Description
Modify your program for Assignment #8 to do followings. You may use one of two (R or Python)
language for this assignment.
1. Prompt the user whether to run regression or classification.
2. If classification is chosen, prompt the user to choose (i) LDA and (ii) QDA, (iii) RDA, (iv) Logistic
regression, (v) Naïve Bayes, (vi) 1-level decision tree, or (vii) Bagging Ensemble. However, if the
data has more than two classes, do not prompt (iv), (v) and (vi).
3. For Bagging Ensemble method, use LDA as the classifier and 51 bootstraps as the number of resampled data.
4. Use a file named “veh.dat” for the training and ‘vehtest.dat’ as the test data in this assignment.
The last column is the class variable.
5. Perform (i)-(vii) methods depending on the choice by the user. Only the output of the test data is
necessary for this assignment.
The output file for classification generated by the program must look like
(1) LDA – no bagging
ID, Actual class, LDA-nobagging pred
—————————–
1, 1, 1
2, 2, 2
3, 1, 1
(continue)
Confusion Matrix (LDA – no bagging)
———————————-
Predicted Class
1 2
Actual 1 239 14
Class 2 12 153
Model Summary (LDA – no bagging)
——————————
Overall accuracy = .793
(2) LDA – bagging
ID, Actual class, LDA-bagging pred
—————————–
1, 1, 1
2, 2, 2
3, 1, 1
(continue)
Confusion Matrix (LDA – bagging)
———————————-
Predicted Class
1 2
Actual 1 239 14
Class 2 12 153
Model Summary (LDA – bagging)
——————————
Overall accuracy = .793
