Developing and Evaluating Graph Counterfactual Explanations with
GRETEL
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Mario Alfonso Prado-Romero, Bardh Prenkaj and Giovanni Stilo
Counterfactual Explanations
• Answer the question: “how should an input instance be perturbed to obtain a desired predicted label?"
• Provide recourse to the users via feedback they can act upon to change the prediction result in their favor.
• Help to indetify bias and increase fairness.
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GCE Literature Limitations
• No well-established datasets
• No standard evaluation metrics
• Distinct oracles, built on different frameworks, are used for the same datasets
• Doesn’t compare exhaustively with other state-of-the-art methods
GRETEL
• Framework for evaluating and developing GCE methods
• Open source with modular and extensible design
• Integrates state-of-the-art datasets, oracles, explainers and evaluation metrics
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GRETEL
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Live Demo
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