Support vector machine is a new learning method based on VC theory, good generalization is required by minimizing the upper abound of expected risk.

支持向量机是一种基于VC理论的创造性学习方法，它能够使期望风险最小化，具有较强的推广能力。

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By the time of middle and late 1990s, a large amount of materials on VC theory and practice were introduced into China, which greatly pushed the development of this industry.

到了九十年代中后期，介绍创业投资制度理论和实践的书刊资料被大量的传播到中国。

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Support Vector Machine (SVM) is a kind of learning machines constructed according to SRM principle on the basis of VC theory, which is much more powerful man the neural networks.

支撑矢量机（SVM）是在VC理论的基础上根据结构风险最小归纳原理建立的一种比神经网络更强有力的学习机。

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