Influence of the Number of the Features with the Neural Network Function

Abstract

This contribution is devoted to the evaluation of probability of success for classification and recognition techniques. It also depends on a proper selection of input elements-features and their number. Error probability is proportional indirectly on a quantity and quality of information provided to a classifier. It can be affected either by a learning algorithm itself and classification or by an element number on classification correctuers has been verified for Kohonen's map designed for a recognition of Czech digits.