What does Richness refer to in an Active Learning project?

Richness in the context of an Active Learning project specifically refers to the percentage of documents in a project that are responsive. This concept is essential because it indicates the effectiveness of the active learning model in distinguishing between relevant and irrelevant documents. The higher the percentage of responsive documents, the richer the dataset is considered, as it demonstrates that the model is accurately identifying the documents that matter within the context of the project's objectives.

This focus on responsiveness allows project teams to understand the quality of the dataset that the model is working with, which can significantly influence the training and refinement of the algorithm used in the active learning process. A project characterized by high richness can lead to improved outcomes since the algorithm is trained on a dataset that aligns closely with the target classification or discovery goals, ultimately enhancing the overall efficiency of the document review process.