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Related Questions
- What is uncertainty sampling and how does it relate to active learning in machine learning?
- How does uncertainty sampling select examples for the model to learn from, and what are the benefits of this approach?
- What are the different methods used for uncertainty estimation in uncertainty sampling, and how do they impact the selection of examples?
- How does uncertainty sampling handle cases where the model is uncertain about the class label, but certain about the class probability?
- Can you explain the difference between uncertainty sampling and other active learning strategies, such as query-by-committee?
- How does the choice of uncertainty estimation method affect the performance of the model in uncertainty sampling?
- What are some common challenges and limitations of uncertainty sampling, and how can they be addressed?
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