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Related Questions
- What are the advantages and disadvantages of oversampling in dealing with imbalanced datasets?
- How does SMOTE (Synthetic Minority Over-sampling Technique) work and what are its limitations?
- Can you explain the concept of ensemble methods, such as bagging and boosting, for handling imbalanced datasets?
- What is the difference between undersampling and oversampling, and when would you choose each method?
- Can you discuss the use of cost-sensitive learning and its impact on the performance of machine learning models with imbalanced datasets?
- What are some techniques for handling class imbalance in regression problems, and how do they differ from those used in classification problems?
- How does the choice of evaluation metric affect the performance of machine learning models on imbalanced datasets, and what are some alternatives to accuracy?
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