This worflow will show how to use the interactive views of JavaScript nodes to visualize in a single Composite View a number of Machine Learning Interpretability (MLI) techniques:
Shapley Values, Partial Dependence, Individual Conditional Expectation (ICE) curves and Surrogate Decision Tree.
- Shapley Values,
- Partial Dependence,
- Individual Conditional Expectation (ICE) curves
- Surrogate Decision Tree.
Computing SHAP explanations takes time.
Use the Component dialog panel to define how many explanations should be explained and which is the class of interest.
To open the Component View: Right click: "Execute and Open View"
To enter the Component: Right click : "Component" > "Open"
Workflow
Interactive MLI Composite View
External resources
Used extensions & nodes
Created with KNIME Analytics Platform version 4.2.0
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