Precision and recall

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In classification, precision and recall are performance metrics that apply to data retrieved from a collection, corpus or sample space. Precision (also called positive predictive value) is the fraction of relevant instances among the retrieved instances. Written as a formula: Precision = Relevant retrieved instances All retrieved instances {\displaystyle {\text{Precision}}={\frac {\text{Relevant retrieved instances}}{{\text{All }}{\textbf {retrieved}}{\text{ instances}}}}} Recall (also known as sensitivity) is the fraction of relevant instances that were retrieved. Written as a formula: Recall =...

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