For this assignment, I want you to make some predictions given some training and test data. Follow the format in the attached sample code 'codeStudents.r' for saving your predictions. Do not deviate from this format for your submission! Only submit test predictions codeSt udents . r Xtra . ta IOIOQOOOOIQOOOOIQOO X . 00.000000000000000 YEE?.iD.-........? Example submission: renHomrig Pr dict" . 00.900009900009000 900000900000900009900009.000090000 The grade on this assignment is going to be as follows. Predictions [50 points]. I'll make predictions of my own (using a basic, quick approach) and get the ABSOLUTE error loss {not squared error loss) on some test data: R_D. You'll submit your predictions, which will be scored on the withheld test supervisors, producing a test error R. Your grade on this part will be determined by occooooccoooo-cooo 9C.d?Cd= mintggad R 1 ) Writeup [50 points]. A brief writeup {no more than 530 words) describing the techniques you used to generate the predictions. Be very specific about what you did. Example: don't just say "I used Elastic net regression". Say what features you used (even if it is all of them) and how you chose tuning parameterts). Some details you should include are: * important features you found and how you judged importance * how you estimated the test error * any visualizations you made about the data Your writeup needn't look like an \"essay\". You can and should use lists to summarize what you did. Include your code as an appendix if you do not use R Markdown (this does not count against the word limit) IMPORTANT: Make your writeup very easy to read. Do not include ANY extraneous output as it will be penalized. yourName = 'firstLast '#fill in your name, no spaces, leave quotes JH 2 load( 'Ytrain. Rdata') 3 Load( 'Xtrain. Rdata' ) 4 Load( 'Xtest . Rdata') 5 6 # Do some applied analytics. . 7 8 ### get preds: X 9 Yhat = data. frame( 'Yhat' = ###PREDICTIONS###) 10 #write . table 11 . if(yourName == 'firstLast'){ 12 print('fill in your name! ') 13 - }else{ 14 fName = paste(c(yourName, 'Predictions. txt' ), collapse=' ') 15 write. table(Yhat, file=fName, row. names=FALSE, col . names=FALSE) 16 -} 17