A Kernel Clustering Algorithm for Fast Training of Support Vector Machines |
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| Authors: | LIU Xiao-zhang FENG Guo-can School of Electronics Information Heyuan Polytechnic Heyuan China Faculty of Mathematics Computing Sun Yat-sen University Guangzhou China |
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| Institution: | LIU Xiao-zhang 1,2,FENG Guo-can 2 1 School of Electronics and Information,Heyuan Polytechnic,Heyuan 517000,China 2 Faculty of Mathematics and Computing,Sun Yat-sen University,Guangzhou 510275,China |
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| Abstract: | A new algorithm named kernel bisecting k-means and sample removal(KBK-SR) is proposed as sampling preprocessing for support vector machine(SVM) training to improve the efficiency.The proposed algorithm tends to quickly produce balanced clusters of similar sizes in the kernel feature space,which makes it efficient and effective for reducing training samples.Theoretical analysis and experimental results on three UCI real data benchmarks both show that,with very short sampling time,the proposed algorithm drama... |
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| Keywords: | support vector machines(SVMs) sample reduction topdown hierarchical clustering kernel bisecting k-means |
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