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Generalization Failure in EEG-based Machine Learning Models

Machine learning models for motor imagery classification using EEG brain signals fail to generalize across different datasets. This limitation hinders the development of reliable and robust models for real-world applications. The issue is attributed to flawed evaluation methods, including subject leakage and weak baselines. There is a need for more rigorous evaluation and development of models that can generalize well across different datasets.

Computing & Technology, Computer Science, Machine Learning