15.5 Pros and cons

Pros

• Most used continuous dependent variable metrics (RMSE, MAD, \(R^2\)) provide a fairly simple way to compare the suitability of predicted and actual values.

• For binary/categorical dependent variables, the use of ROC-AUC and lift charts provide a comprehensive metric to compare models performance.

Cons

• Some continuous dependent variable mtrics (i.e., RMSE) can be sensitive to outliers.

• Binary dependent variable metrics can vary on the selected cut-off values used for creating predictions.