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Related Questions
- What are the key metrics to measure the effectiveness of sampling strategies in active learning for sentiment analysis?
- How do you compare the performance of different sampling strategies, such as uncertainty sampling, diversity sampling, and density-based sampling, in sentiment analysis?
- What are the trade-offs between different sampling strategies, and how do they impact the overall performance of the active learning system?
- How do you evaluate the impact of sampling strategy on the model's ability to generalize to new, unseen data in sentiment analysis?
- What are some common pitfalls to avoid when evaluating the effectiveness of sampling strategies in active learning for sentiment analysis?
- Can you provide examples of how to implement and compare different sampling strategies in a sentiment analysis pipeline using popular machine learning libraries?
- How do you balance the exploration-exploitation trade-off in active learning for sentiment analysis, and what are the implications for sampling strategy selection?
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