A novel fuzzy support vector machine based on the confidence

In this paper, we have focused on a proper fuzzy membership function of the fuzzy support vector machine (FSVM). And we propose a novel fuzzy membership function for fuzzy Supper vector Machines (NFSVM) based on the confidence in the theory of uncertainty. The fuzzy membership function is calculated in the feature space and is represented by kernel function. In addition, a numerical example is used to demonstrate the proposed method and compare with other methods. On the basis of the results, we can conclude that the NFSVM can improve the classification accuracy and reduce the effects of outliers.