Grid search involves specifying a range of values for each parameter of interest. The method then exhaustively evaluates all possible combinations of these parameters to find the optimal set. For example, in a regression model predicting the spread of an infectious disease, parameters like the learning rate, regularization strength, and number of iterations might be tuned using grid search. The process can be computationally intensive, but it ensures that the most effective parameter configuration is identified.
