Logistic regression prediction
As with linear regression, the joy of logistic regression is that you can make predictions. Let's step through the prediction flow one more time!
churn and mdl_churn_vs_both_inter are available; itertools.product is loaded.
This exercise is part of the course
Intermediate Regression with statsmodels in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create time_since_first_purchase
time_since_first_purchase = ____
# Create time_since_last_purchase
time_since_last_purchase = ____
# Create p as all combinations of values of time_since_first_purchase and time_since_last_purchase
p = ____
# Transform p to a DataFrame and name the columns
explanatory_data = ____
# Print the result
print(explanatory_data)