本书介绍的支持向量机方法，是建立在统计学习理论的VC 维理论和结构风险最小原理基础上的，根据有限的样本信息在模型的复杂性（即对特定训练样本的学习精度）和学习能力（即无错误地识别任意样本的能力）之间寻求最佳折衷，以期获得最好的推广能力 。-This book introduces the support vector machine method is based on statistical learning theory, VC dimension and structural risk minimization theory based on the principle, according to the limited sample of information in the complexity of the model (ie, training samples of a specific learning accuracy) and learning capacity (ie, error-free samples to identify any capacity) to find the best compromise between, in order to obtain the best generalization ability.