Interpretable Machine Learning
- Author
- Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry
- Published
- Mon 05 Jun 2023
- Episode Link
- https://podcastae8fac.podigee.io/291-new-episode
Interview with Serg Masis
- Benefits of IML
- Interpretability as the ability to understand how a machine learning model works
- Interpretability is better than explainability.
- Black-box models can be interpretable if viewed from a different perspective.
- Glass box models gaining popularity in IML and provide the benefits of both white-box and black-box models.
- Various modeling approaches related to IML, including rule-based models, decision trees, local linear models, and additive models.
