关键词: 支持向量机, 模糊支持向量机, 正态分布, 概率, 隶属度, π型函数

Abstract: Relative to the defect of fuzzy membership as a function of distance between the point and its class center in feature space for some current fuzzy support vector machines，a new method to calculate the fuzzy membership is proposed.It first utilizes normal distribution based on the probability of membership function π to calculate the ambiguity，due to the normal distribution feature，takes the distribution of the data into consideration to calculate the membership.The outputs can reflect the characteristic of the membership more accurately.Experiments show that compared with SVM and FSVM，this method has a better performance on reducing the effect of outliers and significantly improves the classification accuracy.

Key words: Support Vector Machine（SVM）, Fuzzy Support Vector Machine（FSVM）, normal distribution, probability, membership, function π