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Un résultat de consistance pour des SVM fonctionnels par interpolation spline

Abstract : This Note proposes a new methodology for function classification with Support Vector Machine (SVM). Rather than relying on projection on a truncated Hilbert basis as in our previous work, we use an implicit spline interpolation that allows us to compute SVM on the derivatives of the studied functions. To that end, we propose a kernel defined directly on the discretizations of the observed functions. We show that this method is universally consistent.
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https://hal.archives-ouvertes.fr/hal-00144142
Contributor : Nathalie Vialaneix <>
Submitted on : Tuesday, May 1, 2007 - 4:53:42 PM
Last modification on : Friday, May 25, 2018 - 12:02:04 PM
Long-term archiving on: : Wednesday, April 7, 2010 - 2:11:49 AM

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Nathalie Villa, Fabrice Rossi. Un résultat de consistance pour des SVM fonctionnels par interpolation spline. Comptes rendus de l'Académie des sciences. Série I, Mathématique, Elsevier, 2006, 343 (8), pp.555-560. ⟨10.1016/j.crma.2006.09.025⟩. ⟨hal-00144142⟩

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