Jerry Stevenson is the manager of a travel agency. He wants to build a model that can predict customers’ annual spending on travel products. 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 annual household spending on travel products (TravelSpend). A portion of the Travel_Data worksheet is shown in the accompanying table. Create a regression tree model for predicting the customer’s annual household spending on travel products (TravelSpend). 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 the minimum error tree? What are the rules that can be derived from the root node of the best-pruned tree? 

b. What are the RMSE and MAD of the best-pruned tree on the test data? 

c. Score the two new customers in the Travel_Score worksheet using the best-pruned tree. What are their predicted annual spending amounts on travel products?

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College CreditCard Yes Yes No Yes I Yes Yes FoodSpend 5472.43 9130.73 ⠀ 5584 Income Income TravelSpend 49150 827.4 47806 863.55 : 53504 I 1748.1