How to find feature importance after model building?

[mlauber71]

@somnathdas76 some model would just provide you with the feature importance (most H2O.ai models, Random Forest, XGBoost …), but you can also explore the Global Feature Importance – KNIME Community Hub

Understand Your ML Model: Global Feature Importance | KNIME

Compute and Visualize Global Feature Importance Metrics – lada

Also this thread holds some more hints:

Feature Importance in Decision Trees

Hi @bfrutchey take a look for inspiration and some directions shap and shapley values machine learning interpretability model interpretability Titanic gr Hans

I tried my hand at one idea mentioned here to re-engineer the feature importance via Tree models and the likes. But I am not 100% satisfied with the results:

Re-Engineering the variable importance by feeding the Score (of a binary...

Then … @Morris_Kurz has provided us with two interesting nodes that also might help (TreeSHAP Random Forest – KNIME Community Hub, TreeSHAP Random Forest (Regression) – KNIME Community Hub)

TreeSHAP Example Workflow – morris_kurz