Multi Class Global Feature Importance
<p>Compute and Visualize Global Feature Importance Metrics<br><br>This application is a simple example of inspecting global feature importance for binary and multiclass classification with KNIME Software. The key of this example is the Global Feature Importance component verified and developed by the KNIME Team. </p>
URL: KNIME Integrated Deployment - KNIME.com https://www.knime.com/integrated-deployment
URL: Molnar, Christoph. "Interpretable machine learning. A Guide for Making Black Box Models Explainable", 2019. https://christophm.github.io/interpretable-ml-book/
URL: Seven Techniques for Data Dimensionality Reduction (2015) https://www.knime.com/white-papers
URL: Wine quality data set (Kaggle) https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009
Nodes
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Data Generation
- FeatureKNIME Deep Learning - Keras Integration
- FeatureKNIME Ensemble Learning Wrappers
- FeatureKNIME H2O Machine Learning Integration
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