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On the consistency of multiclass classification methods

Tewari, Ambuj & Bartlett, Peter L. (2005) On the consistency of multiclass classification methods. Lecture Notes in Computer Science, 3559, pp. 143-157.

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Abstract

Binary classification methods can be generalized in many ways to handle multiple classes. It turns out that not all generalizations preserve the nice property of Bayes consistency. We provide a necessary and sufficient condition for consistency which applies to a large class of multiclass classification methods. The approach is illustrated by applying it to some multiclass methods proposed in the literature.

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ID Code: 43968
Item Type: Journal Article
Additional Information: Learning Theory: 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005. Proceedings
DOI: 10.1007/11503415_10
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Mathematical Sciences
Copyright Owner: Copyright 2005 Springer
Deposited On: 18 Aug 2011 08:06
Last Modified: 20 Aug 2013 14:33

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