• Sharad S. Jagtap

for analysis of signals and its processing it is required to sort data for robust classification. Proposed paper represents classification of EEG signals using three different techniques. Brain waves of epilepsy are the data for this classification. Epilepsy is one type of neurological disorder which causes abnormal neuronal activity. To identify the non linearity present in the data, Proper analysis is done. An EEG record of twenty patients is analyzed. The power spectral density is determined which is further used for disturbance reduction. The results show that SVM Classifier gives better results for classification of epileptic data as compare to KNN and K-means algorithm.

KNN, SVM, Epilepsy data, EEG.

"A Review on Epileptic Signals Analysis using KNN, K-means clustering and SVM Classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.173-175, January-2019, Available :http://www.jetir.org/papers/JETIRW006038.pdf

"A Review on Epileptic Signals Analysis using KNN, K-means clustering and SVM Classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp173-175, January-2019, Available at : http://www.jetir.org/papers/JETIRW006038.pdf