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Understanding Mahalanobis distance criterion for feature selection

Masnan, Maz Jamilah and Mahat, Nor Idayu and Md Shakaff, Ali Yeon and Abdullah, Abu Hassan and Zakaria, Nur Zawatil Ishqi and Yusuf, Nurlisa and Subari, Norazian and Zakaria, Ammar and Abdul Aziz, Abdul Hallis (2015) Understanding Mahalanobis distance criterion for feature selection. In: International Conference on Mathematics, Engineering and Industrial Applications 2014, 28–30 May 2014, Penang, Malaysia.

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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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN: 978-0-7354-1304-7
Subjects: Q Science > QA Mathematics
Divisions: School of Quantitative Sciences
Depositing User: Dr. Nor Idayu Mahat
Date Deposited: 04 Oct 2016 06:47
Last Modified: 04 Oct 2016 06:47
URI: http://repo.uum.edu.my/id/eprint/18750

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