Bayesian Optimization

Bayesian Networks are probabilistic graphical models that utilize directed acyclic graphs to illustrate how variables are interconnected through conditional dependencies. They encode uncertainty and facilitate reasoning under uncertainty by representing joint probability distributions. These networks are widely used in decision analysis, diagnostics, and machine learning to make predictions, infer missing data, and understand complex relationships among variables.