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Multi-classification with Tri-class Support Vector Machines. A Review

机译:使用三类支持向量机进行多分类。回顾

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摘要

In this article, with the aim to avoid the loss of information that occurs in the usual one-versus-one SVM decomposition procedure of the two-phases (decomposition, reconstruction) multi-classification scheme tri-class SVM approach is addressed. As the most relevant result, it will be demonstrated the robustness improvement of the proposed scheme based on tri-class machine versus that based on the bi-class machine.
机译:在本文中,为了避免在两阶段(分解,重建)多分类方案三类SVM方法的通常的一对一SVM分解过程中发生信息丢失。作为最相关的结果,将证明所提出的基于三类机器的方案相对于基于双类机器的方案的鲁棒性改进。

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