Timeline violation
To illustrate the importance of the timeline, consider an example where you violate the timeline and use information from the target period to construct the predictive variables.
There are two columns in the pandas dataframe basetable: "amount_2017" is the total amount of donations in 2017, and "target" is 1 if this amount is larger than 30 and 0 else.
Construct a logistic regression model that uses "amount_2017" as single predictive variable to predict the target, and calculate the AUC.
This exercise is part of the course
Intermediate Predictive Analytics in Python
Exercise instructions
- Create a dataframe
Xthat contains the predictive variable and a dataframeythat contains the target. - Fit the logistic regression model such that
yis predicted fromX. Construct a logistic regression model that usesamount_2017as single predictive variable and predictstarget. - Make predictions for the objects in
X. - Calculate and print the AUC of this model using the function
roc_auc_score.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Select the relevant predictors and the target
X = basetable[["____"]]
y = basetable[["____"]]
# Build the logistic regression model
logreg = linear_model.LogisticRegression()
logreg.____(____, ____)
# Make predictions for X
predictions = logreg.____(____)[:,1]
# Calculate and print the AUC value
auc = ____(____, ____)
print(round(auc, 2))