Part 4 (40 points)

Implement a gradient descent function for linear regression:

W₁+1 = Wi - ai

The function will take trainData (RDD of Labeled Point) as an argument and return a tuple of weights and training errors. Reuse the code that you have written in Part 1 and 2.

Initialize the elements of vector w = 0 and a = 1. Update the value of a in ith iteration using the formula:

α₂ =

Σ(w.x; - u;)x;

Test the function on and example RDD. Run it for 5 iterations and print the results.

Q