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Related Questions
- What is the relationship between the number of folds in k-fold cross-validation and the variance of the model performance estimates?
- How does increasing the number of folds affect the bias-variance tradeoff in model performance estimates?
- Can you explain the concept of overfitting and how it relates to the number of folds in k-fold cross-validation?
- What is the optimal number of folds for a given dataset, and how can it be determined?
- How does the number of folds impact the generalizability of model performance estimates to new, unseen data?
- Can you provide examples of how different numbers of folds can affect the model performance estimates in a specific scenario?
- How does the choice of fold size (e.g., 5-fold, 10-fold) impact the variance of the model performance estimates?
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