Suppose that for some linear regression problem (say, predicting life expectancy given cigarettes smoked per day as in the lecture), we have some training set, and for our training set we managed to find some 0,1 such that J(0,1)=0. Which of the statements below must then be true? (Select all that apply.). a) This is not possible: By the definition of J(0,1), it is not possible for there to exist 0 and 1 so that J(0,1)=0; b) Our training set can be fit perfectly by a straight line, i.e., all of our training examples lie perfectly on some straight line c) We can perfectly predict the value of y even for new examples that we have not yet seen. (e.g., we can perfectly predict prices of even new houses that we have not yet seen.) d) Gradient descent is likely to get stuck at a local minimum and fail to find the global minimum