A Partial Dependence Plot shows how a single continuous predictor variable impacts the output of a model when holding all other predictors constant. Essentially we inspect a single predictor variable and observe how the model behaves when we vary the value of that predictor variable. This is achieved by generating samples by varying the value of the given predictor. Knime has nodes that can generate these samples and then help visualize that sampled data using a Partial Dependency Plot. This plot is a great way to understand how your model will behave with new dataset.