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.
Este exercício faz parte do curso
Intermediate Predictive Analytics in Python
Instruções do exercício
- Create a dataframe
X
that contains the predictive variable and a dataframey
that contains the target. - Fit the logistic regression model such that
y
is predicted fromX
. Construct a logistic regression model that usesamount_2017
as 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
.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# 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))