Given a set of results from a processed document, precision is the percentage value that indicates how many of those results are correct based on the expectations of a certain 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 100% precision. Even if half of the instances of dog breeds were missed, the ones that were returned were correct.
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