The estimation of error bounds and feature selection in large character set recognition

Abstract

Based on the reduction of entropy, the analysis of the estimation of error bounds is discussed. This estimation is simple in computation and is associated with a scatter matrix of classes. For the case of a large character set, a novel definition of separability of classes is proposed. It is simple in computation and can be used to evaluate error bounds and to choose a subset of features with minimum loss of information.<>