Multi-category classification by soft-max combination of binary classifiers

被引：0

作者：

Duan, KB ^{[1
]}

Keerthi, SS

Chu, W

Shevade, SK

Poo, AN

机构：

[1] Natl Univ Singapore, Dept Mech Engn, Control Div, Singapore 119260, Singapore

[2] Indian Inst Sci, Dept Comp Sci & Automat, Bangalore 560012, Karnataka, India

来源：

MULTIPLE CLASSIFIER SYSTEMS, PROCEEDING | 2003年 / 2709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：

In this paper, we propose a multi-category classification method that combines binary classifiers through soft-max function. Posteriori probabilities are also obtained. Both, one-versus-all and one-versus-one classifiers can be used in the combination. Empirical comparison shows that the proposed method is competitive with other implementations of, one-versus-all and one-versus-one methods in terms of both classification accuracy and posteriori probability estimate.

引用

页码：125 / 134

页数：10

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