How do I use parameter grids in scikit-learn?

How do I use parameter grids in scikit-learn?

You can use the GridSearchCV class in scikit-learn to perform hyperparameter tuning with parameter grids.

Can you show me an example of how to set up a parameter grid?

Sure! You can define a parameter grid as a dictionary, like this: param_grid = {'n_neighbors': [3, 5, 7], 'weights': ['uniform', 'distance']}.

How do I apply this parameter grid to a model?

You can pass the parameter grid to GridSearchCV along with your model, like this: grid_search = GridSearchCV(model, param_grid).

What should I do after running GridSearchCV?

After running it, you can access the best parameters with grid_search.best_params_ and the best score with grid_search.best_score_.