Overview
SHAP is a popular tool for Explainable AI (XAI). It assigns each feature an importance value (a 'Shapley value') for a particular prediction, showing how much that feature contributed to the final result compared to the average prediction.
Key Features
- Local Explanations: Explains why a specific individual was denied a loan.
- Global Explanations: Shows which features are most important for the model overall.
- Model-Agnostic: Works with any algorithm, from simple linear regression to complex neural networks.
Why it's Trusted
It is based on solid mathematical foundations from cooperative game theory, ensuring that the 'credit' for a prediction is distributed fairly among the features.