Gender classification based on human radiation wave analysis

This paper describes an analysis of body radiation frequency for the purpose of gender classification. The human radiation frequency is experimentally studied from 33 healthy human subjects of 17 males and 16 females. KNN classifier is employed for gender classification. The number of training to te...

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Published in:Proceedings - 2011 UKSim 13th International Conference on Modelling and Simulation, UKSim 2011
Main Author: Jalil S.Z.A.; Taib M.N.; Idris H.A.; Yunus M.M.
Format: Conference paper
Language:English
Published: 2011
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-79956066200&doi=10.1109%2fUKSIM.2011.21&partnerID=40&md5=13fa7b35c0555ee7daf142e4bf49f56e
id 2-s2.0-79956066200
spelling 2-s2.0-79956066200
Jalil S.Z.A.; Taib M.N.; Idris H.A.; Yunus M.M.
Gender classification based on human radiation wave analysis
2011
Proceedings - 2011 UKSim 13th International Conference on Modelling and Simulation, UKSim 2011


10.1109/UKSIM.2011.21
https://www.scopus.com/inward/record.uri?eid=2-s2.0-79956066200&doi=10.1109%2fUKSIM.2011.21&partnerID=40&md5=13fa7b35c0555ee7daf142e4bf49f56e
This paper describes an analysis of body radiation frequency for the purpose of gender classification. The human radiation frequency is experimentally studied from 33 healthy human subjects of 17 males and 16 females. KNN classifier is employed for gender classification. The number of training to testing ratio was evaluated at 50 to 50, 60 to 40 and 70 to 30, to determine best classification accuracy. The data was analyzed separately of raw dataset and post-processing dataset to compare the classification results. At first, the data was classified using raw dataset and yields the classification accuracy of 93.8. Then, the post-processing data was applied to the classifier, and it was found that the classification accuracy was improved to perfect classification on k = 5, 7, 11 and 13 to 15. © 2011 IEEE.


English
Conference paper

author Jalil S.Z.A.; Taib M.N.; Idris H.A.; Yunus M.M.
spellingShingle Jalil S.Z.A.; Taib M.N.; Idris H.A.; Yunus M.M.
Gender classification based on human radiation wave analysis
author_facet Jalil S.Z.A.; Taib M.N.; Idris H.A.; Yunus M.M.
author_sort Jalil S.Z.A.; Taib M.N.; Idris H.A.; Yunus M.M.
title Gender classification based on human radiation wave analysis
title_short Gender classification based on human radiation wave analysis
title_full Gender classification based on human radiation wave analysis
title_fullStr Gender classification based on human radiation wave analysis
title_full_unstemmed Gender classification based on human radiation wave analysis
title_sort Gender classification based on human radiation wave analysis
publishDate 2011
container_title Proceedings - 2011 UKSim 13th International Conference on Modelling and Simulation, UKSim 2011
container_volume
container_issue
doi_str_mv 10.1109/UKSIM.2011.21
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-79956066200&doi=10.1109%2fUKSIM.2011.21&partnerID=40&md5=13fa7b35c0555ee7daf142e4bf49f56e
description This paper describes an analysis of body radiation frequency for the purpose of gender classification. The human radiation frequency is experimentally studied from 33 healthy human subjects of 17 males and 16 females. KNN classifier is employed for gender classification. The number of training to testing ratio was evaluated at 50 to 50, 60 to 40 and 70 to 30, to determine best classification accuracy. The data was analyzed separately of raw dataset and post-processing dataset to compare the classification results. At first, the data was classified using raw dataset and yields the classification accuracy of 93.8. Then, the post-processing data was applied to the classifier, and it was found that the classification accuracy was improved to perfect classification on k = 5, 7, 11 and 13 to 15. © 2011 IEEE.
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language English
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