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--- ai_explainability_manager [2025/05/27 01:18] – [Example 1: Initialization and Explaining a Prediction] eagleeyenebula
+++ ai_explainability_manager [2025/05/27 01:24] (current) – [Class Overview] eagleeyenebula
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 ====== AI Explainability Manager ======
 **[[https://autobotsolutions.com/god/templates/index.1.html|More Developers Docs]]**:
-The **AI Explainability Manager System** leverages **SHAP** (SHapley Additive exPlanations) to provide detailed insights into machine learning model predictions. By calculating and visualizing **SHAP values**, this system enables practitioners to understand the contribution of each input feature to the prediction outcome, enhancing model transparency and aiding in debugging or stakeholder trust.
+The **AI Explainability Manager System** leverages **SHAP** (**SHapley Additive exPlanations**) to provide detailed insights into machine learning model predictions. By calculating and visualizing **SHAP values**, this system enables practitioners to understand the contribution of each input feature to the prediction outcome, enhancing model transparency and aiding in debugging or stakeholder trust.
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 * **Outputs**:
-  * A **SHAP** summary plot visualizing the feature importance for the given `input_data`.
+  * A **SHAP** summary plot visualizing the feature importance for the given **input_data**.
 ===== Usage Examples =====