Active Learning is an application that lets you run continuously updated queues of documents for review, based on your review strategy. The advantages of Active Learning include real-time intelligence, efficiency, flexibility, and integration with all the power of the Relativity platform.
Start your Active Learning project by creating a new classification index and choosing a single-choice field for reviewers to code relevance. Once you start the review queue, reviewers can access the queue and begin coding documents. Coding decisions are ingested by the Active Learning model where Active Learning takes place. This allows the queues to get better at serving relevant documents to reviewers. This whole process is continuous. As reviewers code and the model updates, project admins can monitor the queue for certain metrics.