The Necessity of Leave One Subject Out (LOSO) Cross Validation for EEG Disease DiagnosisHigh variability between individual subjects and recording sessions is a known fact about scalp recorded EEG signal. While some do, the majority of the EEG based machine learning studies do not attempt to ...
We address this question using leave-one-subject- out cross-validation (LOSO CV) to simulate inclusion of test data from future subjects. Investigations are based on EEG of 70 subjects across four studies conducted in our driving simulation lab. 9,297 MS and 10,264 counter-examples of ...
The Necessity of Leave One Subject Out (LOSO) Cross Validation for EEG Disease Diagnosis. In: Mahmud, M., Kaiser, M.S., Vassanelli, S., Dai, Q., Zhong, N. (eds) Brain Informatics. BI 2021. Lecture Notes in Computer Science(), vol 12960. Springer, Cham. https://doi.org/10.1007...
We address this question using leave-one-subject- out cross-validation (LOSO CV) to simulate inclusion of test data from future subjects. Investigations are based on EEG of 70 subjects across four studies conducted in our driving simulation lab. 9,297 MS and 10,264 counter-examples of ...