What is LIME?

LIME (Local Interpretable Model-agnostic Explanations) is a technique that explains the predictions of any classifier in an interpretable and faithful manner by learning an interpretable model locally around the prediction. It helps understand why a machine learning model made a specific prediction for a particular instance. It is commonly used for debugging models, building trust in models, and providing insights into how models are making decisions.