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Cross Validation
- Cross-validation is a technique that involves dividing the data into training and test parts.
- The training part is further divided into subtrain and validation parts for model building.
- The prediction error obtained through cross-validation tends to be an overestimate of the true prediction error.
- Leave-one-out cross-validation is commonly used in linear regression as it does not require rebuilding the models.
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