Grid Search, Hyperparameter Tuning, Machine Learning, Data Science, Fine Tuning.
where each combination of hyperparameters forms a point in the grid. The model is then trained and evaluated using each combination of hyperparameters, and the one that achieves the highest performance metric, such as accuracy, precision, or F1-score, is selected as the optimal configuration.