LIME, which stands for Local Interpretable Model-agnostic Explanations, is a technique used to provide interpretable and explainable predictions from complex machine learning models. It works by approximating the complex model locally with a simpler, interpretable model to highlight the key features that influenced a specific prediction. This approach is crucial for understanding how models arrive at their decisions and ensuring transparency in Natural Language Processing applications.
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