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.