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Support Vector Machine with the Fuzzy Hybrid Kernel for Protein Subcellular Localization Classification

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5 Author(s)
Jin, B. ; Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA ; Yuchun Tang ; Yan-Qing Zhang ; Chung-Dar Lu
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In the paper, we present a fuzzy hybrid kernel that combines several conventional kernels by using the TSK model. The major technical merit is to make a more reliable kernel fusing different kernels. Support vector machine (SVM) with the fuzzy hybrid kernel is employed for protein subcellular localization classification. Experimental results indicate that SVM with the new fuzzy hybrid kernel is better than those with conventional kernels

Published in:

Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on

Date of Conference:

25-25 May 2005