In this paper, the authors concern with the fuzzy support vector classification, in which both of the type of the output training point and the value of the final fuzzy classification function are triangle fuzzy number. The fuzzy classification problem is formulated as a fuzzy chance constrained programming. Then, they transform this programming into its equivalence quadratic programming. Final, a fuzzy support vector classification algorithm is proposed to deal with the problem. An example is presented to illustrate rationality of the algorithm.