From the tutorial, I see that the network is created by defining a function for each random variable where the function outputs the conditional probability given its parents (the parent assignments are arguments to the function). At first glance, this does not seem to allow for one to create a Bayesian network dynamically (say, based on an input file). Is there a good way to dynamically create a Bayesian network?
From the tutorial, I see that the network is created by defining a function for each random variable where the function outputs the conditional probability given its parents (the parent assignments are arguments to the function). At first glance, this does not seem to allow for one to create a Bayesian network dynamically (say, based on an input file). Is there a good way to dynamically create a Bayesian network?