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

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

Choosing the right metrics depends on your model's purpose. Are you focusing on classification, regression, or something else?

I'm working on a classification model for image recognition.

For classification, you might consider metrics like accuracy, precision, recall, and F1 score. Do you have a specific goal in mind?

I want to minimize false negatives.

In that case, prioritizing recall would be beneficial, as it focuses on capturing as many positive instances as possible.

What about the trade-offs between precision and recall?

Great question! There's often a trade-off; increasing recall can decrease precision and vice versa. The F1 score can help balance both.