Compared with the single suppo vector machine method, the support vector machine ensemble method has better classification accuracy.

模拟实验结果表明，该方法具有明显优于单一支持向量机的更高的分类准确率。

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This paper proposed a selective Support Vector Machine (SVM) ensemble algorithm based on double disturbance to improve the generalization ability of SVM.

为了进一步提升支持向量机泛化性能，提出一种基于双重扰动的选择性支持向量机集成算法。

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