<ul><li>A new Explainable Artificial Intelligence (XAI) method called ShapG (Explanations based on Shapley value for Graphs) has been developed for measuring feature importance.</li><li>ShapG is a model-agnostic global explanation method that defines an undirected graph based on the dataset and calculates feature importance using an approximated Shapley value.</li><li>Comparisons with existing XAI methods demonstrate that ShapG provides more accurate explanations and exhibits advantages in terms of computational efficiency.</li><li>The ShapG method has wide applicability and can improve the explainability and transparency of AI systems in various fields.</li></ul>

ShapG: new feature importance method based on the Shapley value

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