A COMPARISON OF THE PREDICTIVE CAPABILITIES OF ARTIFICIAL NEURAL NETWORKS AND REGRESSION MODELS FOR KNOWLEDGE DISCOVERY

Abstract

In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to determine which ofthem performs better. Prediction was done using one hidden layer and three processing elements in the ANN model.Furthermore, prediction was done using regression analysis. The parameters of regression model were estimated using LeastSquare method. To determine the better prediction, mean square errors (MSE) attached to ANN and regression models wereused. Seven real series were fitted and predicted with in both models. It was found out that the mean square error attached toANN model was smaller than regression model which made ANN a better model in prediction.

Keywords: Artificial Neural Networks, Regression, Least Square, Processing Element, Hidden Layer, Mean Square Error.