What are performance metrics for AI models?

What are performance metrics for AI models?

Performance metrics are quantitative measures used to evaluate the effectiveness of AI models, such as accuracy, precision, recall, and F1 score.

How do I choose the right metric for my model?

Choosing the right metric depends on your specific use case. For example, if false positives are costly, you might prioritize precision.

Can you explain accuracy and precision in more detail?

Sure! Accuracy measures the overall correctness of the model, while precision focuses on the proportion of true positive results among all positive predictions.

What are some common pitfalls when interpreting these metrics?

Common pitfalls include over-relying on a single metric, ignoring the context of the problem, and not considering the trade-offs between metrics.