Work out grid search combinations instantly with clear inputs, formula shown and shareable results.
A grid search evaluates the full cross product of the parameter values, and cross-validation multiplies each combination by the fold count. Sixty combinations with five folds is 300 model fits, which is why the total fit count — not the combination count — is the number to check against your compute budget before starting.
Grid search cost
combinations = product of values per parameter; fits = combinations x folds
Yes, most implementations refit the best configuration on all the data at the end, so add one to the total.
Halving strategies such as successive halving and HyperBand allocate few resources to most candidates and only train the promising ones fully, often cutting total cost by an order of magnitude.