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Question & Answer
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Sensitivity and specificity are independent metrics.
High sensitivity indicates low specificity.
High sensitivity suggests high specificity as well.
Sensitivity is the true positive rate while specificity is the true negative rate.
Understanding the Answer
Let's break down why this is correct
Sensitivity counts how many real positives the model finds. Other options are incorrect because The idea that they are completely separate is misleading; People often think a good sensitivity means a bad specificity, but that isn’t always true.
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Sensitivity of Predictors
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Definition
The sensitivity of a predictor measures its responsiveness to changes in input features. Insensitive predictors exhibit stability in their predictions when inputs are close. Sensitivity is crucial for generalization and performance, especially with limited training data.
Topic Definition
The sensitivity of a predictor measures its responsiveness to changes in input features. Insensitive predictors exhibit stability in their predictions when inputs are close. Sensitivity is crucial for generalization and performance, especially with limited training data.
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