In a statistical classification task, the Precision for a class is the number of true positives (i.e. the number of items correctly labeled as belonging to the class) divided by the total number of elements labeled as belonging to the class (i.e. the sum of true positives and false positives, which are items incorrectly labeled as belonging to the class). Recall in this context is defined as the number of true positives divided by the total number of elements that actually belong to the class (i.e. the sum of true positives and false negatives, which are items which were not labeled as belonging to that class but should have been).
http://en.wikipedia.org/wiki/Precision_and_Recall
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