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.
Este ejercicio forma parte del curso
Introduction to Predictive Analytics in Python
Instrucciones del ejercicio
- 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 intargets_test
.
Ejercicio interactivo práctico
Prueba este ejercicio completando el código de muestra.
# Import the matplotlib.pyplot module
____ as plt
# Import the scikitplot module
____ as skplt
# Plot the lift curve
skplt.metrics.____(____, ____)
plt.show()