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Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection

International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.

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Bibliographic Details
Main Authors: Maz Jamilah, Masnan, Ali Yeon, Md Shakaff, Prof. Dr., Ammar, Zakaria, Nor Idayu, Mahat
Other Authors: mazjamilah@unimap.edu.my
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2012
Subjects:
Linear discriminant analysis (LDA)
Multi sensor data fusion
Feature exstraction
Feature selection
Leave-one-out error rate
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/20497
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spelling my.unimap-204972012-07-19T13:55:52Z Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection Maz Jamilah, Masnan Ali Yeon, Md Shakaff, Prof. Dr. Ammar, Zakaria Nor Idayu, Mahat mazjamilah@unimap.edu.my aliyeon@unimap.edu.my Linear discriminant analysis (LDA) Multi sensor data fusion Feature exstraction Feature selection Leave-one-out error rate International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia. Linear discriminant analysis (LDA) has been widely used in the classification of multi sensor data fusion. This paper discusses the performance of LDA when the classifications were performed based on feature extraction and feature selection methods. Comparisons were also made based on single sensor modality. These strategies were studied using a honey dataset along with two types of sugar concentration collected from two types of sensors namely electronic nose (e-nose) and electronic tongue (e-tongue). Assessment of error rate was achieved using the leave-one-out procedure. 2012-07-19T13:55:52Z 2012-07-19T13:55:52Z 2012-02-27 Working Paper http://hdl.handle.net/123456789/20497 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2012) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Linear discriminant analysis (LDA)
Multi sensor data fusion
Feature exstraction
Feature selection
Leave-one-out error rate
spellingShingle Linear discriminant analysis (LDA)
Multi sensor data fusion
Feature exstraction
Feature selection
Leave-one-out error rate
Maz Jamilah, Masnan
Ali Yeon, Md Shakaff, Prof. Dr.
Ammar, Zakaria
Nor Idayu, Mahat
Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection
description International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.
author2 mazjamilah@unimap.edu.my
author_facet mazjamilah@unimap.edu.my
Maz Jamilah, Masnan
Ali Yeon, Md Shakaff, Prof. Dr.
Ammar, Zakaria
Nor Idayu, Mahat
format Working Paper
author Maz Jamilah, Masnan
Ali Yeon, Md Shakaff, Prof. Dr.
Ammar, Zakaria
Nor Idayu, Mahat
author_sort Maz Jamilah, Masnan
title Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection
title_short Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection
title_full Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection
title_fullStr Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection
title_full_unstemmed Comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection
title_sort comparing the classification performance of multi sensor data fusion based on feature extraction and feature selection
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/20497
_version_ 1643793090510585856
score 13.214268

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