Comparative Analysis of Classifiers for Prediction of Epileptic Seizures

  • Shehzaib Shafique Biomedical Engineering Department, Riphah International University, Islamabad, 44000, Pakistan
  • Saba Sarfraz Department of Biomedical Engineering, Riphah International University, I-14, Islamabad, Pakistan
  • Usman Qamar Shaikh Department of Biomedical Engineering, Riphah International University, I-14, Islamabad, Pakistan
  • Aamash Nadeem Computing Engineering and Built Environment Department, Ulster University, Belfast, BT15 1ED, United Kingdom
  • Zia Ur Rehman Department of Biomedical Engineering, Riphah International University, I-14, Islamabad, Pakistan
DOI: https://doi.org/10.51846/vol3iss03pp84-88
Keywords: Classifiers, Epilepsy, Epileptic Seizures, Epileptic Seizures Detection, Machine Learning Algorithms, KNN, Naive Bayes, SVM

Abstract

Epilepsy is a neurological disease in which people suffer from seizure attack and lose the normal function of brain. Almost 50 million people have epilepsy in the world due to which it has become the most common neurological disease. Early prediction of epilepsy helps patients to avoid epilepsy and live normal life. Many studies have been conducted for the early prediction of epilepsy. However, selection of the most appropriate classifier has always been a question that needs to be resolved. In this study, we are using six classifiers of machine learning which are KNN, Naïve Bayes, Linear Classification Model, Discriminant Analysis Model, Support Vector Machine and Decision Tree, to find the best classifier for the prediction of epileptic seizures, in term of accuracy. Dataset from “Kaggle” was used. Preprocessing and cross-validation of the data was carried out for training and testing of classifiers. The results depict that Naive Bayes classifier has a better average accuracy of 95.739% as compared to other classifiers. The future work of this study is to implement the suggested model in real time, so that the workload of medical members could be reduced.

Published
2020-12-27
How to Cite
[1]
S. Shafique, S. Sarfraz, U. Shaikh, A. Nadeem, and Z. Rehman, “Comparative Analysis of Classifiers for Prediction of Epileptic Seizures”, PakJET, vol. 3, no. 03, pp. 84-88, Dec. 2020.
Issue
Vol 3 No 03 (2020): Pakistan Journal of Engineering and Technology
Section
Research Articles

Copyright (c) 2020 Pakistan Journal of Engineering and Technology

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