Consistency of Derivative Based Functional Classifiers on Sampled Data
Résumé
In some applications, especially spectrometric ones, curve classifiers achieve better performances if they work on the $m$-order derivatives of their inputs. This paper proposes a smoothing spline based approach that give a strong theoretical background to this common practice.
Origine | Fichiers produits par l'(les) auteur(s) |
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