16 citations · 28 across the 4 of their papers we have counts for
4 papers
Change Detection for Local Explainability in Evolving Data Streams
Johannes Haug, Alexander Braun, Stefan Zürn +1
As complex machine learning models are increasingly used in sensitive applications like banking, trading or credit scoring, there is a growing demand for reliable explanation mecha…
Standardized Evaluation of Machine Learning Methods for Evolving Data Streams
Johannes Haug, Effi Tramountani, Gjergji Kasneci
Due to the unspecified and dynamic nature of data streams, online machine learning requires powerful and flexible solutions. However, evaluating online machine learning methods und…
On Baselines for Local Feature Attributions
Johannes Haug, Stefan Zürn, Peter El-Jiz +1
High-performing predictive models, such as neural nets, usually operate as black boxes, which raises serious concerns about their interpretability. Local feature attribution method…
Leveraging Model Inherent Variable Importance for Stable Online Feature Selection
Johannes Haug, Martin Pawelczyk, Klaus Broelemann +1
Feature selection can be a crucial factor in obtaining robust and accurate predictions. Online feature selection models, however, operate under considerable restrictions; they need…