Neural networks as an optimization tool for regression

Abstract

Neural networks are a tool to solve prediction problems that have gained much prominence recently. In general, neural networks are used as a predictive method, that is, their are used to estimate a regression function. Instead, this work presents the use of neural networks as an optimization tool to combine existing regression estimators in order to obtain more accurate predictions and to fit local linear models more efficiently. Several tests were conducted to show the greater efficiency of these methods when compared to the usual ones.