Support vector machine (SVM) is a new general learning machine, which analyzes the consistency of learning and speed of convergence from structure risk minimization principle.

支持向量机(SVM)是一种新的通用学习机器，它从结构风险最小化的角度，分析了学习过程的一致性、收敛速度等。

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Compared with multivariate statistics and artificial neural networks, support vector machine based on structure risk minimization has better classification performance.

与统计分析和神经网络相比，基于结构风险最小的支持向量机有更好的分类性能。

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Compared with multivariate statistics and artificial neural networks, support vector machine based on structure risk minimization has better classification performance.

与统计分析和神经网络相比，基于结构风险最小的支持向量机有更好的分类性能。

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