A linear transform that simplifies and improves neural-network classifiers

Abstract

This paper presents a linear transform that compresses data in a manner designed to improve the performance of a binary classifier. The transform, which is called the eigenspace separation transform, allows the reduction of the size of a neural network while enhancing its generalization accuracy as a binary classifier.