01_Explainable_Artificial_Intelligence_(XAI)_Simple
eXplainable Artificial Intelligence (XAI) - Simple
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.
Nodes
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Data Generation
- FeatureKNIME Deep Learning - Keras Integration
- FeatureKNIME Ensemble Learning Wrappers
- FeatureKNIME H2O Machine Learning Integration
- Show all 14 modules
Links
- KNIME Integrated Deployment - KNIME.comwww.knime.com/integrated-deployment
- AutoML Component - KNIME Hubkni.me/c/33fQGaQzuZByy6hE
- XAI View Component - KNIME Hubkni.me/c/no0cArkQ94BnNpeb
- Interpretable Machine Learning - Christoph Molnar - 2020-09-28christophm.github.io/interpretable-ml-book/
- Explainable artificial intelligence - WIkipediaen.wikipedia.org/wiki/Explainable_artificial_intelligence