What does a higher recall indicate in a validation context?

In a validation context, a higher recall indicates a lower number of missing relevant documents. Recall is a metric that measures the ability of a system to identify all relevant instances within a dataset. It is calculated as the ratio of true positives (the relevant documents correctly identified) to the sum of true positives and false negatives (the relevant documents that were not identified). Therefore, when recall is high, it signifies that the system is good at retrieving most or all of the relevant documents, which means fewer relevant documents are being overlooked or missed.

The focus of recall on capturing relevant documents underscores its importance in situations where finding as many relevant documents as possible is critical, such as in legal discovery processes or research tasks. This emphasizes the significance of minimizing false negatives—instances where relevant documents are not found—rather than the precision of the retrieved documents. Hence, in this context, a higher recall is desirable as it reflects an effective identification process of pertinent information.