ComeçarComece de graça

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.

Este exercício faz parte do curso

Intermediate Predictive Analytics in Python

Ver curso

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# AUC of model in July:
predictions = logreg.____(test_july[["age", "max_amount"]])[:,1]
auc = ____(test_july["target"], predictions)
print(auc)
Editar e executar o código