Wavelet-Based Estimation of a Discriminant Function
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In this paper we consider wavelet-based binary linear classifiers. Both consistency results and implementational issues are addressed. We show that under mild assumptions on the design density wavelet discrimination rules are L₂-consistent. The proposed method is illustrated on synthetic data sets in which the "truth" is known and on an applied discrimination problem from the industrial field.