shap

SHAP (SHapley Additive exPlanations) Overview SHAP is a unified approach to explain machine learning model outputs using Shapley values from cooperative game theory. This skill provides comprehensive guidance for: Computing SHAP values for any model type Creating visualizations to understand feature importance Debugging and validating model behavior Analyzing fairness and bias Implementing explainable AI in production SHAP works with all model types: tree-based models (XGBoost, LightGBM, CatBoost, Random Forest), deep learning models (TensorFlow, PyTorch, Keras), linear models, and black-box models. When to Use This Skill Show more