The method where certain portions of a dataset are intentionally left out of training to validate the model's performance is called __________.
- Cross-Validation
- Overfitting
- Regularization
- Underfitting
The method where certain portions of a dataset are intentionally left out of training to validate the model's performance is called "Cross-Validation." Cross-validation helps assess a model's generalization and performance on unseen data.
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