(Georgia Institute of Technology, 2002)
Chang, Woojin; Kim, Seong-Hee; Vidakovic, Brani
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.