Model Summary: Global Explanations

Global Feature importance evaluates the significance of each feature across an entire dataset or project. It provides a comprehensive understanding of how various features contribute to the model's predictions or outcomes on a broader scale.

The 'Model Summary' section in ML Explainability displays the global feature importance. The global feature importance is the aggregation of features and feature importance across all the baseline data.

Below this graph, the 'Feature used' section provides details of all features used in Explainability.