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.
: Sentiment analysis of customer reviews, biomedical literature summarization, and disease-treatment classification.
: These models often require large datasets and can be sensitive to "adversarial noise" (small character-level changes that fool the AI). 113941
Post-hoc explanation of black-box classifiers using confident itemsets
In this context, "deep text" refers to the application of techniques to Natural Language Processing (NLP) . The identifier refers to a specific research article
: 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.
If you tell me more about what you're looking for, I can provide more details: Do you need help text classification models? : These models often require large datasets and
: Common architectures include Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) used to model complex relationships in text data.