SVM solves practical problems such as small samples, nonlinearity, over learning, high dimension and local minima, which exist in most of learning methods, and has high generalization.

• 它较好地解决了以往困扰很多学习方法的小样本、非线性、过学习、高维数、局部极小点等实际问题,具有很强的推广能力。