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Related Questions
- Does a smaller value of k in k-fold cross-validation result in a more conservative estimate of out-of-sample error?
- Can k-fold cross-validation be used to estimate the effect of overfitting when the model is complex and has many parameters?
- How does the number of folds in k-fold cross-validation impact the efficiency of the model selection process?
- Is there a relationship between the value of k and the accuracy of the model on the training set?
- Can k-fold cross-validation be used to compare the performance of different machine learning algorithms?
- How does the choice of k affect the variance of the estimated out-of-sample error in k-fold cross-validation?
- Can the number of folds in k-fold cross-validation be set to a value that optimizes the trade-off between bias and variance?
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