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Counterexample

Instance generated that differs minimally from the original input while producing a different model prediction, allowing to explain the conditions for decision change.

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Hamming Distance

Metric measuring the minimum number of features to modify to transform an instance into a counterexample, essential for evaluating the parsimony of explanations.

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Counterexample Validity

Fundamental criterion ensuring that the generated counterexample actually produces the desired and different prediction from that of the original instance.

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Spatial Proximity

Similarity measure between the original instance and its counterexample in the feature space, crucial for ensuring the relevance and credibility of the explanation.

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Actionability

Ability of a counterexample to suggest feasible and relevant modifications for the user, transforming the explanation into practical recommendations.

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Counterexample Diversity

Generation of sets of counterexamples covering different alternative pathways to modify the prediction, offering a comprehensive view of intervention possibilities.

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Model Robustness

Analysis of prediction stability in the face of counterexamples, revealing the model's weaknesses and its sensitivity areas to input variations.

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Human-Machine Interface

Interactive system allowing users to generate and explore counterexamples, facilitating intuitive understanding of the model's decision mechanisms.

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Causal Interpretation

Extension of counterexamples to identify cause-effect relationships between features and predictions, beyond mere statistical correlations.

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Counterexample Set

Organized collection of counterexamples exploring different modification dimensions, providing a multidimensional understanding of decision boundaries.

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Penalty Regularization

Mechanism controlling the magnitude of modifications allowed during counterexample generation, avoiding unrealistic or excessive changes.

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Membership Constraints

Rules ensuring that counterexamples remain within valid and plausible domains, respecting the physical or logical boundaries of the problem.

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Exploration Method

Systematic algorithm for efficiently discovering relevant counterexamples in the high-dimensional feature space of the model.

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Cost Function

Mathematical expression combining multiple criteria to evaluate the quality of a counterexample, guiding optimization toward the most relevant solutions.

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