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In a case study, if a model has high precision but low recall, what does this in

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Question: In a case study, if a model has high precision but low recall, what does this indicate?

Options:

  1. The model is good at identifying positive cases but misses many.
  2. The model is poor at identifying positive cases.
  3. The model has balanced performance.
  4. The model is overfitting.

Correct Answer: The model is good at identifying positive cases but misses many.

Solution: 

High precision and low recall indicate that the model is good at identifying positive cases but fails to capture many actual positives.

In a case study, if a model has high precision but low recall, what does this in

Practice Questions

Q1
In a case study, if a model has high precision but low recall, what does this indicate?
  1. The model is good at identifying positive cases but misses many.
  2. The model is poor at identifying positive cases.
  3. The model has balanced performance.
  4. The model is overfitting.

Questions & Step-by-Step Solutions

In a case study, if a model has high precision but low recall, what does this indicate?
  • Precision – The ratio of true positive predictions to the total predicted positives, indicating the accuracy of positive predictions.
  • Recall – The ratio of true positive predictions to the total actual positives, indicating the model's ability to capture all relevant cases.
  • Trade-off between Precision and Recall – A model can achieve high precision at the cost of recall, meaning it may miss many actual positive cases.
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