Description
1. (R and Python) For classification, assume that there may be more than two classes. You can assume that
values of the class variable are integers starting with 1. Assume that a training dataset and a test dataset
are available. Modify your program in Assignment #2 to do followings.
a. Prompt the user whether to run regression or classification.
b. If regression is chosen, perform the linear regression as you did in Assignment #2. (You have
nothing to work on the regression algorithm in this assignment).
c. If classification is chosen, ask the user the filename of the training and test dataset. (Assume the
column location of the class variable is the same for both training and test dataset.)
a. Make the program to implement (i) LDA and (ii) QDA that can handle more than two classes.
d. Perform (i) LDA or (ii) QDA depending on the choice by the user. Use a data file named ‘veh.dat’ for
the training and ‘vehtest.dat’ as the test data.
e. The output file for classification generated by the program must look like below. (The numbers are
fictitious).
ID, Actual class, Resub pred
—————————–
1, 1, 1
2, 2, 2
3, 1, 1
(continue)
Confusion Matrix (Resubstitution)
———————————-
Predicted Class
1 2 3 4
Actual 1 239 14 6 8
Class 2 12 153 5 12
3 2 4 98 2
4 3 6 8 123
Model Summary (Resubstitution)
——————————
Overall accuracy = .793
ID, Actual class, Test pred
—————————–
1, 1, 1
2, 2, 2
3, 1, 1
(continue)
Confusion Matrix (Test)
———————————-
Predicted Class
1 2 3 4
Actual 1 239 14 6 8
Class 2 12 153 5 12
3 2 4 98 2
4 3 6 8 123
Model Summary (Test)
——————————
Overall accuracy = .793
