Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/60839
Title: Multi-category classification by soft-max combination of binary classifiers
Authors: Duan, K.
Keerthi, S.S. 
Chu, W.
Shevade, S.K.
Poo, A.N. 
Issue Date: 2003
Source: Duan, K.,Keerthi, S.S.,Chu, W.,Shevade, S.K.,Poo, A.N. (2003). Multi-category classification by soft-max combination of binary classifiers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2709 : 125-134. ScholarBank@NUS Repository.
Abstract: 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. © Springer-Verlag Berlin Heidelberg 2003.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/60839
ISSN: 03029743
Appears in Collections:Staff Publications

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