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1. [2pts] Linear Models. Recall that a function f : R - R is linear if both of the following conditions hold. . For all x, y ER , f(xty) = f(x) + f(y). . For all x E R" and a E R, f(ax) = af (x). Consider the hypothesis class of linear regression. That is, any predictor y(x) = w x with weRD. (0.1) Prove that every linear regression predictor is a linear function. You may use the definition of w x = _; wjx; as well as any basic fact about arithmetic without proof