Abstract
The aim of this chapter is to derive global learning rates for localized SVMs. In Section 4.1 we begin with a motivation of the statistical analysis from Section 4.2, in which we establish finite sample bounds and derive local learning rates. In Section 4.3, we present the main results and compare the obtained rates in Section 4.4.
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© 2020 Springer Fachmedien Wiesbaden GmbH, part of Springer Nature
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Blaschzyk, I.K. (2020). Localized SVMs: Oracle Inequalities and Learning Rates. In: Improved Classification Rates for Localized Algorithms under Margin Conditions. Springer Spektrum, Wiesbaden. https://doi.org/10.1007/978-3-658-29591-2_4
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DOI: https://doi.org/10.1007/978-3-658-29591-2_4
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Publisher Name: Springer Spektrum, Wiesbaden
Print ISBN: 978-3-658-29590-5
Online ISBN: 978-3-658-29591-2
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