This application is a simple example of AutoML with KNIME Software for binary and multiclass classification. The output models are then explained via the interactive XAI View, which works for any model the AutoML component produces. Machine Learning Interpretability (MLI) techniques used: SHAP explanations/reason codes, partial dependence, individual conditional expectation (ICE) curves and a surrogate decision tree. The workflow also works locally on KNIME Analytics Platform. Make sure to use "Apply and Close" in bottom-right corner of each view.
This is a companion discussion topic for the original entry at https://kni.me/w/5xfwkuVsF6Uz8hMC
