Affective state classification using Bayesian classifier

This paper elaborates the basic structure of a machine learning system in classifying affective state. There are several techniques in classifying the states depending on the type of input-output dataset. A proper selection of techniques is crucial in determining the success rate of the system pred...

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Main Authors: Ghazali, Aimi Shazwani, Sidek, Shahrul Na'im, Wok, Saodah
Format: Proceeding Paper
Language:English
English
English
Published: 2014
Subjects:
Online Access:http://irep.iium.edu.my/38240/
http://irep.iium.edu.my/38240/1/official_isms_paper.pdf
http://irep.iium.edu.my/38240/2/naim_uksim.pdf
http://irep.iium.edu.my/38240/8/38240_Affective%20state%20classification%20using%20Bayesian_Scopus.pdf
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author Ghazali, Aimi Shazwani
Sidek, Shahrul Na'im
Wok, Saodah
author_facet Ghazali, Aimi Shazwani
Sidek, Shahrul Na'im
Wok, Saodah
author_sort Ghazali, Aimi Shazwani
building IIUM Repository
collection Online Access
description This paper elaborates the basic structure of a machine learning system in classifying affective state. There are several techniques in classifying the states depending on the type of input-output dataset. A proper selection of techniques is crucial in determining the success rate of the system prediction. The paper proposes a machine learning technique in classifying affective states of human subjects by using Bayesian Network (BN). A structured experimental setup is designed to induce the affective states of the subjects by using a set of audiovisual stimulants. The affective states under study are happy, sad, and nervous. Preliminary results demonstrate the ability of the BN to predict human affective state with 86% accuracy.
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format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
English
English
last_indexed 2025-11-14T15:51:38Z
publishDate 2014
recordtype eprints
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spelling iium-382402019-01-10T05:02:43Z http://irep.iium.edu.my/38240/ Affective state classification using Bayesian classifier Ghazali, Aimi Shazwani Sidek, Shahrul Na'im Wok, Saodah TA164 Bioengineering This paper elaborates the basic structure of a machine learning system in classifying affective state. There are several techniques in classifying the states depending on the type of input-output dataset. A proper selection of techniques is crucial in determining the success rate of the system prediction. The paper proposes a machine learning technique in classifying affective states of human subjects by using Bayesian Network (BN). A structured experimental setup is designed to induce the affective states of the subjects by using a set of audiovisual stimulants. The affective states under study are happy, sad, and nervous. Preliminary results demonstrate the ability of the BN to predict human affective state with 86% accuracy. 2014 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/38240/1/official_isms_paper.pdf application/pdf en http://irep.iium.edu.my/38240/2/naim_uksim.pdf application/pdf en http://irep.iium.edu.my/38240/8/38240_Affective%20state%20classification%20using%20Bayesian_Scopus.pdf Ghazali, Aimi Shazwani and Sidek, Shahrul Na'im and Wok, Saodah (2014) Affective state classification using Bayesian classifier. In: 2014 Fifth International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2014), 27-29 Jan. 2014, Langkawi, Malaysia. http://uksim.info/isms2014/CD+ToC.pdf 10.1109/ISMS.2014.32)
spellingShingle TA164 Bioengineering
Ghazali, Aimi Shazwani
Sidek, Shahrul Na'im
Wok, Saodah
Affective state classification using Bayesian classifier
title Affective state classification using Bayesian classifier
title_full Affective state classification using Bayesian classifier
title_fullStr Affective state classification using Bayesian classifier
title_full_unstemmed Affective state classification using Bayesian classifier
title_short Affective state classification using Bayesian classifier
title_sort affective state classification using bayesian classifier
topic TA164 Bioengineering
url http://irep.iium.edu.my/38240/
http://irep.iium.edu.my/38240/
http://irep.iium.edu.my/38240/
http://irep.iium.edu.my/38240/1/official_isms_paper.pdf
http://irep.iium.edu.my/38240/2/naim_uksim.pdf
http://irep.iium.edu.my/38240/8/38240_Affective%20state%20classification%20using%20Bayesian_Scopus.pdf