Table 2 Hyperparameters tunned for machine learning models.
From: An intelligent life prediction approach employing machine learning models for the power transformers
Model | Hyperparameters Tuned | Values Tested | Selection Criteria |
|---|---|---|---|
Linear Regression | None | N/A | Minimize MSE |
Polynomial Regression | Degree Fixed | 2 | Minimize MSE |
Random Forest Regressor | Number of Trees, Maximum Depth | Trees: 100; Depth: 5, 10, None | Maximize R2 |
Logistic Regression | Regularization Strength (C) | 0.1, 1, 10 | Maximize Accuracy |
SVM (RBF Kernel) | Regularization (C), Kernel Coefficient (gamma) | C: 1, 10, 1000; gamma: 0.01, 0.1, ‘Scale’ | Maximize Accuracy |
Random Forest Classifier | Number of Trees, Maximum Depth | Trees: 100; Depth: 5, 10, None | Maximize Accuracy |
