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...
| Main Authors: | , , , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2015
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| Online Access: | http://umpir.ump.edu.my/id/eprint/10467/ 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 |
| _version_ | 1848818754988802048 |
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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 |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T01:42:42Z |
| format | Conference or Workshop Item |
| id | ump-10467 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T01:42:42Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-104672018-02-19T05:13:00Z 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.. (Published) 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/ http://umpir.ump.edu.my/id/eprint/10467/ 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 |