difference between artificial neural network and Bayesian network

Question

Hello, I am a student working on an internship project where in we are using Bayesian networks to predict a possible outcome from a given set of discrete parent variables.We now intend to use artificial neural network to do the task.So could any one please help me out with the similarities and differences between Bayesian networks and artificial neural network?Any suggestions as how to proceed with migration would be helpful.

Thanks

Answer 1

Similarity

• Both use directed graphs.

Difference

• In Bayesian networks the vertices and edges have meaning- The network structure itself gives you valuable information about conditional dependence between the variables. With Neural Networks the network structure does not tell you anything.