Fast learning rates for plug-in classifiers
Fast learning rates for plug-in classifiers
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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It has been recently shown that, under the margin (or low noise) assumption, there exist classifiers attaining fast rates of convergence of the excess Bayes risk, that is, rates faster than \(n^{-1/2}\). The work on this subject has suggested the following two conjectures: (i) the best achievable fast rate is of the order \(n^{-1}\), and (ii) the p...
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Full title
Fast learning rates for plug-in classifiers
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TN_cdi_proquest_journals_2088010521
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2088010521
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E-ISSN
2331-8422
DOI
10.48550/arxiv.0708.2321
