关键词: 支持向量机 , 约简 , 样本

Abstract: When the number of the training set is very large, the training time and needed memory of support vector machine increase quickly. In order to solve the problem, an improved simplifying method was put forward. The samples which may be support vectors mainly distribute on both borders, so a method which fetches border samples better was used to improve simplifying rate, and decrease the number of samples by preserving border samples and deleting non-border samples. The experiment results prove that the simplifying rate and the generalization are almost unchangeable, so the method is feasible.

Key words: Support vector machine , Simplifying , Sample