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Related Questions
- What strategies can be employed to prevent overfitting in large datasets?
- How can data augmentation techniques be used to increase the size of a dataset without introducing data leakage?
- What are some methods for splitting a dataset into training and testing sets to minimize data leakage?
- Can you explain the concept of data leakage and how it can occur in machine learning model development?
- How can data preprocessing techniques, such as normalization and feature scaling, impact the risk of overfitting?
- What role does cross-validation play in preventing overfitting and ensuring model generalizability?
- How can you use techniques like regularization and early stopping to prevent overfitting in large datasets?
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