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.
Bu egzersiz
Intermediate Predictive Analytics in Python
kursunun bir parçasıdırUygulamalı interaktif egzersiz
Bu örnek kodu tamamlayarak bu egzersizi bitirin.
# AUC of model in July:
predictions = logreg.____(test_july[["age", "max_amount"]])[:,1]
auc = ____(test_july["target"], predictions)
print(auc)