A multiclass SVM trained on EEG features from a public 12-subject dataset reported 92.9% person-identification accuracy, though the evaluation is compromised by overlapping test windows and parameter tuning on the same data.
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Support Vector Machine for Person Classification Using the EEG Signals
A multiclass SVM trained on EEG features from a public 12-subject dataset reported 92.9% person-identification accuracy, though the evaluation is compromised by overlapping test windows and parameter tuning on the same data.