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Related Questions
- What are the different types of cross-validation techniques, and how do they differ in their approach to evaluating model performance?
- How does k-fold cross-validation work, and what are its advantages and disadvantages compared to other techniques?
- Can you explain the concept of hyperparameter tuning, and how does cross-validation play a crucial role in this process?
- How is cross-validation used to prevent overfitting and ensure that a model generalizes well to unseen data?
- What are some common metrics used to evaluate model performance during cross-validation, and how do they help in selecting the best hyperparameters?
- Can you describe a scenario where cross-validation is particularly useful, such as when dealing with imbalanced datasets or high-dimensional data?
- How does cross-validation interact with other techniques, such as regularization and ensemble methods, to improve model performance and robustness?
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