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.

External resources

• Burr Settles, Active Learning Literature Survey, 2010 - Chapter 3.1 Uncertainty Sampling