Intuitionistic Fuzzy Support Vector Machine

As the extending of Support vector machine, fuzzy support vector machine (FSVM) can effectively solve the classification of points which include the noise points or isolated points that can make the support vector machine (SVM) classify error, but fuzzy support vector machine weakened support vector's contribution for classification hyperplane while it reduce the noise points influence. In view of the above situation, base on intuitionistic fuzzy sets and the fuzzy support vector machine, this paper proposed the intuitionistic fuzzy support vector machine (IFSVM) and extend to the muticlassification. This algorithm intuitionistic fuzzy the training sample , make sure the membership and the intuitionistic index of the training sample, and then using support vector machines classify the samples. Experiments show that, the intuitionistic fuzzy support vector machine enhance classification accuracy further than the fuzzy support vector machine.