Research Article
Adaptive Particle Swarm Optimization Algorithm Ensemble Model Applied to Classification of Unbalanced Data
Table 4
Parameters of all algorithms in the experiments.
| Algorithm | Parameters |
| DT | Min_samples_leaf = 6 | Max_depth = 8 | Min_samples_split = 2 | Gamma = 0.0 | Max_leaf_nodes = 4 |
| LR | No parameters specified |
| MLP | Epoch = 1000 | Learning_rate = 0.01 | Hidden_units = 5 |
| SVM | Kernel: RBF | C = 32 | Gamma = 0.1 |
| RF | N_estimators = 100 | Max_features = 12 | Max_depth = 400 | Min_samples_split = 2 | Min_samples_leaf = 1 |
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