The file UniversalBank.jmp contains data on 5000 customers. The data include customer demographic information (age, income, etc.), the customer’s relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign.

Data Mining Tasks:

• Perform a k-NN classification with all predictors except ID and ZIP code using k = 10. (Hint: Cast the variable “Personal Loan” to Y, Response and the variable “Validation” to Validation field, all other variables (except for ID and ZIP) to X factors (see the picture below). Set Random Seed=123 (Note: This analysis may take a few minutes)