LIME: local interpretable model-agnostic explanations

When a complex model makes a prediction for a specific individual, a natural question arises: why did the model make this particular decision?  LIME approaches this question with a simple and intuitive idea: even if a model is complicated overall, it may behave in a simpler way locally, around a specific data point. Instead of trying to understand the entire model, LIME focuses on one instance at a time. It does this by: - Generating small variations of the original input, - Observing how the model’s prediction changes, - Fitting a simple, interpretable model to approximate the behavior of the complex model in that small neighborhood. The result is a local explanation: a simplified view of how the model behaves near that particular point.