GA Based Polynomial Neural Network for Data Classification

Polynomial Neural Network is a self-organizing network whose performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, a training algorithm for Polynomial Neural Network (PNN) based on Genetic Algorithm (GA) has been proposed for classification problems. A performance comparison of the proposed PNN-GA and Back Propagation based PNN (PNN-BP) has also been carried out by considering four popular datasets obtained from UCI machine learning repository. Experimental results show that the proposed PNN-GA outperforms PNN-BP for all the four datasets and thus may be applied as classification model in many real world problems.