Precision and Recall

Definition

Precision and recall are the measures used in the information retrieval domain to measure how well an information retrieval system retrieves the relevant documents requested by a user. The measures are defined as follows:

Precision  =  Total number of documents retrieved that are relevant/Total number of documents that are retrieved.

Recall  =  Total number of documents retrieved that are relevant/Total number of relevant documents in the database.

We can use the same terminology used in a confusion matrix to define these two measures. Let relevant documents be positive examples and irrelevant documents, negative examples. The two measures can be redefined with reference to a special case of the confusion matrix, with two classes, one designated the positive class, and the other the negative class, as indicated in Table 1.

Precision and Recall. Table 1 The outcomes of classification into positive and negative classes