shap - Explain machine learning models with SHAP
Computes SHAP values and visual explanations for interpreting, debugging, comparing, and assessing machine learning models.
Tags
Updated: 2026-10-03Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Compute SHAP values
- Generate SHAP plots
- Explain individual predictions
- Debug model behavior
- Analyze bias and fairness
- Compare model importance
- Analyze feature interactions
- Deploy model explanations
Inputs
- Trained machine learning model
- Input or test data
- Background data
- Model output specification
- Protected-group attributes
Outputs
- SHAP values
- Feature-importance plots
- Individual prediction explanations
- Model analysis findings
- Explanation service endpoints
Requirements
- Python environment with SHAP installed
- Compatible model framework
- Access to model and data