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Performance Analysis of Classifier in Detecting Epileptic Seizure Based on Discrete Wavelet Transform

The paper demonstrates epileptic seizure detection by analyzing the performance of k-nearest neighbor (KNN) classification technique. The writer applies this classifier on epileptic patient seizure datasets based on extracted feature from Discrete Wavelet Transform (DWT). The research indicates that DWT improved the KNN classifier with average 93.42% on the datasets and less chance of false detection rate for epileptic seizure datasets.