A Study of Epileptic Seizure Detection using Machine Learning Algorithms
| dc.contributor.author | Kamaraju, Rajeev | |
| dc.contributor.author | Peixoto, Nathalia | |
| dc.date.accessioned | 2022-05-16T18:01:54Z | |
| dc.date.available | 2022-05-16T18:01:54Z | |
| dc.date.issued | 2022-05 | |
| dc.description.abstract | This paper focuses on studying epileptic seizure detection using machine learning algorithms. Algorithms like Naïve Bayes, Logistic Regression, Stochastic Gradient Descent, KNearest Neighbour, Decision trees and random forests have been studied. For each of the classifier, many performance metrics have been computed and Area Under Curve (AUC) has been chosen as our performance metric. The paper also introduces the possibility of detecting epileptic seizures using Neural networks. | |
| dc.identifier.uri | https://hdl.handle.net/1920/12869 | |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/us/ | |
| dc.subject | Epileptic Seizure detection | |
| dc.subject | Machine learning | |
| dc.title | A Study of Epileptic Seizure Detection using Machine Learning Algorithms | |
| dc.type | Article |