Table 5 Hyperparameter description.
From: An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification
Hyperparameter | Value | Description |
|---|---|---|
Optimizer | Adam | Optimizer used for the training process. |
Loss function | Categorical Cross-Entropy | Loss function to evaluate the model’s predictions against the true labels. |
Performance metric | Accuracy | Metric used to assess the model’s performance during training. |
Learning rate | Initial or Adaptive | Starting learning rate, adjusted by callbacks during training. |
ReduceLROnPlateau factor | 0.2 | Factor by which the learning rate is reduced when validation loss plateaus. |
ReduceLROnPlateau patience | 5 | Number of epochs with no improvement after which learning rate will be reduced. |
ReduceLROnPlateau Min LR | 0.001 | Minimum learning rate after which it will not reduce further. |
EarlyStopping patience | 10 | Number of epochs with no improvement after which training will be stopped. |
EarlyStopping best weights | True | Option to restore the best weights from the training process to prevent overfitting. |
