Consider the predictive model building for the airline on-time performance dataset discussed in Section XXXXXXXXXXFor this model, we selected 6 variables—month, day of the month, day of the week,...

Consider the predictive model building for the airline on-time performance dataset discussed in Section 2.4.3. For this model, we selected 6 variables—month, day of the month, day of the week, hour, flight distance, and days from holiday. Next we developed logistic regression and random forest predictive models.

Select a different set of variables and build logistic regression and random forest predictive models. Do you get different results? Are these results better?

Also experiment with other predictive models such as decision trees and support vector machines.