Le reti neurali in problemi di classificazione: una soluzione basata sui metodi di segmentazione binaria

Abstract

In this paper the use of neural networks in the solution of a classification problem is described and a non parametric classifier which combines radial basis function networks (RBF networks) and binary classification trees is proposed. It is shown that from a classification tree a class of RBF networks can be derived, whose elements differ in the degree of dependence from the discriminant rules described by the tree. A simulation study based on a two-class problem shows that the proposal represents a valid solution, particularly in presence of noisy variables.