This article is cited in 1 paper

Nonparametric estimation of Bayesian classifier elements

M. P. Krivenko

Institute for Problems of Informatics RAS

Abstract: The problemof constructing an empirical Bayesian classifier, providing recognition of the text, where some symbols have different picture sizes, is considered. A combined method of constructing an evaluation of Bayesian classifier is proposed. The method includes nonparametric kernel estimation and parametric estimation with the help of the density of normal distribution. This combined assessment allows to deal effectively with the task of handling small amounts of training set. Productivity of the proposed ideas is illustrated by an example of recognizing the real text.

Keywords: Bayesian classifier; combined multivariate density estimation; adaptive kernel estimation; text recognition.