alibi-explainer

# alibi-explainer ## Overview Alibi explainability skill for counterfactual explanations, anchors, trust scores, and advanced model interpretation techniques. ## Capabilities - Counterfactual instance generation - Anchor explanations (rule-based) - Integrated gradients for deep learning - Kernel SHAP integration - Contrastive Explanation Method (CEM) - Trust scores for prediction confidence - Pertinent positives and negatives - Prototype and criticism selection ## Target Processes - Model Interpretability and Explainability Analysis - Model Evaluation and Validation Framework ## Tools and Libraries - Alibi - Alibi Detect - TensorFlow/PyTorch - scikit-learn ## Input Schema ```json { "type": "object", "required": ["modelPath", "explainerType", "instancePath"], "properties": { "modelPath": { "type": "string", "description": "Path to the trained model" }, "explainerType": { "type": "string", "enum": ["counterfactual", "anchor", "integrated_gradients", "cem", "trust_score", "prototype"], "description": "Type of Alibi explainer to use" }, "instancePath": { "type": "string", "description": "Path to instance(s) to explain" }, "counterfactualConfig": { "type": "object", "properties": { "targetClass": { "type": "integer" }, "maxIterations": { "type": "integer" }, "lambda": { "type": "number" }, "featureRange": { "type": "object" } } }, "anchorC...