A reformative kernel Fisher discriminant analysis |
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Authors: | Yong Xu [Author Vitae] Jing-yu Yang [Author Vitae]Author Vitae] |
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Affiliation: | Department of Computer Science, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, People's Republic of China |
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Abstract: | A reformative kernel Fisher discriminant method is proposed, which is directly derived from the naive kernel Fisher discriminant analysis with superiority in classification efficiency. In the novel method only a part of training patterns, called “significant nodes”, are necessary to be adopted in classifying one test pattern. A recursive algorithm for selecting “significant nodes”, which is the key of the novel method, is presented in detail. The experiment on benchmarks shows that the novel method is effective and much efficient in classifying. |
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Keywords: | Fisher discriminant analysis Kernel trick Pattern recognition |
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