Quantifying Local Model Validity using Active Learning

Real-world applications of machine learning models are often subject to legal or policy-based regulations. Some of these regulations require ensuring the validity of the model, i.e., the approximation error being smaller than a threshold. A global metric is generally too insensitive to determine the...

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Bibliographische Detailangaben

Hauptverfasser:	Lämmle, Sven, Bogoclu, Can, Voßhall, Robert, Haselhoff, Anselm, Roos, Dirk
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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