Consistency of Derivative Based Functional Classifiers on Sampled Data
Abstract
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.
Origin : Files produced by the author(s)
Loading...