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What does a high precision but low recall indicate?

Practice Questions

Q1
What does a high precision but low recall indicate?
  1. The model is good at identifying positive cases but misses many
  2. The model is good at identifying all 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

What does a high precision but low recall indicate?
  • Step 1: Understand what precision means. Precision is the number of true positive results divided by the total number of positive results predicted by the model.
  • Step 2: Understand what recall means. Recall is the number of true positive results divided by the total number of actual positive cases.
  • Step 3: A high precision means that when the model predicts a positive case, it is usually correct.
  • Step 4: A low recall means that the model is missing many actual positive cases and not identifying them.
  • Step 5: Therefore, high precision but low recall indicates that the model is good at correctly identifying the few positive cases it does find, but it fails to find many other positive cases.
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