Derive this Machine learning calculas problem

D Question 2 2 pts Show that ridge regression is equivalent to OLS on an augmented dataset that has been augmented as follows . Assume the data in X are standardized (centered and unit-variance) . Append the d x d matrix vI to X Note that is a scalar lit is the regularization parameter) and I is a d d identity matrix . The augmented data matrix R(N+)xd, where the final d rows comprise the matrix . Append a vector of zeros of length d to the output vector y The augmented output vector y E RN+4, where the hnal d elements are zeros Hint: Write the SSE cost function with the augmented dataset and expand/manipulate it to show that it can be equivalently expressed as the ridge regression cost function. Your submission will be an uploaded file including all your work deriving the solution. Upload Choose a File D Question 2 2 pts Show that ridge regression is equivalent to OLS on an augmented dataset that has been augmented as follows . Assume the data in X are standardized (centered and unit-variance) . Append the d x d matrix vI to X Note that is a scalar lit is the regularization parameter) and I is a d d identity matrix . The augmented data matrix R(N+)xd, where the final d rows comprise the matrix . Append a vector of zeros of length d to the output vector y The augmented output vector y E RN+4, where the hnal d elements are zeros Hint: Write the SSE cost function with the augmented dataset and expand/manipulate it to show that it can be equivalently expressed as the ridge regression cost function. Your submission will be an uploaded file including all your work deriving the solution. Upload Choose a File