Based on fuzzy support vector machine(FSVM)

we presented a rough margin based fuzzy support vector machine(RFSVM)by introducing the effects of positions of training samples in the margin on decision hyper-plane in this paper.After computing the degree of fuzzy membership of each training point

we used these data for training to obtain the decision hyper-plane by maximizing rough margin's method.In this algorithm

points in the lower margin have major penalty than those in the boundary.We compared RFSVM with other support vector machine algorithms on several benchmark datasets.Experimental results show that RFSVM is effective and feasible.