Which metric can you use to evaluate a classification model?

Which metric can you use to evaluate a classification model?
A . true positive rate
B . mean absolute error (MAE)
C . coefficient of determination (R2)
D . root mean squared error (RMSE)

View Answer

Answer: A

Explanation:

What does a good model look like? An ROC curve that approaches the top left corner with 100% true positive rate and 0% false positive rate will be the best model. A random model would display as a flat line from the bottom left to the top right corner. Worse than random would dip below the y=x line.

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml#classification