SHAP Analysis: Revision history

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    29 November 2024

    • curprev 17:3817:38, 29 November 2024‎ Fortify talk contribs‎ 2,985 bytes +2,985‎ Created page with "'''SHAP Analysis''' (SHapley Additive exPlanations) is a machine learning interpretability technique based on cooperative game theory. It is used to explain the predictions of complex machine learning models by attributing the contribution of each feature to the model's output. SHAP values provide a consistent and mathematically sound way to interpret individual predictions and global feature importance. ==Overview== SHAP values are derived from Shapley values, a concept..." Tag: Visual edit
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