What is feature importance and how is it computed?
Updated May 16, 2026
Short answer
Feature importance measures how much each feature contributes to model predictions.
Deep explanation
Feature importance can be computed using tree-based models (Gini importance), permutation importance, or SHAP values. It helps interpret models and select relevant features.
Real-world example
Used in healthcare models to identify important risk factors for diseases.
Common mistakes
- Assuming feature importance implies causation.
Follow-up questions
- What is permutation importance?
- What are SHAP values?