4 citations · 4 across the 10 of their papers we have counts for
4 papers · 1 filter
Improving Online Bagging for Complex Imbalanced Data Stream
Bartosz Przybyl, Jerzy Stefanowski
Learning classifiers from imbalanced and concept drifting data streams is still a challenge. Most of the current proposals focus on taking into account changes in the global imbala…
A-PETE: Adaptive Prototype Explanations of Tree Ensembles
Jacek Karolczak, Jerzy Stefanowski
The need for interpreting machine learning models is addressed through prototype explanations within the context of tree ensembles. An algorithm named Adaptive Prototype Explanatio…
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels
Oleksii Furman, Patryk Wielopolski, Łukasz Lenkiewicz +2
The growing complexity of AI systems has intensified the need for transparency through Explainable AI (XAI). Counterfactual explanations (CFs) offer actionable "what-if" scenarios…
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows
Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski +1
We present PPCEF, a novel method for generating probabilistically plausible counterfactual explanations (CFs). PPCEF advances beyond existing methods by combining a probabilistic f…