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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Vydané v:	IEEE/ACM International Conference on Automated Software Engineering : [proceedings] s. 1326 - 1338
Hlavní autori:	Shar, Lwin Khin, Goknil, Arda, Husom, Erik Johannes, Sen, Sagar, Tun, Yan Naing, Kim, Kisub
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 11.09.2023
Predmet:	Bayes methods Clustering algorithms Complexity theory Manuals Measurement Optimization Unsupervised learning
ISSN:	2643-1572
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