Visualizing feature importances
Your random forest classifier from earlier exercises has been fit to the telco data and is available to you as clf. Let's visualize the feature importances and get a sense for what the drivers of churn are, using matplotlib's barh to create a horizontal bar plot of feature importances.
Den här övningen är en del av kursen
Marketing Analytics: Predicting Customer Churn in Python
Övningsinstruktioner
- Calculate the feature importances of
clf. - Use
plt.barh()to create a horizontal bar plot ofimportances.
Interaktiv övning med praktiskt arbete
Testa den här övningen genom att slutföra den här exempelkoden.
# Calculate feature importances
importances = ____.____
# Create plot
____.____(range(X.shape[1]), ____)
plt.show()