Table 2 Model hyperparameters and optimization methods.
Model | Hyperparameter | Value/Range | Optimization Method |
|---|---|---|---|
ET | n_estimators | 200 | Bayesian Search |
max_features | sqrt (square root of total features) | ||
max_depth | 10 | ||
RF | n_estimators | 150 | Grid Search |
criterion | Gini impurity | ||
max_depth | 12 | ||
DT | max_depth | 8 | Manual Tuning |
min_samples_split | 5 | ||
SVM | kernel | Radial Basis Function (RBF) | Cross-Validation |
C (regularization) | 1.0 | ||
gamma | scale | ||
LSTM | hidden_units | 64 | Random Search |
dropout_rate | 0.2 | ||
epochs | 100 |
