AutoConf: Automated Configuration of Unsupervised Learning Systems Using Metamorphic Testing and Bayesian Optimization

Unsupervised learning systems using clustering have gained significant attention for numerous applications due to their unique ability to discover patterns and structures in large unlabeled datasets. However, their effectiveness highly depends on their configuration, which requires domain-specific e...

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Veröffentlicht in:	IEEE/ACM International Conference on Automated Software Engineering : [proceedings] S. 1326 - 1338
Hauptverfasser:	Shar, Lwin Khin, Goknil, Arda, Husom, Erik Johannes, Sen, Sagar, Tun, Yan Naing, Kim, Kisub
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 11.09.2023
Schlagworte:	Bayes methods Clustering algorithms Complexity theory Manuals Measurement Optimization Unsupervised learning
ISSN:	2643-1572
Online-Zugang:	Volltext
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