Can you explain the differences between Leave-One-Out Cross-Validation (LOOCV) and k-fold Cross-Validation?
- LOOCV is a specific case of k-fold with k equal to the number of observations
- LOOCV is a specific case of k-fold with k=1
- LOOCV is faster than k-fold
- LOOCV uses k folds, while k-fold uses LOOCV folds
Leave-One-Out Cross-Validation (LOOCV) is a specific case of k-fold Cross-Validation, where k equals the number of observations in the dataset. In LOOCV, each observation is used as a validation set exactly once, whereas in k-fold, the dataset is divided into k equally-sized folds. LOOCV is computationally more intensive but may provide a less biased estimate.
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