This AI Paper Introduces KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions

Machine learning interpretability is a critical area of research for understanding complex models’ decision-making processes. These models are often seen as “black boxes,” making it difficult to discern how specific features influence their predictions. Techniques such as feature attribution and interaction indices have been developed to shed light on these contributions, thereby enhancing the transparency […]

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