An Evolutionary Computational Approach to Probabilistic Neural Network with Application to Hepatic Cancer Diagnosis
Florin Gorunescu, Marina Gorunescu, Elia El‐Darzi, S. Gorunescu · 2005
The performance of a probabilistic neural network is strongly influenced by the smoothing parameter. This paper introduces an evolutionary approach based on genetic algorithm to optimise the search of the smoothing parameter in a modified probabilistic neural network. A Java implementation is introduced and the computational results showed the viability of this hybrid approach to determine the optimum diagnosis for hepatic diseases.