Suppose I am facing a highly imbalanced classification problem, where the number of yes cases is significantly

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Suppose I am facing a highly imbalanced classification problem, where the number of "yes" cases is significantly low compared to the number of "no" cases. In this situation, what is likely the worst error metric to use when evaluating potential classifiers on the training data? A. Percent correct. B. Recall. C. F1 D. AUC E. Any of the above would be fine

Posted Date: May 17, 2024 07:04 PM

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Suppose I am facing a highly imbalanced classification problem, where the number of yes cases is significantly

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