Data Science

Final Project Part 6: Feature Importance

Senior Data Analyst
May 26, 2026
5 min read

Feature Importance

importance = pd.Series(best_model.feature_importances_, index=X.columns)

importance.sort_values(ascending=False).head(10).plot(kind='barh')

plt.title('Top 10 Features for Churn Prediction')

plt.show()

*Day 147: Business Recommendations.*

Ready to put your knowledge into practice?

Join SQL Mastery and learn through interactive exercises.