This article explains how Shapley values, a method used in game theory to fairly distribute gains and costs to actors working in a coalition, can be used to interpret a machine learning model.
- The Shapley value is a method used in game theory to fairly distribute gains and costs to actors working in a coalition, ensuring each actor gets a fair share based on their contribution.
- Shapley values can be used to determine the contribution of each feature in a group, such as advertising strategies.
- SHAP can be used to visualize the contribution and importance of each feature in a machine learning model, such as daily internet usage and area income.
- The Python library SHAP uses Shapley values to explain the output of any machine learning model.
