What is recall in AI models and why is it important?

What is recall in AI models and why is it important?

Recall is a metric that measures the ability of an AI model to identify all relevant instances. It's crucial for tasks where missing a positive instance is costly.

Can you give me an example of how recall is used in real-world applications?

Sure! In medical diagnosis, recall helps ensure that all patients with a disease are identified, minimizing false negatives.

How does recall differ from precision?

Recall focuses on the true positives out of all actual positives, while precision measures the true positives out of all predicted positives.

What are some ways to improve recall in AI models?

You can improve recall by adjusting the decision threshold, using more data, or employing techniques like oversampling.