Absrtact: SVM represented many unique advantages in many applications, such as solving the problem of nonlinear, high dimension pattern recognition and small sample problem.
摘要：在解决非线性、高维模式识别以及小样本等问题中，支持向量机表现出许多独有的优势。
SVM solves the small sample problem mainly and finds the best compromise between the complexity of the model and the learning ability in order to obtaining the best generalization ability.
SVM主要解决小样本问题，在模型的复杂度和学习能力之间寻求最佳折衷，目的在于获得最好的泛化能力。
During analyzing and estimating the risk, we often meet with the situation of inadequate sample information and incomplete data, that is, small-sample problem.
在进行风险分析和评估过程中，经常遇到样本信息不充分，数据不完备，即小样本问题。
应用推荐