A perfect model
In this exercise you will reconstruct the lift curve of a perfect model. To do so, you need to construct perfect predictions.
Recall that the plot_lift_curve method requires two values for the predictions argument: the first argument for the target to be 0 and the second one for the target to be 1.
This exercise is part of the course
Introduction to Predictive Analytics in Python
Exercise instructions
- Construct a list that has perfect predictions.
- The true values of the target are in
targets_test. Plot the lift curve using the perfect predictions.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Generate perfect predictions
perfect_predictions = [(1-target , ____) for target in targets_test["target"]]
# Plot the lift curve
skplt.metrics.____(targets_test, ____)
plt.show()