Support Vector machine is one of the hot points in machine learning research, it's theoretical basis is Statistical learning Theory.

支持向量机是机器学习领域的研究热点之一，其理论基础是统计学习理论。

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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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For this reason, several important properties of kernel function are discussed on the basis of support vector machine.

为此，在研究支持向量机的基础上，给出了核函数的若干重要性质。

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