: These models often require large datasets and can be sensitive to "adversarial noise" (small character-level changes that fool the AI).
: Common architectures include Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) used to model complex relationships in text data.
In this context, "deep text" refers to the application of techniques to Natural Language Processing (NLP) . 113941
: 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.
Post-hoc explanation of black-box classifiers using confident itemsets : These models often require large datasets and
: Sentiment analysis of customer reviews, biomedical literature summarization, and disease-treatment classification.
Are you researching for a specific industry? : The paper introduces Confident Itemsets Explanation (CIE)
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.