SHAP Values (SHapley Additive exPlanations)
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YouTubeData Science Foundry
SHAP Values (SHapley Additive exPlanations)
Understanding SHAP Values (SHapley Additive exPlanations) SHAP is a framework used in Explainable AI (XAI) to interpret complex machine learning models. Rooted in game theory, it fairly attributes a model's prediction to each of its features. How it works: 1️⃣ Baseline: Start with the average prediction of the model across the dataset ...
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SHAP Values (SHapley Additive exPlanations)
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