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Related Questions
- What are the different types of class imbalance, and how do they occur in machine learning datasets?
- How can class imbalance affect the accuracy and performance of machine learning models?
- What are some common ways to handle class imbalance, such as oversampling minority classes or undersampling majority classes?
- What are the pros and cons of using class balancing techniques, and when to use them?
- Can class imbalance also affect the interpretability and explainability of machine learning models?
- How can data preprocessing methods, such as feature selection and dimensionality reduction, impact class imbalance?
- Are there any new techniques or approaches for handling class imbalance in recent years, and what are their advantages?
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