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Found 2 papers, 1 papers with code
CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions
Our Contrastive Entropy-based explanation method, CEnt, approximates a model locally by a decision tree to compute entropy information of different feature splits.
An Explainable Model for EEG Seizure Detection based on Connectivity Features
Also, we were able to explain the relevance of each feature across all patients.
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