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Related Questions
- What are the key strategies for implementing active learning to reduce the need for large datasets?
- How can uncertainty sampling and query-by-committee methods be used to select the most informative data points for labeling?
- What are the benefits of using active learning for model performance improvement, and how does it compare to traditional supervised learning?
- Can you explain the concept of 'pool-based' and 'stream-based' active learning, and when to use each approach?
- How can active learning be used to improve model performance on imbalanced datasets?
- What are some common challenges and limitations of active learning, and how can they be addressed?
- Can you discuss the role of human-in-the-loop (HITL) and human-annotator interfaces in active learning, and their impact on model performance?
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