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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.

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Difference between ANN and Bayesian Network

The vertices and edges in Bayesian Network have some sort of meaning. The network building itself gives you important information about the subject dependence between the variables. With Neural Networks the network structure does not tell you anything like Bayesian Network.

Similarity in ANN and Bayesian Network is that they both uses directed graphs.

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