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: