Assigned Material: Retail Relay (C), UVA-M-UBBS Detection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models. Journal of Marketing Research Chapter 4: Decision Trees - from introduction to Data Mining by Tan, Steinbach, and Kumar Assignment Questions: 1. Use the Relay train data to deveiop a model to predict customer retention. You may use logistic regression to predict the variable "retained." You can use any combination of the independent variables available in the data to obtain a model with the best predictive ability and usability. You are free to use different transformations and combinations of the independent variables. Be aware that there is no \"magic bullet" to finding the ideal model. You will have to go through multiple iterations. 2. Once you obtain the best model that you can find, predict retention in the test data. You will use the coefficients obtained from the model estimated using the train data to do this. Name this predicted value "pretain." 3. Calculate the hit rate. This can be calculated as % of matches between the value of pretain and retained in the train data. 4. Be prepared to present your results in class. The team with the best model, as judged by your peers, will win "bragging rights."