What is 'Feature Importance'?

What is 'Feature Importance'?

Approach: Explain measuring how much each feature contributes to the model's predictions.

Techniques that assign a score to input features based on how useful they are at predicting a target variable. In trees, it is often calculated based on the total decrease in impurity brought by that feature.

Follow-up: Can feature importance be misleading for correlated features?

Key concepts: permutation importance, impurity decrease, shap.