Predictive Labeling

Predictive labeling generates labels based on your existing labeled data.

Overview

Predictive labeling uses machine learning to generate labels based on a subset of manually labeled data. It helps reduce manual labeling effort and improves consistency, especially for large datasets.

Use case

This example uses Predictive labeling for spam message detection.

1. Create a row labeling project.

   
2. Click the gear icon from the extension panel on the right to open the Manage extensions dialog, then enable the Predictive labeling extension.

   
3. Label at least five items for each answer option. For example, if you have two answer options (True and False), label at least five items as True and five items as False.

4. Select the input columns as context for the prediction and select the target field where predicted labels will be added. Then click Save configuration.

   
5. Review the predicted labels and choose Accept or Reject.

   

For further details, please visit Assisted Labeling - Predictive Labeling.