支持向量机 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-Support vector machine Support vector machine is Jianli statistical learning theory of VC dimension theory and structural risk minim

关于支持向量机的算法 支持向量机在解决小样本、非线性及高维模式识别中表现出许多特有的优势，并能够推广应用到函数拟合等其他机器学习问题中-On support vector machine support vector machine algorithm to solve small sample, nonlinear and high dimensional pattern recognition showed the advantage of many special, and can be

支持向量机软件的使用说明，从外国网站下，下载的，希望对模式识别研究的学生有帮助啊-Support vector machine software instructions from a foreign website, the download and hope for pattern recognition research students to help ah

支持向量机的各种论文，需要在万方维普上花钱下载的文献，描述各种SVM的识别方法的数学过程，没有编程语言。-Various papers that support vector machines, you need to spend money in the Articles Weipu download literature to describe the various SVM identification of the mathematical process, there is no pr