What does the Relevance Rate in the validation results indicate?

The Relevance Rate in the validation results is a measure that reflects the percentage of sampled documents that were coded as relevant by reviewers. This rate is significant because it provides insight into the effectiveness of the document review process, demonstrating how accurately the system is identifying relevant documents based on the manual coding by human reviewers.

By analyzing this percentage, organizations can evaluate the performance of their predictive coding or machine learning algorithms to ensure they are successfully identifying documents that are meaningful to the case or investigation. A higher relevance rate suggests that the predictive model is functioning effectively, while a lower rate may indicate areas that need improvement in the review process or the algorithms used.

In this context, understanding the relevance of coding is crucial for establishing trust in the results generated by the analytics processes employed. It offers a clear picture of how many of the documents reviewed matched the expectations set during the training phase, thus enabling fine-tuning of the model for better future outcomes.