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Bookmark or Share- 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.
- 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.
- Lloyd S. Shapley - UCLA EconomicsLloyd Shapley, a UCLA emeritus professor of economics and mathematics and co-winner of the 2012 Nobel Memorial Prize in Economic Sciences, died on March 12. He was 92 years old. Shapley was widely considered one of the fathers of game theory.
- Lloyd Shapley | American Mathematician & Game Theory Pioneer - BritannicaLloyd Shapley (born June 2, 1923, Cambridge, Massachusetts, U.S.—died March 12, 2016, Tucson, Arizona) was an American mathematician who was awarded the 2012 Nobel Prize for Economics. He was recognized for his work in game theory on the theory of stable allocations.
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