Bayesian risk

Bayesian risk is a way to evaluate how well a decision-making process performs by considering the likelihood of different outcomes and their potential costs or errors. It uses existing information (prior knowledge) and updates it with new data (Bayes' theorem) to estimate the expected “cost” or “risk” associated with each choice. The goal is to select the decision that minimizes this expected risk, leading to more informed and optimal outcomes. Essentially, Bayesian risk helps balance uncertainty and consequences to guide better decisions in uncertain situations.