Towards Evaluating Exploratory Model Building Process with AutoML Systems

Sungsoo Ray Hong
Sungsoo Ray Hong
Sonia Castelo
Sonia Castelo
Vito D'Orazio
Vito D'Orazio
Christopher Benthune
Christopher Benthune
Aecio Santos
Aecio Santos
Scott Langevin
Scott Langevin
Cited by: 0|Bibtex|Views20
Other Links: arxiv.org

Abstract:

The use of Automated Machine Learning (AutoML) systems are highly open-ended and exploratory. While rigorously evaluating how end-users interact with AutoML is crucial, establishing a robust evaluation methodology for such exploratory systems is challenging. First, AutoML is complex, including multiple sub-components that support a vari...More

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