This research proposes methodologies for evaluating and comparing feature attribution methods, suggesting optimal selections for model predictions.
Feature attribution methods explain model predictions by assigning importance to input features. Choosing the most suitable method is difficult due to inconsistencies and a lack of universal solutions. Our research focuses on proposing tools and methodologies for evaluating, comparing, and selecting these methods.
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Priscylla Silva (2025) studied this question.
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