4. In the supervised learning, what is the purpose of a grid search?(A) To shift the decision boundary or regression line.(B) To split the data into training and testing sets.(C) To select the best features for a model.(D) To prevent overfitting.(E) To search for the best combination of hyperparameters for a given model.

11. Which of the following statements about machine learning is CORRECT? (A) We can generate new features by linearly or non-linearly combining the original features, which is a method of feature engineering. (B) In a dataset, all pairwise combinations of data point vectors are called the support vectors of the dataset. (C) During the training process of a neural network, the validation loss typically fluctuates, but the training loss will always decrease. (D) In k-NN classification, k should be set equal to the size of the dataset so that the entire dataset is considered before making a decision. (E) When training a deep learning model, if the accuracy of the test set is higher than that of the training set, it should be considered evidence of overfitting.

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