Trace ratio criterion for feature extraction in classification
A generalized linear discriminant analysis based on trace ratio criterion algorithm (GLDA-TRA) is derived to extract features for classification. With the proposed GLDA-TRA, a set of orthogonal features can be extracted in succession. Each newly extracted feature is the optimal feature that maximize...
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2014
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sg-ntu-dr.10356-799072020-03-07T13:57:21Z Trace ratio criterion for feature extraction in classification Li, Guoqi Wen, Changyun Wei, Wei Xu, Yi Ding, Jie Zhao, Guangshe Shi, Luping School of Electrical and Electronic Engineering DRNTU::Engineering::Mathematics and analysis A generalized linear discriminant analysis based on trace ratio criterion algorithm (GLDA-TRA) is derived to extract features for classification. With the proposed GLDA-TRA, a set of orthogonal features can be extracted in succession. Each newly extracted feature is the optimal feature that maximizes the trace ratio criterion function in the subspace orthogonal to the space spanned by the previous extracted features. Published version 2014-07-03T01:26:05Z 2019-12-06T13:36:31Z 2014-07-03T01:26:05Z 2019-12-06T13:36:31Z 2014 2014 Journal Article Li, G., Wen, C., Wei, W., Xu, Y., Ding, J., Zhao, G., et al. (2014). Trace Ratio Criterion for Feature Extraction in Classification. Mathematical Problems in Engineering, 2014, 725204-. 1024-123X https://hdl.handle.net/10356/79907 http://hdl.handle.net/10220/20016 10.1155/2014/725204 en Mathematical problems in engineering © 2014 Guoqi Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf |
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DRNTU::Engineering::Mathematics and analysis Li, Guoqi Wen, Changyun Wei, Wei Xu, Yi Ding, Jie Zhao, Guangshe Shi, Luping Trace ratio criterion for feature extraction in classification |
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A generalized linear discriminant analysis based on trace ratio criterion algorithm (GLDA-TRA) is derived to extract features for classification. With the proposed GLDA-TRA, a set of orthogonal features can be extracted in succession. Each newly extracted feature is the optimal feature that maximizes the trace ratio criterion function in the subspace orthogonal to the space spanned by the previous extracted features. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Li, Guoqi Wen, Changyun Wei, Wei Xu, Yi Ding, Jie Zhao, Guangshe Shi, Luping |
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Article |
| author |
Li, Guoqi Wen, Changyun Wei, Wei Xu, Yi Ding, Jie Zhao, Guangshe Shi, Luping |
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Li, Guoqi |
| title |
Trace ratio criterion for feature extraction in classification |
| title_short |
Trace ratio criterion for feature extraction in classification |
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Trace ratio criterion for feature extraction in classification |
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Trace ratio criterion for feature extraction in classification |
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Trace ratio criterion for feature extraction in classification |
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trace ratio criterion for feature extraction in classification |
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2014 |
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https://hdl.handle.net/10356/79907 http://hdl.handle.net/10220/20016 |
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