What are the best metrics for evaluating AI models?
The best metrics depend on the type of model and task. Common metrics include accuracy, precision, recall, and F1 score.
Can you explain precision and recall?
Sure! Precision measures the accuracy of positive predictions, while recall measures the ability to find all relevant instances.
How do I choose the right metric for my model?
Consider the problem type and the consequences of false positives vs. false negatives. For example, in medical diagnosis, recall might be more important.
Are there any metrics specific to regression models?
Yes! For regression models, common metrics include Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared.
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