What is recall?
The proportion of relevant items that are correctly identified by a model
recall explained in plain English
Analogy
A librarian trying to find all the books on a specific topic. If the librarian finds 9 out of 10 books, but also picks up 2 irrelevant books, their recall is high because they found most of the relevant books, but their precision might be low because they also picked up some irrelevant ones.
Example
A search engine's recall is high if it returns most of the relevant websites for a given search query, even if it also returns some irrelevant ones.
How is recall used?
Recall is used to evaluate the performance of models in information retrieval, classification, and other tasks where finding relevant items is important.
Common misconceptions about recall
History
The concept of recall has been around since the early days of information retrieval, and it's still widely used today in many fields, including machine learning and data science.
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