Abstract
This article deals with a weighted-type combined classification rule where the combining is based on a data discretization and the “weights” are determined by exponential kernels. The smoothing parameter of the kernel is estimated by a data-splitting approach. Both the mechanics and the asymptotic validity of the proposed procedure are discussed.
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