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Related Questions
- Does a larger value of k in k-fold cross-validation result in a more conservative estimate of out-of-sample error?
- What is the relationship between the value of k in k-fold cross-validation and the bias-variance tradeoff?
- How does the choice of k in k-fold cross-validation affect the generalizability of a machine learning model?
- Can a smaller value of k in k-fold cross-validation lead to overfitting?
- What is the effect of k-fold cross-validation on the variance of the model's performance estimate?
- Is k-fold cross-validation more effective for estimating out-of-sample error when k is set to a small value?
- What are the implications of using a small value of k in k-fold cross-validation for model selection and hyperparameter tuning?
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