A Framework on Performance Analysis of Mathematical Model-Based Classifiers in Detection of Epileptic Seizure from EEG Signals with Efficient Feature Selection

<table class="table-group" id="tab6"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left" rowspan="2">Confusion matrix</td><td class="align_center" rowspan="2">Class</td><td class="align_center" colspan="2">Predicted</td></tr><tr class="thead"><td class="align_center">Normal</td><td class="align_center">Seizure</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left" rowspan="2">Actual</td><td class="align_center">Normal</td><td class="align_center">TN</td><td class="align_center">FP</td></tr><tr><td class="align_center">Seizure</td><td class="align_center">FN</td><td class="align_center">TP</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Confusion matrix for the seizure detection.</div>

Journal of Healthcare Engineering

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Table 6

Table 6: A Framework on Performance Analysis of Mathematical Model-Based Classifiers in Detection of Epileptic Seizure from EEG Signals with Efficient Feature Selection 

Table 6 | A Framework on Performance Analysis of Mathematical Model-Based Classifiers in Detection of Epileptic Seizure from EEG Signals with Efficient Feature Selection 