You are working with a small dataset, and your model is prone to overfitting. What techniques could you employ to mitigate this issue?
- Add complexity
- Reduce complexity
- Use L1 regularization
- Use cross-validation and data augmentation
Using techniques like cross-validation and data augmentation can mitigate overfitting when working with a small dataset. Cross-validation ensures that the model is evaluated on unseen data, and data augmentation artificially increases the size of the dataset, reducing the risk of overfitting.
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