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Related Questions
- How do active learning and human-in-the-loop methods differ in terms of the level of human involvement in the machine learning process?
- What are the key benefits of using active learning for improving dataset quality, and how does it compare to traditional supervised learning?
- Can you provide examples of real-world applications where active learning has been successfully used to improve dataset quality?
- How can human-in-the-loop methods be used to address the issue of class imbalance in datasets, and what are the potential drawbacks of these approaches?
- What are some common metrics used to evaluate the effectiveness of active learning and human-in-the-loop methods in improving dataset quality?
- How can active learning and human-in-the-loop methods be combined to create a more robust and efficient machine learning pipeline?
- What are some challenges and limitations of using active learning and human-in-the-loop methods, and how can they be addressed in practical applications?
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