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Related Questions
- What are the key differences between uncertainty sampling and other active learning methods like query-by-committee and expected model change?
- How do the limitations of uncertainty sampling, such as overestimation of uncertainty, impact its integration with other active learning methods?
- Can you explain the trade-offs between using uncertainty sampling alone versus combining it with other active learning methods?
- How does uncertainty sampling interact with methods that use diversity-based selection, such as co-training and core-set selection?
- What are some strategies for mitigating the curse of dimensionality when combining uncertainty sampling with other active learning methods?
- How can the uncertainty estimates from uncertainty sampling be combined with other uncertainty estimates from other active learning methods?
- What are some common pitfalls to avoid when implementing uncertainty sampling with other active learning methods, such as over-sampling or under-sampling certain classes?
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