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What does recall measure in a classification model?

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Question: What does recall measure in a classification model?

Options:

  1. The ratio of true positives to the total actual positives
  2. The ratio of true positives to the total predicted positives
  3. The ratio of true negatives to the total actual negatives
  4. The ratio of false negatives to the total actual positives

Correct Answer: The ratio of true positives to the total actual positives

Solution: 

Recall, also known as sensitivity, measures the ability of a model to find all the relevant cases (true positives).

What does recall measure in a classification model?

Practice Questions

Q1
What does recall measure in a classification model?
  1. The ratio of true positives to the total actual positives
  2. The ratio of true positives to the total predicted positives
  3. The ratio of true negatives to the total actual negatives
  4. The ratio of false negatives to the total actual positives

Questions & Step-by-Step Solutions

What does recall measure in a classification model?
  • Step 1: Understand that recall is a metric used in classification models.
  • Step 2: Recall is also called sensitivity.
  • Step 3: Recall measures how well the model identifies positive cases.
  • Step 4: Positive cases are the instances that are actually relevant or true positives.
  • Step 5: A high recall means the model finds most of the relevant cases.
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