Partial Dependence Plot with a Custom Regression Model

This is an example for visualizing a partial dependence plot and an ICE curves plot in KNIME.
An XGBoost Tree Ensemble Regression model was selected, but any model and its set of Learner and Predictor nodes can be used.

- Read the dataset about wines
- Partition the data in train and test
- Create the samples via the apposite shared component Partial Dependence Pre-processing
- Score the samples using the selected predictor and learner nodes.
- Visualize the Partial Dependence/ICE Plot and customize it directly in the View (Execute > Right Click > Open View)
- Apply and Close to save the custom in-view settings

External resources

• Data Source: UCI - Wine Quality Data Set
• Christoph Molnar - Interpretable Machine Learning - A Guide for Making Black Box Models Explainable - 5.1 Partial Dependence Plot (PDP)
• Verified Components