LIME
Local Interpretable Model-agnostic Explanations is a technique that explains individual predictions by fitting a simple proxy model locally around the input.
Think of It Like This
Like understanding a complex curved road by looking at a tiny, perfectly straight one-meter segment right in front of you.
LIME works by perturbing a specific input sample, feeding those variations into the black-box model, and training a simple linear regression or decision tree on the results. This reveals which features locally drove that specific decision. It provides crucial transparency for high-stakes models in healthcare or finance.