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Data mining is a new filed in data processing research. Support vector machine (SVM) is one of the new methods using in data mining, which has gained great applicable success. However, there are stiff plenty of limitations in SVM. For example, SVM won't work if its training set contains fuzzy information. In order to solve the problem presented above, this article discusses the constraining programming...
When the training subset of a support vector machine contains fuzzy information, the support vector machine won't work. A method for calculating fuzzy linear separable support vector classifier is discussed. With the given confidence level, convert the fuzzy classification problem into finding the fuzzy chance constrained programming, and establish a solution finding theory with fuzzy chance constrained...
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