Linear regression models: polynomial regression Let x E R' be an independent variable and / E R its associated target variable. We consider the polynomial model y ( x ) : = wot wix1 + wax2 + waxjx2 + wax, + waxz. We further assume the target variables, obtained from such a model, be affected by additive Gaussian noise: 1 (x) = y(x) +E, with p(e) = N(E | 0,02). (a) What is the data likelihood of a single observation, p(r | x)? (b) What is the joint likelihood of a series of i.i.d. observations, X = {x,}, with target variables t = { }, p(t | X)? (c) State the quadratic error function associated with the maximum likelihood estimation (MLE) problem for the parame- ters w = (wo, . .., Ws)