Model Diagnostics, Machine Learning.
This helps assess how well the model generalizes to unseen variations. Adversarial Testing: Generate or obtain adversarial examples, which are intentionally crafted inputs designed to mislead the model. Test the model’s performance on these adversarial samples. Noisy Data Testing: Add random noise