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TriPat‑XFE: a triangle pattern‑based explainable feature engineering framework for EEG classification
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DOI：10.1016/j.neuroscience.2025.12.004.png)
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Abstract
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• TriPat introduces a linear triangle-based transformer for EEG features • TriPat-XFE achieves 100% accuracy on Stress and Psychosis datasets. • DLob provides symbolic EEG explanations with connectome diagrams. • CWINCA and tkNN enhance feature selection and classification stability. • TriPat-XFE outperforms SOTA with low cost and high interpretability.
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