Lasso (Least Absolute Shrinkage and Selection Operator) applies L1 regularization, which drives some coefficients exactly to zero. This means Lasso simultaneously trains a model and selects features.Documentation Index
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Configuration
| Parameter | Description | Default |
|---|---|---|
| Alpha | Regularization strength. Higher = more coefficients pushed to zero. | 1.0 |
| Fit Intercept | Whether to include a bias/intercept term. | true |
| Max Iterations | Maximum solver iterations. | 1000 |
| Random State | Seed for reproducibility. | 42 |
Input / Output
| Type | |
|---|---|
| Input | X Train + Y Train |
| Output | Trained Model |