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Related Questions
- What is the difference between cross-validation and traditional training and testing, and how does it help prevent overfitting?
- How does the number of folds in cross-validation impact the model's performance and generalizability?
- Can you explain the concept of bias-variance tradeoff in cross-validation, and how to find the optimal model size?
- What is the purpose of shuffling the data in cross-validation, and how does it affect the model's performance?
- How does cross-validation handle class imbalance issues in binary classification problems?
- Can you compare the results of different cross-validation strategies, such as K-fold, Stratified K-fold, and Repeated K-fold?
- What are the pros and cons of using grid search and random search for hyperparameter tuning with cross-validation?
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