Shapley Values

Shapley values is a concept in cooperative game theory that assigns a value to each player in a game based on their marginal contributions to the overall outcome. In the context of machine learning, Shapley values are used to explain the predictions of a model by attributing the contribution of each feature to the final prediction. Shapley values provide a fair way to distribute the credit among the features and can help in identifying the most important features in a model. The calculation of Shapley values involves computing the average marginal contribution of each feature over all possible feature combinations. This can be computationally expensive, but there are several approximation algorithms available that can speed up the process without sacrificing too much accuracy.

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Shapley Values

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