AINeutralarXiv – CS AI · Jun 96/10
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SAILS: Surrogate-based Analysis of Interactions via Local Effect Smooths
Researchers introduce SAILS, a model-agnostic framework that goes beyond detecting feature interactions in machine learning models to reveal their functional forms and characteristics. Using surrogate generalized additive models, SAILS categorizes interactions as linear, product-separable, or non-product-separable and provides tailored visualizations, advancing the field of explainable AI.