Also known as: Hyperparameter Optimisation
Hyperparameter optimization is the process of selecting hyperparameter values that improve a learning algorithm’s performance. It may involve manual search, grid search, random search, Bayesian optimization, or other tuning methods.
The process of choosing a set of optimal hyperparameters for a learning algorithm.