LIME

LIME (Local Interpretable Model-agnostic Explanations) is a technique used to understand the predictions of machine learning models by approximating them locally with a more interpretable model. It focuses on explaining individual predictions by perturbing the input data around a specific instance and observing how the model's prediction changes. This allows one to identify which features are most important for that particular prediction, even if the underlying model is complex and opaque.