Problem
The term churn in marketing means that a customer switches loyalty to another company. The file CustomerChurn.xlsx contains data on over 3000 customers of a cell phone provider. Columns B through N provide information about the account and usage of each customer and column O indicates whether the customer churned during the given period of time.
Assign a weight vector to the data (features), and then compute the weighted combination of the data for each customer. Let's refer to the customer's weighted combination as the customer's discriminant score. Then given a cutoff score, classify a customer into a class depending on which side of the cutoff score the customer's discriminant score falls.
Use the enclosed data and the Excel Solver to develop a classification model for predicting whether a customer will churn by finding the optimal weight vector and cutoff score that maximizes the percentage of correct classifications in the training data. Clearly explain what your decision variables, constraints, and objective function are, what solving method you use, and what your optimal solution is.