Neural Networks and Related Methods for Classification

Abstract

SUMMARY Feed-forward neural networks are now widely used in classification problems, whereas non-linear methods of discrimination developed in the statistical field are much less widely known. A general framework for classification is set up within which methods from statistics, neural networks, pattern recognition and machine learning can be compared. Neural networks emerge as one of a class of flexible non-linear regression methods which can be used to classify via regression. Many interesting issues remain, including parameter estimation, the assessment of the classifiers and in algorithm development.