Jerry Stevenson is the manager of a travel agency. He wants to build a model that can predict whether or not a customer will travel within the next year. He has compiled a data set that contains the following variables: whether the individual has a college degree (College), whether the individual has credit card debt (CreditCard), annual household spending on food (FoodSpend), annual income (Income), and whether the customer has plans to travel within the next year (TravelPlan, 1 = has travel plans, 0 = does not have travel plans). A portion of the Travel_Plan_Data worksheet is shown in the accompanying table. Create a classification tree model for predicting whether or not the customer will travel within the next year (TravelPlan). Select the best-pruned tree for scoring and display the full-grown, best-pruned, and minimum error trees.

a. How many leaf nodes are in the best-pruned tree and minimum error tree? What are the predictor variable and split value for the root node of the best-pruned tree? 

b. What are the classification accuracy rate, sensitivity, and specificity of the best-pruned tree on the test data? 

c. Generate the ROC curve. What is the area under the ROC curve (or AUC value)? 

d. Score the two new customers in the Travel_Plan_Score worksheet using the best-pruned tree. What is the probability of the first customer having plans to travel within the next year? What is the probability for the second customer?

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College Credit Card No No Yes No ⠀ B No No FoodSpend 2905.97 4677.03 ⠀ 1892.37 Income 65982 57274 ⠀ 77626 TravelPlan 1 1 B 0