Getting a feel for probabilistic reasoning. Using Bayes networks for diagnostic reasoning, and earning some hands-on experience with JavaBayes Requirements You will define and reason on a network for medical diagnosis.
Pathology is affected by the primal causes.
The symptoms are modeled by noisy-or nodes, each potentially caused by one or more diseases. Make up probabilities such that you will be able to demonstrate all behaviours required below. Now that your model is ready, use JavaBayes to create the network, edit probability tables, and save the network as an XML file. Now, perform reasoning on the network using JavaBayes. Establish values for primal cause nodes and some symptoms, and perform observations - i.e. find the probability of all diseases given the evidence, and state the most likely disease.