Interactive MLI Composite View

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"


This is a companion discussion topic for the original entry at https://kni.me/w/NQCbRsanrzNnzCDX