113941 〈UHD〉

If you tell me more about what you're looking for, I can provide more details: Do you need help text classification models?

: Common architectures include Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) used to model complex relationships in text data.

: Sentiment analysis of customer reviews, biomedical literature summarization, and disease-treatment classification. 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"

The identifier refers to a specific research article titled "Post-hoc explanation of black-box classifiers using confident itemsets" , published in the journal Expert Systems with Applications (Volume 165, March 2021). Key Details of the Research Authors : Milad Moradi and Matthias Samwald. If you tell me more about what you're

: 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.

In this context, "deep text" refers to the application of techniques to Natural Language Processing (NLP) . : It addresses the "black-box" problem where complex

: Explaining the decision-making process of "black-box" Deep Learning (DL) models used in text classification , particularly within the biomedical domain.