A neural network approach to a Bayesian statistical decision problem

1 January 1991

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Neural Networks

Vol. 2 (5) , 538-540
https://doi.org/10.1109/72.134293

Abstract

Generalized mean-squared error (GMSE) objective functions are proposed that can be used in neural networks to yield a Bayes optimal solution to a statistical decision problem characterized by a generic loss function.

Keywords

NEURAL NETWORK
DECISION PROBLEM
STATISTICAL DECISION
BAYESIAN STATISTICAL
MEAN SQUARED ERROR
PROBLEM CHARACTERIZED
BAYES OPTIMAL
GENERIC LOSS

This publication has 3 references indexed in Scilit:

Bayes statistical behavior and valid generalization of pattern classifying neural networks
IEEE Transactions on Neural Networks, 1991
The multilayer perceptron as an approximation to a Bayes optimal discriminant function
IEEE Transactions on Neural Networks, 1990
Neural network classification: a Bayesian interpretation
IEEE Transactions on Neural Networks, 1990