3. Assume you have about 10K training examples. Which would you expect to take longer to train: a) a kNN classifier, or b) a logistic regression classifier? 4. (Yes/No) In fitting a logistic regression model, do we seek to minimize mean squared error, as we do with a linear regression model? 5. What would be a reason for using logistic regression rather than kNN for classification? (select all that apply) a. concern over available storage b. concern over the time needed to train c. concern over the time needed to make predictions