A Dashboard for Simplifying Machine Learning Models using Feature Importances and Spurious Correlation Analysis

Cech, TimKohlros, ErikScheibel, WillyDöllner, JürgenKucher, KostiantynDiehl, AlexandraGillmann, Christina2024-05-212024-05-212024978-3-03868-258-5https://doi.org/10.2312/evp.20241075https://diglib.eg.org/handle/10.2312/evp20241075Machine Learning models underlie a trade-off between accurracy and explainability. Given a trained, complex model, we contribute a dashboard that supports the process to derive more explainable models, here: Fast-and-Frugal Trees, with further introspection using feature importances and spurious correlation analyses. The dashboard further allows to iterate over the feature selection and assess the trees' performance in comparison to the complex model.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing → Visualization techniques; Information systems → Users and interactive retrievalHuman centered computing → Visualization techniquesInformation systems → Users and interactive retrievalA Dashboard for Simplifying Machine Learning Models using Feature Importances and Spurious Correlation Analysis10.2312/evp.202410753 pages