The effect of seasonality
Assume you want to predict whether a candidate donor will donate next month. As predictive variable, you want to include the maximum gift of each donor in the previous month. As you learned in the video, the mean amount of the gifts in July and September are similar, but the gifts are fairly higher in December. In this exercise, you will see how this can influence the performance of your model.
The logistic regression model is created and fitted for you in logreg on the data in July.
Deze oefening maakt deel uit van de cursus
Intermediate Predictive Analytics in Python
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# AUC of model in July:
predictions = logreg.____(test_july[["age", "max_amount"]])[:,1]
auc = ____(test_july["target"], predictions)
print(auc)