How do I choose the right metrics for evaluating AI models?

How do I choose the right metrics for evaluating AI models?

Choosing the right metrics depends on your specific goals. Are you focusing on accuracy, precision, recall, or something else?

I want to ensure my model is not just accurate but also fair.

In that case, you might want to consider metrics like fairness, bias, and interpretability alongside traditional accuracy.

What are some common metrics used for classification tasks?

Common metrics for classification include accuracy, precision, recall, F1 score, and ROC-AUC. Each serves a different purpose.

How can I measure the performance of a regression model?

For regression models, you can use metrics like Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared.