Active Learning with Modular Score

This workflow shows an example of Active Learning. We read a simple dataset of images separated in two classes and calculate some features on them. Now the Active Learning Loop determines the best sample which could be manuallay labeled by a user and benefits most to the separation of the calsses. The decision of the best sample is based on a specific score. Here we use a modular score calculation approach in order to find the best sample.

External resources

• KNIME Active Learning