What are the applications of SHAP in machine learning?

What are the applications of SHAP in machine learning?

SHAP, or SHapley Additive exPlanations, is used for interpreting model predictions. It helps in understanding feature importance.

Can you give me some specific examples of how SHAP is used?

Sure! SHAP is used in finance for credit scoring, in healthcare for patient risk assessment, and in marketing for customer segmentation.

How does SHAP improve model transparency?

SHAP provides a unified measure of feature importance, allowing stakeholders to see how each feature contributes to predictions, enhancing trust.

Are there any limitations to using SHAP?

Yes, SHAP can be computationally expensive for large datasets and complex models, which may limit its practicality in some scenarios.