Calculating AUC

The AUC value assesses how well a model can order observations from low probability to be target to high probability to be target. In Python, the roc_auc_score function can be used to calculate the AUC of the model. It takes the true values of the target and the predictions as arguments.

You will make predictions again, before calculating its roc_auc_score.

The model logreg from the last chapter has been created and fitted for you, the DataFrame X contains the predictor columns of the basetable. Make predictions for the objects in the basetable.
Select the second column of predictions, as it contains the predictions for the target.
The true values of the target are loaded in y. Use the roc_auc_score function to calculate the AUC of the model.

Exercise

Calculating AUC

Instructions