Ridge and Lasso are techniques used for ________ to prevent overfitting.
- Data Preprocessing
- Feature Engineering
- Hyperparameter Tuning
- Regularization
Ridge and Lasso are both regularization techniques used to prevent overfitting in machine learning. Regularization adds penalty terms to the model's loss function to discourage excessive complexity and make the model generalize better.
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