Description
Probabilistic graphical models can be built and analyzed for research, inference, and machine-learning experiments. Data scientists use pgmpy for Bayesian networks, factor graphs, parameter estimation, and causal-model prototypes. Results depend on assumptions, training data, and validation against the domain.