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How does SHAP (Shapley Additive Explanations) contribute to explainability?
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Answer Posted / Sourabh Kumar Bhargava
SHAP (Shapley Additive Explanations) is a method for explaining the output of any model by splitting the total prediction into additive contributions from each feature. It assigns a value to each feature, representing its marginal contribution to the final prediction. This helps understand how each feature impacts the overall outcome.
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