Bayesian Network that Learns Conditional Probabilities by Neural Networks

摘要

In this paper, we discuss a Bayesian network that learns conditional probabilities by neural networks (BNNN). The real world domain is filled with many kinds of variables, which often have uncertainty factors. For the reasoning about such variables, we propose a Bayesian network using feed forward neural networks.