Implementing Grid Search with scikit-learn #ai #artificialintelligence #machinelearning #aiagent

@genaiexp Scikit-learn, a powerful Python library for machine learning, offers the GridSearchCV class to facilitate hyperparameter tuning. To implement Grid Search, first, import the necessary modules from scikit-learn. Then, set up the parameter grid as a dictionary where keys are hyperparameter names and values are lists of settings to try. Next, initialize the GridSearchCV class with your model, parameter grid, and desired cross-validation settings. Execute the grid search by fitting the model on your data. Once complete, you can access the best parameters and score using the .best_params_ and .best_score_ attributes. This process allows you to systematically find the best hyperparameters for your model.