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Related Questions
- Can you explain the concept of diversity in machine learning datasets?
- How does the use of synthetic negative examples impact the representativeness of a dataset?
- Can over-reliance on synthetic data lead to biased models?
- What are some potential consequences of lacking diversity in a training dataset?
- How can data augmentation techniques be used to increase diversity in a dataset?
- Can you discuss the importance of data quality in maintaining diversity in a dataset?
- What is the potential impact of over-sampling synthetic examples on model performance and generalizability?
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