Which of the following statements about GridSearchCV is/are True?1 pointGridSearchCV scans over a dictionary of parameters.GridSearchCV finds the hyperparameter set that has the best out-of-sample score.GridSearchCV retrains on all data with the "best" hyper-parameters.All of the above are True.

Which of the following statements about cross-validation is/are True?1 pointCross-validation is essential step in hyperparameter tuning.We can manually generate folds by using KFold function.GridSearchCV is commontly used in cross-validation.All of the above are True.

What is the primary purpose of the GridSearchCV() method?1 pointTo split your data into folds, then iterate over the folds to train and test your model.To determine the appropriate order of a model.To help select appropriate hyperparameter values.To determine if you’ve underfit or overfit your data.

Write a function that returns the best hyperperameters for a given model (i.e. the GridSearchCV).Function specifications:Should take in an sklearn GridSearchCV object.Should return a dictionary of optimal parameters for the given model.

Every hyperparameter if set poorly,can have a huge impact on training and so all hyperparameters are about equally important to tune well.Review LaterTrueFalse

Question 6Which of the following statements about datasets used in Machine Learning is NOT true?1 pointTesting data is data the model has never seen before and is used to evaluate how good the model isTraining subset is the data used to train the algorithm Training data is used to fine-tune algorithm’s parameters and evaluate how good the model isValidation data subset is used to validate results and fine-tune the algorithm's parameters