Preprocessing effects of 22 linear univariate features on the performance of seizure prediction methods

Combining multiple linear univariate features in one feature space and classifying the feature space using machine learning methods could predict epileptic seizures in patients suffering from refractory epilepsy. For each patient, a set of twenty-two linear univariate features were extracted from 6...

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Bibliographic Details
Main Author: Rasekhi, Jalil (author)
Other Authors: Mollaei, Mohammad Reza Karami (author), Bandarabadi, Mojtaba (author), Teixeira, Cesar A. (author), Dourado, António (author)
Format: article
Language:eng
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10316/27431
Country:Portugal
Oai:oai:estudogeral.sib.uc.pt:10316/27431