Direct Mailing to Airline Customers. East–West Airlines has entered into a partnership with the wireless phone company Telcon to sell the latter’s service via direct mail. The file EastWestAirlinesNN.csv contains a subset of a data sample of who has already received a test offer. About 13% accepted. You are asked to develop a model to classify East–West customers as to whether they purchase a wireless phone service contract (target attribute Phone_Sale). This model will be used to classify additional customers.

a. Run a neural net model on these data, using a single hidden layer with five nodes. Remember to first convert categorical attributes into dummies, and use the normalize parameter in the Neural Network operator to normalize the data to a [-1, 1] scale prior to model training. Create a decile lift chart for the training and holdout sets. Interpret the meaning (in business terms) of the leftmost bar of the holdout decile lift chart.

b. Comment on the difference between the training and holdout lift charts.

c. Run a second neural net model on the data, this time setting the number of hidden nodes to 1. Comment now on the difference between this model and the model you ran earlier and how overfitting might have affected results.

d. What sort of information, if any, is provided about the effects of the various attributes?