6 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Effector: A Python package for regional explanations
Vasilis Gkolemis, Christos Diou, Dimitris Kyriakopoulos +10
Effector is a Python package for interpreting machine learning (ML) models that are trained on tabular data through global and regional feature effects. Global effects, like Partia…
cs.LG2023★ 6 cited
Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis
Christian A. Scholbeck, Julia Moosbauer, Giuseppe Casalicchio +3
We argue that interpretations of machine learning (ML) models or the model-building process can be seen as a form of sensitivity analysis (SA), a general methodology used to explai…