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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

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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)
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