Once the network structure is learned, you can choose how to learn the probability tables selecting a class in the weka.classifiers.bayes.net.estimate package.
The SimpleEstimator class produces direct estimates of the conditional probabilities,
With the BMAEstimator, we get estimates for the conditional probability tables based on Bayes model averaging of all network structures that are substructures of the network structure learned . This is achieved by estimating the conditional probability table of a node given its parents as a weighted average of all conditional probability tables of given subsets of . The weight of a distribution with used is proportional to the contribution of network structure to either the BDe metric or K2 metric depending on the setting of the useK2Prior option (false and true respectively).