In pattern recognition, information retrieval and binary classification, precision is the fraction of relevant instances among the retrieved instances, while recall is the fraction of relevant instances that have been retrieved over the total amount of relevant instances.
In the field of information retrieval, precision is the fraction of retrieved documents that are relevant to the query:
In information retrieval, recall is the fraction of the relevant documents that are successfully retrieved.
Precision and recall are two extremely important model evaluation metrics and also for an SEO company. While precision refers to the percentage of your results which are relevant, recall refers to the percentage of total relevant results correctly classified by your algorithm.
Calculating precision and recall: