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Exercise

Confusion matrices

Confusion matrices are a great way to start exploring your model's accuracy. They provide the values needed to calculate a wide range of metrics, including sensitivity, specificity, and the F1-score.

You have built a classification model to predict if a person has a broken arm based on an X-ray image. On the testing set, you have the following confusion matrix:

Prediction: 0 Prediction: 1
Actual: 0 324 (TN) 15 (FP)
Actual: 1 123 (FN) 491 (TP)
Instructions
100 XP
  • Use the confusion matrix to calculate overall accuracy.
  • Use the confusion matrix to calculate precision and recall.
  • Use the three print statements to print each accuracy value.
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