20 min read

Bayesian Optimization for Hyperparameter Tuning

There are many issues with grid search and random search. * They are computationally expensive due to exhaustive search. * The search is restricted to the specified hyperparameter range. But what if the ideal hyperparameter exists outside that range? * They can ONLY perform discrete searches, even if the hyperparameter is continuous. Bayesian