Epilepsy is a serious brain illness that is an endemic neurological disorder all over the world. It is a clinical result that occurs with abnormal neurological electrical discharging of brain. Epileptic seizures represent the most common positive signs and symptoms of brain disturbance, and epilepsy is one of the most common primary brain disorders . Vascular causes, traumatic causes, infections and brain abscesses, brain tumors, nutritional deficiencies, pyridoxine deficiency, calcium metabolism disorders are lead causes for epilepsy. For in diagnosing epilepsy, research is needed for better understanding of mechanisms causing epileptic disorders. The evaluation and treatment of neurophysiologic disorders are diagnosed with the electroencephalogram (EEG). EEG is crucial for accurate classification of different forms of epilepsy .

The aim of this Research is to contribute to the diagnosis of epilepsy by taking advantage of the engineering. So, for diagnosing of epileptic seizures from EEG signals are transformed discrete wavelet and auto regressive models. After these transformations, extract data is applied input for Back-propagation, KNN, Linear SVM, SVM, ANN ,Logistic Regression.