Suppose fi is a model that optimally fits the data (x, y), and f is another model that optimally fits the data (X2, y), where X are the quadratic features of X. Then the loss function value obtained by f2 is always going to be at least equal to that for f. Try to come up with a solid mathematical argument that justifies this claim. [Note: as with anything else, feel free to discuss this on Canvas.]