Predicting Flight Delays (Bootstrap Forest aod Boosted Trees). We return to the

flight delays data for this exercise, and fit both a bootstrap forest and a boosted tree

to the data. Use scheduled departure time (CRS.DEP TIME) rather than the binned

version for these models.

a. Fit a bootstrap forest, with the default settings. Save the formula for this models

to the data table.

i. Look at the column contributions report. Which variables were involved in

the most splits?

ii. What is the error rate on the test set?

b. Fit a boosted tree to the flight delays data, again with the default settings. Save the

formula to the data table.

i. Which variables were involved in the most splits? Is this similiar to wbat you

observed with the bootstrap forest model?

ii. What is the error rate on the test set for this model?

c. Use the Model Comparison platform to compare these models to the final reduced

model found earlier (again, put the validation column in the Group field in the

Model Comparison dialog.

i. Which model has the lowest overall error rate on the test set?

ii. Explain why this model might have the best performance over the other models

you fit.