An Efficient Algorithm for Multi-class Support Vector Machines
An Efficient Algorithm for Multi-class Support Vector Machines
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DOI：
10.1109/icacte.2008.48
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发表时间：
2008-12
期刊：
影响因子：
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通讯作者：
Jun Guo;Norikazu Takahashi;Wenxin Hu
中科院分区：
文献类型：
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作者：
Jun Guo;Norikazu Takahashi;Wenxin Hu
提出了一种新的多类支持向量机算法。在我们的算法中构造的树由一系列的两类SVM。在每次迭代中，根据两类之间的距离和每类中模式的数目，将多类模式分为两个集合，同时考虑了模式的可分性和平衡性。该算法可以很好地处理非均匀分布的问题。实验结果验证了该方法的有效性。
A novel algorithm for multi-class support vector machines (SVMs) is proposed in this paper. The tree constructed in our algorithm consists of a series of two-class SVMs. Considering both separability and balance, in each iteration multi-class patterns are divided into two sets according to the distances between pairwise classes and the number of patterns in each class. This algorithm can well treat with the unequally distributed problems. The efficiency of the proposed method are verified by the experimental results.