Figure 1.

An interactive machine learning cycle begins with the review step, with output from the learning model displayed to the user. User feedback is used by the system to improve upon the machine learning models by providing labels for documents that were previously not part of the training set, or by correcting any misclassified documents. After retraining, a new model is created and the tool shows prediction changes and provides guidance for resolving potentially contradictory feedback items.