Jan Ittner
Computer scientist specialising in Artificial Intelligence, Machine Learning & Software Engineering. Co-founder of BCG GAMMA and member of GAMMA's leadership.
Sessions
Understanding dependencies between features is crucial in the process of developing and interpreting black-box ML models. Mistreating or neglecting this aspect can lead to incorrect conclusions and, consequentially, sub-optimal or wrong decisions leading to financial losses or other undesired outcomes. Many common approaches to explain ML models – as simple as feature importance or more advanced methods such as SHAP – can yield misleading results if mutual feature dependencies are not taken into account.
In this talk we present FACET 2.0 - a new approach for global feature explanations using a new technique called SHAP vector projection, open-sourced at: https://github.com/BCG-Gamma/facet/.