In this homework, we will study the effect of different regularizations with respect to different hyper-parameters. You will build a linear regression model for the data file sample_linear_regression_data.txt, stored under c:/spark/data/mslib after you install your Spark following the instructors directions and compare 2 among L1, L2, and Elastic Net regularizations with = 0 10 0.1. Input:sample_linear_regression_data.txt and hyper-parameters Output: three tables of 2s w.r.t for L1, L2, and Elastic Net regularizations. Ideas: You first follow the lecture slides for Linear Methods RDD APIs to get your Scala program works and understand ins and outs of each statement. Next, try to experiment different settings for L1, L2, or Elastic Net regularizations with a fixed = 0.1 and make sure each individual setting works. Lastly, create a for-loop to compute 2 for each , running from 0.0, 0.1, 0.2, , 10.0. You could pack (, 2) in a tuple.