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一种基于FCOWA-ER的SVM多分类方法

DOI: 10.13195/j.kzyjc.2014.1215, PP. 1773-1778

Keywords: 支持向量机,DS证据理论,多属性决策

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Abstract:

支持向量机(SVM)在处理多分类问题时,需要综合利用多个二分类SVM,以获得多分类判决结果.传统多分类拓展方法使用的是SVM的硬输出,在一定程度上造成了信息的丢失.为了更加充分地利用信息,提出一种基于证据推理-多属性决策方法的SVM多分类算法,将多分类问题视为一个多属性决策问题,使用证据推理-模糊谨慎有序加权平均方法(FCOWA-ER)实现SVM的多分类判决.实验结果表明,所提出方法可以获得更高的分类精度.

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