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In machine learning, dealing with covariate imbalance is an important consideration. Can you explain some approaches or techniques that can be used to address covariate imbalance in a dataset? How do these approaches help in improving the performance of machine learning models?
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Discuss both data preprocessing techniques and algorithm-specific methods, with examples of their impact on model performance
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