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In a binary classification, what does a high recall indicate?

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Question: In a binary classification, what does a high recall indicate?

Options:

  1. The model is good at identifying negative cases
  2. The model is good at identifying positive cases
  3. The model has a high number of false positives
  4. The model has a high number of false negatives

Correct Answer: The model is good at identifying positive cases

Solution: 

High recall indicates that the model is effective at identifying most of the actual positive cases.

In a binary classification, what does a high recall indicate?

Practice Questions

Q1
In a binary classification, what does a high recall indicate?
  1. The model is good at identifying negative cases
  2. The model is good at identifying positive cases
  3. The model has a high number of false positives
  4. The model has a high number of false negatives

Questions & Step-by-Step Solutions

In a binary classification, what does a high recall indicate?
  • Step 1: Understand what binary classification means. It is a type of problem where there are two classes: positive and negative.
  • Step 2: Know what recall is. Recall measures how many actual positive cases were correctly identified by the model.
  • Step 3: Realize that a high recall means the model is good at finding most of the positive cases.
  • Step 4: Conclude that if a model has high recall, it means it misses very few positive cases.
  • Recall – Recall is a metric that measures the ability of a model to identify all relevant instances, specifically the proportion of true positives out of the total actual positives.
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