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Related Questions
- How does active learning help identify the most informative samples for labeling and reduce the need for human annotation?
- What are the key differences between active learning and traditional machine learning approaches in terms of data selection and model updating?
- Can you explain the concept of uncertainty sampling in active learning and how it is used to select the most informative samples?
- How does active learning enable the model to adapt to changing data distributions and improve its performance over time?
- What are the potential challenges and limitations of active learning in refining prompts and improving model performance?
- How can I integrate active learning into my existing workflow to improve the efficiency and effectiveness of my model's performance?
- What are some common metrics and evaluation techniques used to assess the performance of active learning algorithms and their impact on model refinement?
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