Run a neural net model on these data, using a single hidden layer with five nodes. Remember to first convert categorical variables into dummies and scale numerical predictor variables to 0–1 (use the scikit-learn transformer MinMaxScaler()). Create a decile lift chart for the training and validation sets. Interpret the meaning (in business terms) of the leftmost bar of the validation decile lift chart.
Comment on the difference between the training and validation lift charts.
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.
What sort of information, if any, is provided about the effects of the various variables?
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