assistance with deriving

3. Locally Weighted Linear Regression and bias-variance tradeoff Consider a dataset with n data points (x,, y;), x, E RP, drawn from the following linear model: vi = B* xi te, i = 1, 2, ....n where c is a Gaussian noise and the star sign is used to differentiate the true parameter from the estimators that will be introduced later. Consider the regularized linear regression as follows: p(A) = arg min n where 1 2 0 is the regularized parameter. Let X E R" denote the matrix obtained by stacking x, in each row. 1. (10 points) Derive the bias as a function of 1 and some fixed test point x. 2. (10 points) Derive the variance term a function of 1