector machines Nur Ayuni Binti Jalaluddin System identification Identity (Psychology) This 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. 2023-05-03T15:34:01Z 2023-05-03T15:34:01Z 2010 Resource Types::text::Thesis https://irepository.uniten.edu.my/handle/123456789/20913 en application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
topic System identification
Identity (Psychology)
spellingShingle System identification
Identity (Psychology)
Nur Ayuni Binti Jalaluddin
Gender identification using support vector machines
description This 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.
format Resource Types::text::Thesis
author Nur Ayuni Binti Jalaluddin
author_facet Nur Ayuni Binti Jalaluddin
author_sort Nur Ayuni Binti Jalaluddin
title Gender identification using support vector machines
title_short Gender identification using support vector machines
title_full Gender identification using support vector machines
title_fullStr Gender identification using support vector machines
title_full_unstemmed Gender identification using support vector machines
title_sort gender identification using support vector machines
publishDate 2023
_version_ 1806426394011369472
score 13.222552

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