Bayesian Network

Bayesian networks are useful for modeling complex variable relationships in an explicit and interpretable way. Each node represents a variable, while edges encode conditional dependencies. This structure is well suited for causal intuition, decision support, and inference under uncertainty. When combined with expert knowledge, it offers a powerful framework for knowledge representation and probabilistic reasoning.