“Enhancing Model Transparency: Simple Insights with SHAP and Feature Engineering”

SHAP (SHapley Additive exPlanations) is a tool used in the field of machine learning to explain the output of models. It helps to understand how each feature in the dataset contributes to the prediction of a model, making the model’s decisions transparent and interpretable.

What is SHAP Used for

1.Model Explanation

2.Feature Importance