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Related Questions
- How does active learning select the most informative samples for model training to reduce overfitting?
- Can you explain the trade-off between exploration and exploitation in active learning to balance model generalization and accuracy?
- What are some common metrics used to measure the uncertainty of model predictions in active learning?
- How does active learning compare to traditional supervised learning in terms of reducing overfitting and improving model generalization?
- Can you discuss the role of human annotators in active learning and how their input affects the model's performance?
- What are some strategies for handling class imbalance in active learning to improve model fairness and accuracy?
- Can you explain how active learning can be used to reduce overfitting in deep learning models, particularly those with large neural networks?
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