Unit 5 Bayesian networks Part 3|GULSHAN|SNS INSTITUTIONS

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Bayesian networks are graphical models used to represent probabilistic relationships between variables. They consist of nodes (representing variables) and directed edges (indicating dependencies). Each node has a probability distribution based on its parent nodes. Bayesian networks are used for reasoning under uncertainty, allowing inferences about unknown variables given observed data. They are widely applied in fields like machine learning, decision analysis, and diagnostic systems.