关键词: 线性规划, 模糊支持向量机, 隶属度

Abstract: As the traditional Support Vector Machines（SVM） is sensitive to the noises or outliers，Fuzzy Support Vector Machines is introduced，but the determination of fuzzy membership is a difficulty.One-class classification algorithm based on linear programming is used to determine fuzzy membership in this paper，then the corresponding membership is given according to different input data affects on the classification results.So this method effectively distinguishes between the noises or outliers and the valid samples.Experimental results indicate that Fuzzy Support Vector Machines yields better classification result than the traditional SVM，thus the effects of the noise or outliers can be diminished.

Key words: linear programming, Fuzzy Support Vector Machines（FSVM）, membership