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Related Questions
- What are some common data preprocessing techniques used to detect and mitigate bias in training data?
- How can data normalization and feature scaling affect the presence of bias in machine learning models?
- What role can data augmentation play in reducing bias in image classification tasks?
- Can you explain the concept of representative sampling and how it can be used to collect unbiased data?
- How do data preprocessing techniques such as handling missing values and outliers impact the fairness of machine learning models?
- What is the difference between bias and variance in the context of machine learning, and how can data preprocessing techniques mitigate them?
- Can you discuss the importance of data validation and verification in ensuring that training data is free from bias and errors?
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