Download the data set UniversalBank.jmp, again (Don`t use the previously downloaded dataset). Repartition the data UniversalBank.jmp, this time into training, validation, and test sets (50%, 30%, 20%) (Analyze>Predictive Modelling>Make Validation Column and click OK in the next screen) by using the Fixed Random Seed: 456. You must have 2 validation columns in your data set now. Apply the k-NN method with k=10 and by casting the same variables to X-factor and using the new validation column "Validation2." Compare the misclassification rates for the Personal Loan in Training, Validation, and test sets. With this partitioning of the data, the best K, based on the validation data, is K = ___ At the best k, the misclassification rate in the Validation Set is ___%, and in the test set is ___%.

How would you classify a customer with the following information? (You need to save your prediction formula again) Answer: ___

Age = 27, Experience = 5, Income = 110, Family = 2, CCAvg = 4.7, Education = 1, Mortgage = 0, Securities Account = 0, CDAccount = 1, Online = 1 and Credit Card = 1