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 employ 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