Support Vector Machine (SVM) was first proposed in 1995 by Cortes and Vapnik [15] for solving classification and regression problems. The solving strategy of SVM on the multiple classification problems is commonly “one to one” strategy, whose basic thought is that the classification problems with N categories will be decomposed into ()1/2 NN− binary classification problems to deal with, and meantime, ()1/2 NN− training classifiers needed to be trained. In the training process, any two categories of all the N categories would be selected as one group. Assume that we have five categories, and these categories are labeled ,,, , ABC DE. Figure 3 shows the () 551/2 ×− classifiers according to “one to one” tragedy.

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