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.
Questo esercizio fa parte del corso
Marketing Analytics: Predicting Customer Churn in Python
Istruzioni dell'esercizio
- Calculate the feature importances of
clf. - Use
plt.barh()to create a horizontal bar plot ofimportances.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Calculate feature importances
importances = ____.____
# Create plot
____.____(range(X.shape[1]), ____)
plt.show()