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Related Questions
- What is the primary purpose of SMOTE in machine learning, and how does it address class imbalance?
- How does SMOTE create synthetic samples, and what are the benefits of using this technique?
- Can you explain the difference between SMOTE and other oversampling techniques, such as random oversampling?
- What are the common applications of SMOTE in real-world scenarios, and how does it improve model performance?
- How can SMOTE be used in combination with other techniques, such as undersampling or ensemble methods, to address class imbalance?
- What are the potential drawbacks of using SMOTE, and how can they be mitigated?
- Can you provide an example of how SMOTE can be implemented in a machine learning pipeline to address class imbalance?
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