What is Bayesian evaluation of machine learning models?

Bayesian evaluation quantifies uncertainty in model performance using probability distributions.

Instead of point estimates of metrics, Bayesian evaluation treats metrics as random variables with posterior distributions. This allows credible intervals for accuracy, AUC, or loss. It is especially useful for small datasets or high-variance evaluation settings. Bayesian methods incorporate prior beliefs and update them with observed data.