Guided Labeling for Document Classification

This workflow defines a fully automated web based application that will label your data using active learning. The workflow was designed for business analysts to easily go through documents to be labeled in any number of classes. In each iteration the user labels more documents and the model is trained using the already labeled instances. With every new iteration, the model proposes the most uncertain documents using the entropy scorer node. Once the user is happy with the performance achieved with the available labels, they can exit the loop and export the model to label the remaining instances.

This is a companion discussion topic for the original entry at

Thank you for creating this workflow, I had been searching for how to do this interactive learning. I am getting stuck between steps 2 and 3: after labelling some data, I have to press the button ‘Next’ - however, I do not see one. Is this bacause I do not have Knime Server installed? I am just using the free personal version of Knime.