Table 2.
The classification accuracy of 120 EEG samples of familiar logos (class 1) and unfamiliar logos (class 2) are obtained using leave-one-out cross validation in a SNN model.
| The proposed SNN-based methodology | ||||||
|---|---|---|---|---|---|---|
| Predicted | Familiar Stimuli (C1) | Unfamiliar Stimuli (C2) | Total accuracy % | F-Score % | Sensitivity % | Specificity % |
| Real | ||||||
| Familiar Stimuli (class C1) | 52 | 8 | 83.00 | 84.00 | 84.00 | 86.00 |
| Unfamiliar Stimuli (class C2) | 10 | 50 | ||||
In the confusion table, the rows are the real values and the columns are the predicted values.