Consider the following data containing 4 training data points consisting of two features x1 and x2 (so here p = 4, N = 2):

Our goal is to approximate y as (linear regression)

a. Apply feature scaling to x2 to make it on the same scale with x1, more specifically,

b, Provide the equation which gives the values of . Provide the values.

c. Find the mean squared error (MSE) for the training data which is defined as

4. Consider the following data containing 4 training data points consisting of two features 261 and 962 (so here p = 4-,N = 2): Training Data #1 #2 #3 #4 x1 (feature 1) -1 0 1 2 x2 (feature 2) 1000 1200 500 1800 y -1 1 3 3.5 Our goal is to approximate y as (linear regression). y z 30 + 31361 + 32x2 a. Apply feature scaling to x2 to make it on the same scale with x1, more specifically, x2 1000 500 b. Provide the equation which gives the values of 30,131. 32. Provide the values 30:51: z. c. Find the mean squared error (MSE) for the training data which is defined as 362( MSE _ RSS _ N