Technical GlossaryMachine Learning

Bayesian Optimization

A sample-efficient optimization method that intelligently selects new hyperparameter candidates by learning from past trials.

Bayesian optimization turns hyperparameter tuning from blind trial-and-error into an informed decision process. It builds a probabilistic model over past trials and uses it to choose the next candidates intelligently. This is especially valuable when model evaluations are expensive. Its ability to reach promising regions with fewer trials makes it a powerful tool in modern AutoML and model-optimization workflows.