In _______-fold Cross-Validation, each observation is left out once as the validation set, providing a robust estimate of model performance.
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- 2
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- n
In 1-fold Cross-Validation, also known as Leave-One-Out Cross-Validation (LOOCV), each observation is left out once as the validation set. It provides a robust estimate of model performance but can be computationally expensive as it requires fitting the model n times, where n is the number of observations in the dataset.
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