A consumer advocacy agency, Equitable Ernest, is interested in providing a service that allows an individual to estimate their own credit score (a continuous measure used by banks, insurance companies, and other businesses when granting loans, quoting premiums, and issuing credit). The file creditscore contains data from several thousand individuals. The variables in these data are listed in the following table.

Predict the individuals’ credit scores using an individual regression tree. Use 100%
of the data for training and validation and set aside no data as a test set.

a. Train a full regression tree and report its RMSE from a validation experiment.

b. Train a pruned regression tree and report its RMSE from a validation experiment.

c. Compare the RMSE from the full regression tree in part (a) to the RMSE from the pruned regression tree in part (b). Explain the difference.

d. Consider an individual with 5 credit bureau inquiries, that has used 10% of their available credit, has $14,500 of total available credit, has no collection reports or missed payments, is a homeowner, has an average credit age of 6.5 years, and has worked continuously for the past 5 years. Using the pruned tree from part (b), what is the predicted credit score for this individual?

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Variable Bureaulnquiries CreditUsage TotalCredit Collected Reports Missed Payments HomeOwner CreditAge TimeOnJob CreditScore Description number of inquiries about an individual's credit percent of an individual's credit used total amount of credit available to individual number of times an unpaid bill was reported to collection agency number of missed payments 1 if individual is homeowner. O if not average age of individual's credit how long the individual has been continuously employed score between 300 and 850 with larger number representing increased credit worthiness