What does a high Coverage percentage indicate about a model?

A high Coverage percentage in the context of a model indicates that the model covers a high proportion of the dataset. This means that the model is capable of making predictions on a large portion of the available data, which is crucial for ensuring that the model is tested and validated on diverse samples. High coverage suggests that the model is likely to generalize well across various scenarios and data points because it has encountered enough representative examples during its training phase.

In practical terms, effective coverage leads to more robust and reliable performance, as the model has learned from a broad spectrum of cases rather than being limited to a narrow set of examples. Thus, a model exhibiting a high Coverage percentage demonstrates its applicability and readiness for real-world situations where it needs to handle varied input.