GAM Changer: Editing Generalized Additive Models with Interactive Visualization

Recent strides in interpretable machine learning (ML) research reveal that models exploit undesirable patterns in the data to make predictions, which potentially causes harms in deployment. However, it is unclear how we can fix these models. We present our ongoing work, GAM Changer, an open-source i...

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Bibliographische Detailangaben

Hauptverfasser:	Wang, Zijie J, Kale, Alex, Nori, Harsha, Stella, Peter, Nunnally, Mark, Chau, Duen Horng, Vorvoreanu, Mihaela, Vaughan, Jennifer Wortman, Caruana, Rich
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction Computer Science - Learning
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