Model Importance:
The relative importance of the feature in the model's predictions
Contribution to Model:
How the feature affects the model's output (positive or negative direction)
Impact on Robustness:
How much the feature affects model robustness when perturbed
Stability Score:
How consistently the feature behaves across different perturbation levels (higher is better)