TABLE 6.
Seventeen traditional machine learning algorithms used in the TML17 method
| Algorithm | Description |
|---|---|
| RF | Random Forest regressor (12) |
| ET | Extra Trees regressor (29) |
| LightGBM | Light Gradient Boosting Machine (30) |
| GBR | Gradient Boosting Regressor (9) |
| KNN | K Neighbors regressor (31) |
| DT | Decision Tree regressor (32) |
| BR | Bayesian Ridge (33) |
| LR | Linear Regressor (34) |
| Ridge | Ridge Regressor (10) |
| Huber | Huber regressor (35) |
| Ada | AdaBoost regressor (36) |
| OMP | Orthogonal Matching Pursuit (37) |
| PAR | Passive Aggressive Regressor (38) |
| LAR | Least Angle Regressor (39) |
| Lasso | Lasso Regressor (11) |
| EN | Elastic Net (8) |
| LLAR | Lasso Least Angle Regressor (40) |