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Related Questions
- What are some common techniques used for data augmentation in the presence of missing values in a dataset?
- How does data augmentation help to improve the performance of machine learning models when dealing with missing data?
- Can you provide examples of data augmentation techniques that can be used to handle missing values in categorical and numerical data?
- What are the challenges associated with applying data augmentation to missing values in high-dimensional datasets?
- How does data augmentation compare to other methods for handling missing values, such as imputation and interpolation?
- Can data augmentation be used to handle missing values in time series data?
- What are the trade-offs between data augmentation and other methods for handling missing values, such as ignoring or deleting missing values?
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