Abstract
In the problem of classification (or pattern recognition), given a set of n samples, we attempt to construct a classifier g n with a small misclassification error. It is important to study the convergence rates of the misclassification error as n tends to infinity. It is known that such a rate can't exist for the set of all distributions. In this paper we obtain the optimal convergence rates for a class of distributions \({\fancyscript D}\) (λ,ω) in multicategory classification and nonstandard binary classification.
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Research supported in part by NSF of China under Grants 10571010 and 10171007. The work was partially done while the first author was visiting the Institute for Mathematical Sciences, National University of Singapore in 2003. The visit was supported by the Institute
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Chen, D.R., You, X. Minimax Optimal Rates of Convergence for Multicategory Classifications. Acta Math Sinica 23, 1419–1426 (2007). https://doi.org/10.1007/s10114-005-0880-2
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DOI: https://doi.org/10.1007/s10114-005-0880-2