Suppose we want to do polynomial linear regression based on the following dataset: { (2, 3.1), (-0.4, -0.5), (0.8, 1.6)} where each pair (x,t) gives the target value t for a given input x. Suppose that the linear regressor takes the form

t = w₀ + w₁x

(a) Write the error function E(w) for this linear regressor based on the training dataset.

(b) Write down the batch gradient descent algorithm for training the model parameters. Show the exact equations for parameters update based on the given training dataset.