Gradient Boosting Regressor builds trees iteratively, where each tree corrects the residual errors of the current ensemble. It typically achieves the best accuracy among regression models in the toolbox.Documentation Index
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Configuration
| Parameter | Description | Default |
|---|---|---|
| N Estimators | Number of boosting stages. | 100 |
| Learning Rate | Contribution of each tree. Lower = more conservative, more trees needed. | 0.1 |
| Max Depth | Maximum depth of individual trees. | 3 |
| Subsample | Fraction of samples used per tree. Below 1.0 adds stochasticity. | 1.0 |
| Random State | Seed for reproducibility. | 42 |
Input / Output
| Type | |
|---|---|
| Input | X Train + Y Train |
| Output | Trained Model |