Answer by jeza for Why is accuracy not the best measure for assessing classification models?

Classification accuracy is the number of correct predictions divided by the total number of predictions.

Accuracy can be misleading. For example, in a problem where there is a large class imbalance, a model can predict the value of the majority class for all predictions and achieve a high classification accuracy. So, further performance measures are needed such as F1 score and Brier score.