Given a set of results from a processed document, recall is the percentage value that indicates how many correct results have been retrieved based on the expectations of the application. It can apply to any class of a predictive AI system such as search, categorization and entity recognition.
For example, say you have an application that is supposed to find all the dog breeds in a document. If the application analyzes a document that mentions 10 dog breeds but only returns five values (all of which are correct), the system will have performed at 50% recall.
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