Understanding Mahalanobis Distance Criterion for Feature Selection

Distance criteria are widely applied in cluster analysis and classification techniques. One of the well known and most commonly used distance criteria is the Mahalanobis distance, introduced by P. C. Mahalanobis in 1936. The functions of this distance have been extended to different problems such a...

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Main Authors: Maz Jamilah, Masnan, Nor Idayu, Mahat, Ali Yeon, Md Shakaff, Abu Hassan, Abdullah, Nur Zawatil, Ishqi Zakaria, Nurlisa, Yusuf, Norazian, Subari, Ammar, Zakaria, Abdul Hallis, Abdul Aziz
Format: Conference or Workshop Item
Language:English
English
Published: 2015
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/10467/1/Understanding%20Mahalanobis%20Distance%20Criterion%20for%20Feature%20Selection.pdf
http://umpir.ump.edu.my/id/eprint/10467/6/Understanding%20Mahalanobis%20Distance%20Criterion%20for%20Feature%20Selection.pdf
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author Maz Jamilah, Masnan
Nor Idayu, Mahat
Ali Yeon, Md Shakaff
Abu Hassan, Abdullah
Nur Zawatil, Ishqi Zakaria
Nurlisa, Yusuf
Norazian, Subari
Ammar, Zakaria
Abdul Hallis, Abdul Aziz
author_facet Maz Jamilah, Masnan
Nor Idayu, Mahat
Ali Yeon, Md Shakaff
Abu Hassan, Abdullah
Nur Zawatil, Ishqi Zakaria
Nurlisa, Yusuf
Norazian, Subari
Ammar, Zakaria
Abdul Hallis, Abdul Aziz
author_sort Maz Jamilah, Masnan
collection UMP
description Distance criteria are widely applied in cluster analysis and classification techniques. One of the well known and most commonly used distance criteria is the Mahalanobis distance, introduced by P. C. Mahalanobis in 1936. The functions of this distance have been extended to different problems such as detection of multivariate outliers, multivariate statistical testing, and class prediction problems. In the class prediction problems, researcher is usually burdened with problems of excessive features where useful and useless features are all drawn for classification task. Therefore, this paper tries to highlight the procedure of exploiting this criterion in selecting the best features for further classification process. Classification performance for the feature subsets of the ordered features based on the Mahalanobis distance criterion is included.
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spelling UMPir104672018-02-19T05:13:00Z http://umpir.ump.edu.my/id/eprint/10467/ Understanding Mahalanobis Distance Criterion for Feature Selection Maz Jamilah, Masnan Nor Idayu, Mahat Ali Yeon, Md Shakaff Abu Hassan, Abdullah Nur Zawatil, Ishqi Zakaria Nurlisa, Yusuf Norazian, Subari Ammar, Zakaria Abdul Hallis, Abdul Aziz TK Electrical engineering. Electronics Nuclear engineering Distance criteria are widely applied in cluster analysis and classification techniques. One of the well known and most commonly used distance criteria is the Mahalanobis distance, introduced by P. C. Mahalanobis in 1936. The functions of this distance have been extended to different problems such as detection of multivariate outliers, multivariate statistical testing, and class prediction problems. In the class prediction problems, researcher is usually burdened with problems of excessive features where useful and useless features are all drawn for classification task. Therefore, this paper tries to highlight the procedure of exploiting this criterion in selecting the best features for further classification process. Classification performance for the feature subsets of the ordered features based on the Mahalanobis distance criterion is included. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/10467/1/Understanding%20Mahalanobis%20Distance%20Criterion%20for%20Feature%20Selection.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/10467/6/Understanding%20Mahalanobis%20Distance%20Criterion%20for%20Feature%20Selection.pdf Maz Jamilah, Masnan and Nor Idayu, Mahat and Ali Yeon, Md Shakaff and Abu Hassan, Abdullah and Nur Zawatil, Ishqi Zakaria and Nurlisa, Yusuf and Norazian, Subari and Ammar, Zakaria and Abdul Hallis, Abdul Aziz (2015) Understanding Mahalanobis Distance Criterion for Feature Selection. In: AIP Conf. Proc., 1660, 050075 : International Conference on Mathematics, Engineering and Industrial Applications (ICoMEIA 2014) , 28-30 May 2014 , Penang. pp. 1-6.. http://dx.doi.org/10.1063/1.4915708
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Maz Jamilah, Masnan
Nor Idayu, Mahat
Ali Yeon, Md Shakaff
Abu Hassan, Abdullah
Nur Zawatil, Ishqi Zakaria
Nurlisa, Yusuf
Norazian, Subari
Ammar, Zakaria
Abdul Hallis, Abdul Aziz
Understanding Mahalanobis Distance Criterion for Feature Selection
title Understanding Mahalanobis Distance Criterion for Feature Selection
title_full Understanding Mahalanobis Distance Criterion for Feature Selection
title_fullStr Understanding Mahalanobis Distance Criterion for Feature Selection
title_full_unstemmed Understanding Mahalanobis Distance Criterion for Feature Selection
title_short Understanding Mahalanobis Distance Criterion for Feature Selection
title_sort understanding mahalanobis distance criterion for feature selection
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/10467/1/Understanding%20Mahalanobis%20Distance%20Criterion%20for%20Feature%20Selection.pdf
http://umpir.ump.edu.my/id/eprint/10467/6/Understanding%20Mahalanobis%20Distance%20Criterion%20for%20Feature%20Selection.pdf
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