The problems and defections of the existing methods of SVM multi-class classification were analyzed. A multi-class classification based on binary tree was put forward.

介绍了几种常用的支持向量机多类分类方法，分析其存在的问题及缺点。

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A new method of fault classification for mechanical system by means of support vector machine (SVM) is proposed and a multi-class SVM classifier based on binary classification was developed.

提出了一种利用支持向量机(SVM)对机械系统故障进行分类的新方法；以二值分类为基础，开发了基于支持向量机的多值分类器。

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The presented multi-class SVM is of better classification ability and can solve the unclassifiable region problems int.

新的多类SVM在一定程度上解决了传统投票决策方法的不可分区域问题，因此具有更好的分类性能。

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