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Related Questions
- Can ensemble methods like bagging or boosting improve the robustness of a model to noisy labels?
- How do ensemble methods handle label noise, and what are the potential benefits of using them in this context?
- Can you explain the concept of 'majority voting' in ensemble methods and how it relates to reducing label noise?
- What are some common techniques used in ensemble methods to detect and correct label noise?
- How do the performance metrics of a model change when label noise is introduced, and how can ensemble methods mitigate this effect?
- Can you provide an example of a scenario where ensemble methods are particularly effective in reducing label noise?
- What are some challenges associated with using ensemble methods to address label noise, and how can they be overcome?
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