Table 7 The grid search-yielded optimal results for the hyperparameters for the C-3 mode
From: A hybrid deep CNN model for brain tumor image multi-classification
Hyperparameters | Changes in Parameter Values | Maximal Value |
|---|---|---|
Layers of maximum pooling and CNN | (1, 2, 3, 4) | 3 |
Number of layers that are completely connected | (1, 2, 3, 4) | 2 |
Total number of filters | (8, 16, 24, 32, 48, 64, 96, 128, 256) | 64, 96, 128 |
Intensity of filtration | (3, 4, 5, 6, 7) | 6, 6, 4 |
Role of activation | (ReLU, ELU, Leaky ReLU) | ReLU |
Size of minibatch | (4, 6, 16, 24, 32, 64) | 32 |
Rate of change | (0.78, 0.77, 0.95, 0.96) | 0.95 |
Rate of learning | (0.0002, 0.00043, 0.002, 0.004) | 0.004 |
R2—regularization | (0.0002, 0.00043, 0.002, 0.004) | 0.002 |