Neural network classification: a Bayesian interpretation
Eric A. Wan · IEEE Transactions on Neural Networks · 1990
The relationship between minimizing a mean squared error and finding the optimal Bayesian classifier is reviewed. This provides a theoretical interpretation for the process by which neural networks are used in classification. A number of confidence measures are proposed to evaluate the performance of the neural network classifier within a statistical framework.