Constructing the cumulative gains curve

The cumulative gains curve is an evaluation curve that assesses the performance of your model. It shows the percentage of targets reached when considering a certain percentage of your population with the highest probability to be target according to your model.

To construct this curve, you can use the .plot_cumulative_gain() 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.

Cet exercice fait partie du cours

Introduction to Predictive Analytics in Python

Afficher le cours

Instructions

Import the matplotlib.pyplot module.
Import the scikitplot module.
Construct the cumulative gains curve, given that the model outputs the values in predictions_test and the true target values are in targets_test.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Import the matplotlib.pyplot module 
import ____.____ as plt

# Import the scikitplot module
import ____ as skplt

# Plot the cumulative gains graph
skplt.metrics.____(targets_test, ____)
plt.show()

Modifier et exécuter le code