Visualizing Classification Model Outputs

The data

The data that we will use for the following plots is a customer churn dataset that details many important people attributes such as their Age, CreditScore, gender (1 if male and 0 otherwise), etc. We also notice some one-hot encoded columns Geography_France, Geography_Germany, and Geography_Spain. These values are either 1 or zero, so if a person is from France, Geography_France=1, Geography_Germany=0, and Geography_Spain=0. We then use these variables to predict whether someone has Exited (churned).