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...
| Autor principal: | |
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| Outros Autores: | , , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2013
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10316/27431 |
| País: | Portugal |
| Oai: | oai:estudogeral.sib.uc.pt:10316/27431 |