Random Forest Regressor averages the predictions of many decision trees trained on random data subsets. It handles non-linear relationships well and is robust to noisy data.Documentation Index
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Configuration
| Parameter | Description | Default |
|---|---|---|
| N Estimators | Number of trees in the forest. | 100 |
| Max Depth | Maximum depth of each tree. Leave empty for unlimited. | None |
| Min Samples Split | Minimum samples to split a node. | 2 |
| Min Samples Leaf | Minimum samples in a leaf node. | 1 |
| Random State | Seed for reproducibility. | 42 |
Input / Output
| Type | |
|---|---|
| Input | X Train + Y Train |
| Output | Trained Model |