Active Learning with Basic SVM Model

This workflow uses a simple example to demonstrate one possible structure for an active learning application and compares the effectiveness of the active learning strategy vs a random labeling approach.

The example model is trained to predict whether a point on the x-y plane lies above or below the x-axis.

In a real application of the active learning loop, replace the Rule Engine nodes with your method of labeling. For example the Label View node for easy labeling in the KNIME WebPortal.

External resources

• Burr Settles, Active Learning Literature Survey, 2010 - Chapter 3.1 Uncertainty Sampling
• Active learning for object classification - Nicolas Cebron et al - Data Min Knowl Disc (2009)