ReddRadar
Agent skill
alibi-explainer
Alibi explainability skill for counterfactual explanations, anchors, and trust scores.
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/data-science-ml/skills/alibi-explainer
SKILL.md
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
{
"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" }
}
},
"anchorConfig": {
"type": "object",
"properties": {
"threshold": { "type": "number" },
"coverageSamples": { "type": "integer" },
"beamSize": { "type": "integer" }
}
},
"cemConfig": {
"type": "object",
"properties": {
"mode": { "type": "string", "enum": ["PP", "PN"] },
"kappaMin": { "type": "number" },
"kappaMax": { "type": "number" }
}
},
"trainingDataPath": {
"type": "string",
"description": "Path to training data (required for some explainers)"
}
}
}
Output Schema
{
"type": "object",
"required": ["status", "explanations"],
"properties": {
"status": {
"type": "string",
"enum": ["success", "error"]
},
"explanations": {
"type": "array",
"items": {
"type": "object",
"properties": {
"instanceId": { "type": "string" },
"originalPrediction": { "type": "string" },
"explanation": { "type": "object" }
}
}
},
"counterfactuals": {
"type": "array",
"items": {
"type": "object",
"properties": {
"instanceId": { "type": "string" },
"counterfactual": { "type": "object" },
"targetClass": { "type": "string" },
"changedFeatures": { "type": "array" }
}
}
},
"anchors": {
"type": "array",
"items": {
"type": "object",
"properties": {
"instanceId": { "type": "string" },
"rules": { "type": "array", "items": { "type": "string" } },
"precision": { "type": "number" },
"coverage": { "type": "number" }
}
}
},
"trustScores": {
"type": "array",
"items": {
"type": "object",
"properties": {
"instanceId": { "type": "string" },
"score": { "type": "number" },
"closestClass": { "type": "string" }
}
}
}
}
}
Usage Example
{
kind: 'skill',
title: 'Generate counterfactual explanations',
skill: {
name: 'alibi-explainer',
context: {
modelPath: 'models/loan_classifier.pkl',
explainerType: 'counterfactual',
instancePath: 'data/rejected_applications.csv',
counterfactualConfig: {
targetClass: 1,
maxIterations: 1000,
lambda: 0.1
},
trainingDataPath: 'data/train.csv'
}
}
}
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