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Bookmark or Share- A Comprehensive Guide to SHapley Additive exPlanations - GeeksforGeeksSHAP is a framework used to interpret the output of machine learning models. The key idea behind SHAP values is rooted in cooperative game theory and the concept of Shapley values. Unlike other methods, SHAP gives us a detailed understanding of how each feature contributes to predictions.
- Shapley value - WikipediaThe Shapley value is a solution concept in cooperative game theory. It was named in honor of Lloyd Shapley , who introduced it in 1951 and won the Nobel Memorial Prize in Economic Sciences for it in 2012.
- Harlow Shapley - WikipediaHarlow Shapley (November 2, 1885 – October 20, 1972) was an American scientist, head of the Harvard College Observatory (1921–1952), and political activist during the latter New Deal and Fair Deal.
- An introduction to explainable AI with Shapley valuesShapley values are a widely used approach from cooperative game theory that come with desirable properties. This tutorial is designed to help build a solid understanding of how to compute and interpet Shapley-based explanations of machine learning models.
- The Shapley Value for ML Models - towardsdatascience.comSo what is the Shapley value, and why is it central to so many explainability techniques? What questions do Shapley values answer? At a high level, the Shapley value approach attempts to explain why an ML model reports the outputs that it does on an input.
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