AI engineering glossary · AI ethics law product
What is SHAP?
SHAP (also called SHapley Additive exPlanations): A method that explains a prediction by assigning each feature a contribution value based on Shapley values from cooperative game theory. The contributions add up to the difference between the prediction and the average prediction, and can be aggregated for global views.
SHAP: an example
For a house-price model predicting Rs 85 lakh against an average of Rs 70 lakh, SHAP might attribute +9 lakh to area and +6 lakh to location.
Related terms
- Shapley value
- LIME
- Local explanation
- Feature importance
More AI ethics law product terms
- Significant Data Fiduciary
- Transparency (AI)
- Trust calibration
- Verifiable parental consent
- Watermarking AI outputs
- Accountability (AI)
- Activation rate
- AI audit
Where you learn it
SHAP is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.