learnDBN is Java implementation of a Dynamic Bayesian Network (DBN) structure learning algorithm. It can learn tDBN, cDBN and bcDBN structures from a file with multivariate longitudinal observations. Also, it improves these algorithms by allowing the data to have missing values. As such this implementation can impute missing values. Moreover, it has the capability of learning a Dynamic Bayesian Multinet (DBM) which is an extension of a Bayesian Multinet. By using the DBM model this implementation has the capability of performing clustering on the data.
For further details, please refer to the project website: https://ssamdav.github.io/learnDBM/