Constructing the lift curve
The lift curve is an evaluation curve that assesses the performance of your model. It shows how many times more than average the model reaches targets.
To construct this curve, you can use the plot_lift_curve method in the scikitplot module and the matplotlib.pyplot module. As for each model evaluation metric or curve, you need the true target values on the one hand and the predictions on the other hand to construct the cumulative gains curve.
This is a part of the course
“Introduction to Predictive Analytics in Python”
Exercise instructions
- Import the
matplotlib.pyplotmodule. - Import the
scikitplotmodule. - Construct the cumulative gains curve, given that the model outputs the values in
predictions_testand the true target values are intargets_test.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import the matplotlib.pyplot module
____ as plt
# Import the scikitplot module
____ as skplt
# Plot the lift curve
skplt.metrics.____(____, ____)
plt.show()This exercise is part of the course
Introduction to Predictive Analytics in Python
In this course you'll learn to use and present logistic regression models for making predictions.
Now that you know how to build a good model, you should convince stakeholders to use it by creating appropriate graphs. You will learn how to construct and interpret the cumulative gains curve and lift graph.
Exercise 1: The cumulative gains curveExercise 2: Interpreting the cumulative gains curveExercise 3: Constructing the cumulative gains curveExercise 4: A random modelExercise 5: The lift curveExercise 6: Interpreting the lift curveExercise 7: Constructing the lift curveExercise 8: A perfect modelExercise 9: Guiding business to better decisionsExercise 10: Targeting using cumulative gains curveExercise 11: Business case using lift curveExercise 12: Business case using cumulative gains curveWhat is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.