LASTS is a framework that can explain the decisions of black box models for time series classification. The explanation consists of factual and counterfactual rules revealing...

TRIPLEX is an explainability package for Transformer-based models fine-tuned on Natural Language Inference, Semantic Text Similarity, or Text Classification tasks. TRIPLEX...

A Python library to explain machine learning models by hierarchically aggregating single explanations of its predictions. Explanations are provided as decision rules...