using MSE as the cost function. Prove that the closed-form solution for Ridge Regression is w = (al + X] . X) -1 . XT . y, where I is the identity matrix, X = (x(1), x(2), ...,x(m)) is the input data matrix, x () = (1, X1, X2, ..., Xn) is the i-th data sample, and y = (y(1), y(2), ..., ym). Assume the hypothesis function hw(x) = Wo + WIX1 + W2x2+ ... + WnXn, and yis the measurement of hw(x) for the j-th training sample. The cost function of the Ridge Regression is E(w) = EF 1(W . x(i) - y(1)) 2 + 2 Em, Wi2