Table 2 Classification precision and recall calculated by the classifiers using combination of all features at different frequency bands
From: EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features
| Â | Alpha-band | Beta-band | Delta-band | Theta-band | Gamma-band |
|---|---|---|---|---|---|
Precision, Recall | |||||
 SVM (Linear) | 0.615, 0.528 | 0.613, 0.555 | 0.674, 0.523 | 0.685, 0.615 | 0.751, 0.664 |
 SVM (RBF) | 0.622, 0.547 | 0.741, 0.593 | 0.618, 0.554 | 0.613, 0.444 | 0.783, 0.688 |
 Gradient Boosting | 0.577, 0.513 | 0.611, 0.512 | 0.667, 0.499 | 0.569, 0.466 | 0.781, 0.688 |
 Decision Tree | 0.574, 0.447 | 0.713, 0.716 | 0.685, 0.532 | 0.601, 0.514 | 0.688, 0.577 |
 Random Forest | 0.583, 0.502 | 0.694, 0.532 | 0.587, 0.495 | 0.604, 0.488 | 0.766, 0.644 |