Un résultat de consistance pour des SVM fonctionnels par interpolation spline

Mathematics – Statistics Theory

Scientific paper

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6 pages

Scientific paper

10.1016/j.crma.2006.09.025

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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