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Ranges and optimal value of hyperparameters of the surrogate models.
| ML Model | Hyperparameter | Range | Optimal value |
|---|---|---|---|
| Artificial Neural Network (ANN) | No. of neurons in the hidden layer | 1–10 | 9 |
| Learning rate | 0.001–1 | 0.01 | |
| Activation function | tanh, relu | relu | |
| Batch Size | 16, 32, 64, 128 | 16 | |
| L1 Regularization factors | 0.001–0.1 | 0.01 | |
| Support Vector Regression (SVR) | Kernel Type | linear, poly, rbf | rbf |
| Regularization parameter C) | 0.1–1000 | 10 | |
| Kernel Coefficient (Gamma) | 0.001–10 | 1 | |
| Epsilon | 0.01–1 | 0.1 |
