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: The paper introduces Confident Itemsets Explanation (CIE) , a model-agnostic method that identifies sets of features (words or tokens) that strongly influence a model's prediction. 113941

: Explaining the decision-making process of "black-box" Deep Learning (DL) models used in text classification , particularly within the biomedical domain. Are you researching for a specific industry

In this context, "deep text" refers to the application of techniques to Natural Language Processing (NLP) . 113941

: It addresses the "black-box" problem where complex neural networks provide accurate results but lack transparency, which is critical for high-stakes fields like healthcare. Understanding "Deep Text"

Post-hoc explanation of black-box classifiers using confident itemsets