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What does recall measure in a classification task?

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Question: What does recall measure in a classification task?

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 overall accuracy of the model
  4. The number of false negatives

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 relevant cases (true positives) in the dataset.

What does recall measure in a classification task?

Practice Questions

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

Questions & Step-by-Step Solutions

What does recall measure in a classification task?
  • Step 1: Understand that recall is a metric used in classification tasks.
  • Step 2: Recall focuses on the positive cases in the dataset.
  • Step 3: Identify true positives, which are the relevant cases that the model should find.
  • Step 4: Recall measures how many of these true positives the model successfully identifies.
  • Step 5: A higher recall means the model is good at finding most of the relevant cases.
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