What is recall in machine learning?
An example of an AI chatbot conversation about recall in machine learning.
What is recall in machine learning?
Recall is a metric that measures the ability of a model to find all the relevant cases (true positives) in a dataset.
How is recall calculated?
Recall is calculated using the formula: Recall = True Positives / (True Positives + False Negatives).
Why is recall important?
Recall is crucial in scenarios where missing a positive case is more costly, like in medical diagnoses.
Can you give an example of recall in a real-world application?
Sure! In spam detection, recall helps ensure that most spam emails are identified and not missed.
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