Detection of Epileptic Seizure from EEG Signal Data by Employing Machine Learning Algorithms with Hyperparameter Optimization

Epileptic seizure refers to a brief occurrence of signs in the brain caused by abnormally high or synchronized neuronal activity. With the utilization of EEG signal, the epileptic seizure can be identified. However, incorporating machine learning classifiers with this EEG data can significantly contribute in detecting epileptic seizure in an automated manner. In this paper, nine machine learning algorithms have been studied and models have been constructed by utilizing UCI Epileptic Seizure dataset. The performances of the ML models are noted and detailed comparative analysis has been exhibited for both hyperparameter tuning and without hyperparameter tuning. Random search cross validation has been used for tuning the hyperparameters. Satisfactory results have been witnessed in terms of different performance metrics like accuracy,…