Table 13 The result of tenfold cross-validation of VGGNet for classification accuracy
From: WBC image classification and generative models based on convolutional neural network
| Â | NE. (%) | EO. (%) | BA. (%) | LY. (%) | MO. (%) |
|---|---|---|---|---|---|
Fold-0 | 100 | 2 | 21 | 0 | 32 |
Fold-1 | 100 | 0 | 0 | 0 | 75 |
Fold-2 | 100 | 3 | 31 | 0 | 57 |
Fold-3 | 100 | 87 | 47 | 16 | 12 |
Fold-4 | 100 | 84 | 81 | 4 | 74 |
Fold-5 | 100 | 33 | 0 | 20 | 89 |
Fold-6 | 100 | 0 | 7 | 40 | 68 |
Fold-7 | 100 | 44 | 2 | 1 | 12 |
Fold-8 | 100 | 62 | 16 | 0 | 51 |
Fold-9 | 100 | 64 | 21 | 8 | 57 |
Avr. Acc. | 100 | 38 | 23 | 9 | 53 |