Generalization error problem on training set

Training data: $$\mathcal {T} =\{(2,1),(3,2),(4,6),(0,0),(1,1)\}$$

you already computed a predictor for the output using linear regression by least squares, where you used the first 3 samples as training samples:

$$f(X) = -4.5 + 2.5X$$

Approximate the generalization error using the validation set approach, i.e. on the remaining validation set.

How I started:

$$\text{Error = Irreducible Error + Bias^2 + Variance .}$$

$$\text{EGE(f, x_0) =σ^2_ε + [E_T (f_T (x_0)) − f_{exact}(x_0)]^2 + E_T(f_T (x_0) − E_T (f_T (x_0)))^2 }$$

How to compute the term $$E_T (f_T (x_0))$$ and $$E_T(f_T (x_0) − E_T (f_T (x_0)))^2$$