Скачать или смотреть Configuring Search Spaces for Tuning

Configuring search spaces is a crucial step in hyperparameter tuning. A search space is essentially a defined range of values for each hyperparameter you wish to optimize. Common search methods include grid search and random search. Grid search exhaustively searches through a specified subset of hyperparameter space, whereas random search selects random combinations of hyperparameters to evaluate. Each method has its advantages—grid search is more thorough, while random search can be more efficient. Consider the computational cost and model complexity when choosing your search method. Balancing these factors will help you set up efficient and effective search spaces.