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A Study of Epileptic Seizure Detection using Machine Learning Algorithms

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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.identifier.uri http://hdl.handle.net/1920/12869
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. en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject Epileptic Seizure detection en_US
dc.subject machine learning en_US
dc.title A Study of Epileptic Seizure Detection using Machine Learning Algorithms en_US
dc.type Article en_US


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