What are some alternative metrics for evaluating AI models?

What are some alternative metrics for evaluating AI models?

Alternative metrics include F1 score, AUC-ROC, precision-recall curves, and Matthews correlation coefficient.

Can you explain the F1 score and when to use it?

The F1 score is the harmonic mean of precision and recall, useful when you need a balance between the two.

What about AUC-ROC? How does it differ from F1?

AUC-ROC measures the model's ability to distinguish between classes, while F1 focuses on the balance of precision and recall.

Are there any metrics specific to imbalanced datasets?

Yes, metrics like the Matthews correlation coefficient and balanced accuracy are particularly useful for imbalanced datasets.