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: | , , , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2015
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| 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 http://umpir.ump.edu.my/id/eprint/10467/ http://dx.doi.org/10.1063/1.4915708 |
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| Summary: | 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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