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This Note proposes a new methodology for function classification with SupportVector Machine (SVM). Rather than relying on projection on a truncated Hilbertbasis as in our previous work, we use an implicit spline interpolation thatallows us to compute SVM on the derivatives of the studied functions. To thatend, we propose a kernel defined directly on the discretizations of theobserved functions. We show that this method is universally consistent.

Un r\'esultat de consistance pour des SVM fonctionnels par interpolation spline