Probability estimates for multi-class classification by pairwise coupling

被引：0

作者：

Wu, TF ^{[1
]}

Lin, CJ ^{[1
]}

Weng, RC ^{[1
]}

机构：

[1] Natl Taiwan Univ, Dept Comp Sci, Taipei 106, Taiwan

来源：

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 16 | 2004年 / 16卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Pairwise coupling is a popular multi-class classification method that combines together all pairwise comparisons for each pair of classes. This paper presents two approaches for obtaining class probabilities. Both methods can be reduced to linear systems and are easy to implement. We show conceptually and experimentally that the proposed approaches are more stable than two existing popular methods: voting and [3].

引用

页码：529 / 536

页数：8

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