SHAP (SHapley Additive exPlanations) offers a way to interpret machine learning models by attributing feature importance to predictions. Utilized by data scientists and AI developers, its robust approach provides a comprehensive understanding of complex models. Its ability to explain individual predictions promotes transparency, turning intricate data into insightful, actionable decisions, making it an invaluable tool for businesses across multiple sectors.
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