What term denotes incorrectly labeling a positive case as negative?

Unlock all questions

This demo includes only 20 questions. Upgrade to access hundreds of questions, flashcards, exam simulations, and disable ads.

Full question bankExam simulationsFlashcards
From $9.99Unlock all

Prepare for the GARP Risk and AI (RAI) Exam with targeted quizzes. Utilize flashcards, multiple-choice questions, and detailed explanations to enhance learning. Ace your exam with our comprehensive quiz!

Multiple Choice

What term denotes incorrectly labeling a positive case as negative?

Explanation:
In binary classification, when the actual case is positive but the model predicts negative, that mistake is a false negative. It means a real positive case was missed, which hurts recall—the ability to detect positives. The opposite error would be labeling a negative case as positive, which is a false positive. The F1 score and AUC are metrics used to evaluate performance, not the name of the error type itself. So the term for incorrectly labeling a positive case as negative is false negative.

In binary classification, when the actual case is positive but the model predicts negative, that mistake is a false negative. It means a real positive case was missed, which hurts recall—the ability to detect positives. The opposite error would be labeling a negative case as positive, which is a false positive. The F1 score and AUC are metrics used to evaluate performance, not the name of the error type itself. So the term for incorrectly labeling a positive case as negative is false negative.

More Multiple Choice Questions
Subscribe

Get the latest from Examzify

You can unsubscribe at any time. Read our privacy policy