In a medical diagnosis scenario, how would you evaluate a model using Precision, Recall, and the ROC Curve? Explain the considerations you would take into account.
- Focus equally on Precision and Recall, use ROC for sensitivity
- Focus on Precision to minimize false positives, use ROC for specificity
- Focus on Recall to minimize false negatives, use ROC for overall trade-off
- nan
In medical diagnosis, minimizing false negatives (missing a true condition) is often crucial, so Recall is highly valued. The ROC Curve is used to understand the trade-off between sensitivity and specificity, providing a comprehensive view of the model's performance.
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