Multi Class Global & Local Feature Importance

Compute and Visualize Global Feature Importance Metrics

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.

External resources

• KNIME Integrated Deployment - KNIME.com
• Molnar, Christoph. "Interpretable machine learning. A Guide for Making Black Box Models Explainable", 2019.
• Seven Techniques for Data Dimensionality Reduction (2015)
• Wine quality data set (Kaggle)