SHAP Prediction Explanations estimate how much each feature contributes to a given prediction differing from the average. They are intuitive, unbounded (computed for all features), fast, and, due to the open source nature of SHAP, transparent. Not only does SHAP provide the benefit of helping you better understand model behavior&mdash;and quickly&mdash;it also allows you to easily validate if a model adheres to business rules. 

Use SHAP to understand, for each model decision, which features are key. What drives a particular customer's decision to buy&mdash;age? gender? buying habits?&mdash;what is the magnitude on the decision for each factor?



