Table 14 Evaluation of dropout, batch normalization and learning rate for model2 with last unfrozen Convlayer
From: Deep convolutional neural network based medical image classification for disease diagnosis
Learning rate | Decay rate | Training image | Dropout1 | Dropout2 | BNlayer | VGG16 |
|---|---|---|---|---|---|---|
0.001 | 0.9 | 20,000 | 0.5 | NA | No | 0.871 |
0.001 | 0.5 | 5323 | 0.5 | NA | No | 0.873 |
0.001 | 0.9 | 20,000 | 0.7 | 0.5 | Yes | 0.875 |
0.0009 | 0.8 | 5323 | 0.5 | NA | No | 0.9 |
0.0005 | 0.5 | 10,000 | 0.5 | NA | No | 0.902 |
0.001 | 0.9 | 20,000 | 0.7 | NA | Yes | 0.906 |
0.001 | 0.9 | 5323 | 0.5 | NA | Yes | 0.912 |
0.001 | 0.9 | 5323 | 0.7 | 0.5 | Yes | 0.916 |
0.001 | 0.9 | 5323 | 0.5 | NA | No | 0.924 |