Two cases of learning Bayesian network from observable variables

In terms of differences the structure of the network and the variables, the process of learning Bayesian networks takes different forms. The variables can be observable or hidden in all or some of the data points, and the structure of the network can be known or unknown. Consequently, there are four cases of learning Bayesian networks from data: known structure and observable variables, unknown structure and observable variables, known structure and unobservable variables and unknown structure and unobservable variables. In this paper, we focus on known structure and observable variables, unknown structure and observable variables.