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AI & Machine Learning · Advanced

Bayesian Optimization

Hyperparameter tuning that builds a probabilistic model of performance to choose the most promising next trial.

Definition

Bayesian optimization uses past trial results, often with a Gaussian process or tree-structured estimator, to balance exploring new regions against exploiting known good ones. It typically reaches good configurations in fewer trials, but trials are more sequential.

Exam tip

Choose Bayesian optimization when each training run is expensive.

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