Fast Learning Rates for Plug-In Classifiers
Fast Learning Rates for Plug-In Classifiers
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Hayward, CA: Institute of Mathematical Statistics
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English
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Hayward, CA: Institute of Mathematical Statistics
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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 plug-in cl...
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Fast Learning Rates for Plug-In Classifiers
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TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1183667286
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1183667286
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ISSN
0090-5364
E-ISSN
2168-8966
DOI
10.1214/009053606000001217
