A kernel-based combined classification rule

Majid Mojirsheibani

Statistics & Probability Letters, 2000, vol. 48, issue 4, 411-419

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.

Keywords: Classification; rule; Bayes; classifier; Kernel; Misclassification; error; Shatter; coefficient; Consistency (search for similar items in EconPapers)
Date: 2000
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