Table 6 Accuracies (in %) while evaluating using 5-fold cross validation scheme.
From: TOPSIS aided ensemble of CNN models for screening COVID-19 in chest X-ray images
Fold | Dataset-1 | Dataset-2 | ||||||
|---|---|---|---|---|---|---|---|---|
Classifier 1 | Classifier 2 | Classifier 3 | Ensemble | Classifier 1 | Classifier 2 | Classifier 3 | Ensemble | |
Fold1 | 96.09 | 96.42 | 95.84 | 96.58 | 96.43 | 96.46 | 95.84 | 96.83 |
Fold2 | 97.79 | 97.74 | 97.55 | 98.12 | 95.64 | 95.60 | 95.80 | 96.27 |
Fold3 | 97.02 | 96.58 | 97.72 | 97.80 | 97.46 | 97.52 | 97.72 | 97.85 |
Fold4 | 97.71 | 97.79 | 97.71 | 98.24 | 96.73 | 96.86 | 96.93 | 96.96 |
Fold5 | 96.57 | 96.74 | 96.82 | 97.06 | 95.59 | 95.95 | 95.16 | 96.13 |
Maximum | 97.79 | 97.79 | 97.72 | 98.24 | 97.46 | 97.52 | 97.72 | 97.85 |
Minimum | 96.09 | 96.42 | 95.84 | 96.58 | 95.59 | 95.60 | 95.16 | 96.13 |
Average | 97.04 | 97.05 | 97.13 | 97.56 | 96.37 | 96.48 | 96.29 | 96.80 |
SD | 0.65 | 0.59 | 0.72 | 0.64 | 0.70 | 0.67 | 0.91 | 0.61 |
