首页> 外文会议>International conference on life system modeling and simulation;International conference on intelligent computing for sustainable energy and environment;LSMS 2010;ICSEE 2010 >An Algorithm of Sphere-Structure Support Vector Machine Multi-classification Recognition on the Basis of Weighted Relative Distances
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An Algorithm of Sphere-Structure Support Vector Machine Multi-classification Recognition on the Basis of Weighted Relative Distances

机译:基于加权相对距离的球体结构支持向量机多分类识别算法

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Theories on sphere-structure support vector machine (SVM) and multi-classification recognition algorithms were studied in the first place, and on this basis, in view of the issue of the difference in the hypersphere radiuses resulted from the difference in the quantity of the training samples and the discrepancy in their distributions, the concepts of relative distance and weight were introduced, and subsequently a new algorithm of sphere-structure SVM multi-classification recognition was proposed on the basis of weighted relative distances. Accordingly, the data from the UCI database were used to conduct simulation experiments, and the results verified the validity of the algorithm propose.
机译:首先研究了球结构支持向量机(SVM)和多分类识别算法的理论,并在此基础上,考虑了由于球体数量的差异而引起的超球半径差异的问题。介绍了训练样本及其分布的差异,提出了相对距离和权重的概念,然后在加权相对距离的基础上提出了一种球体结构支持向量机多分类识别的新算法。据此,利用UCI数据库中的数据进行了仿真实验,结果验证了所提算法的有效性。

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