On the consistency of multiclass classification methods
Data(s) |
01/05/2007
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Resumo |
Binary classification is a well studied special case of the classification problem. Statistical properties of binary classifiers, such as consistency, have been investigated in a variety of settings. Binary classification methods can be generalized in many ways to handle multiple classes. It turns out that one can lose consistency in generalizing a binary classification method to deal with multiple classes. We study a rich family of multiclass methods and provide a necessary and sufficient condition for their consistency. We illustrate our approach by applying it to some multiclass methods proposed in the literature. |
Identificador | |
Publicador |
Journal of Machine Learning Research |
Relação |
http://www.jmlr.org/papers/volume8/tewari07a/tewari07a.pdf Tewari, Ambuj & Bartlett, Peter L. (2007) On the consistency of multiclass classification methods. Journal of Machine Learning Research, 8, pp. 1007-1025. |
Direitos |
Copyright 2007 Journal of Machine Learning Research |
Fonte |
Faculty of Science and Technology; Mathematical Sciences |
Palavras-Chave | #080100 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING #170200 COGNITIVE SCIENCE #multiclass classification #consistency #Bayes risk #OAVJ |
Tipo |
Journal Article |