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Related Questions
- What is the primary goal of passive learning in model training, and how does it differ from active learning?
- Can you explain the key differences between the two approaches in terms of data labeling and annotator involvement?
- How does active learning affect the overall performance of a model, particularly in terms of accuracy and generalization?
- What are some common applications of passive learning in real-world scenarios, and why are they effective?
- In what situations would an active learning approach be more beneficial than a passive learning approach?
- How do the computational resources required for passive and active learning compare, and what are the implications for large-scale model training?
- Can you provide examples of industries or domains where passive learning is more commonly used, and why it is well-suited for those areas?
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