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Consider a machine learning model where the model is attempting to predict if a patient...

Consider a machine learning model where the model is attempting to predict if a patient is at risk for stroke. The model collects information on each patient regarding their blood pressure, red blood cell count, smoking status, history of heart disease, cholesterol level, and demographics. Then, using a decision tree the model predicts whether or not the associated patient is likely to have a stroke in the near future. Once the model is created using a training dataset, it is used to predict a stroke in 80 additional patients. The table below shows a confusion matrix on whether or not the model made a correct or incorrect prediction.

The testers have calculated what they believe to be an appropriate functional performance metric for the model. They calculated a value of 0.6667.

Which metric did the testers calculate?

A.

F1-score

B.

Precision

C.

Recall

D.

Accuracy

ISTQB CT-AI Summary

  • Vendor: ISTQB
  • Product: CT-AI
  • Update on: Jul 21, 2025
  • Questions: 80
Price: $52.5  $149.99
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