Predicting Flight Delays (Bootstrap Forest and 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 what 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.11