Fuzzy Support Vector Classification Based on Possibility Theory
YANG ZhiMin1, DENG NaiYang2
1.Department of Science, Zhijiang College of Zhejiang University of Technology, Hangzhou 310024 2.College of Science, China Agriculture University, Beijing 100083
Abstract:The fuzzy support vector classification is discussed, in which both the output of the training point and the value of the final fuzzy classification function are triangle fuzzy number. First, the fuzzy classification problem is formulated as a fuzzy chance constrained programming. Then, this programming is transformed into its equivalence quadratic programming. As a result, fuzzy support vector classification algorithm is proposed. An example is presented to show the rationality of the algorithm.
杨志民,邓乃扬. 基于可能性理论的模糊支持向量分类机*[J]. 模式识别与人工智能, 2007, 20(1): 7-14.
YANG ZhiMin , DENG NaiYang. Fuzzy Support Vector Classification Based on Possibility Theory. , 2007, 20(1): 7-14.
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