The balance property in neural network modelling

Abstract

In estimation and prediction theory, considerable attention is paid to the question of having unbiased estimators on a global population level. Recent developments in neural network modelling have mainly focused on accuracy on a granular sample level, and the question of unbiasedness on the population level has almost completely been neglected by that community. We discuss this question within neural network regression models, and we provide methods of receiving unbiased estimators for these models on the global population level.