AutoWeka4MCPS-AVATAR: Accelerating automated machine learning pipeline composition and optimisation

Automated machine learning pipeline (ML) composition and optimisation aim at automating the process of finding the most promising ML pipelines within allocated resources (i.e., time, CPU and memory). Existing methods, such as Bayesian-based and genetic-based optimisation, which are implemented in Au...

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Podrobná bibliografie
Vydáno v:	Expert systems with applications Ročník 185; s. 115643
Hlavní autoři:	Nguyen, Tien-Dung, Musial, Katarzyna, Gabrys, Bogdan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Elsevier Ltd 15.12.2021 Elsevier BV
Témata:	Algorithms Automated machine learning Automation AutoML Composition Configuration space reduction Knowledge bases (artificial intelligence) Machine learning Machine learning pipeline evaluation Optimization Petri nets Pipeline composition and optimisation Pipelining (computers) Prediction models Configuration space reduction Automated machine learning Pipeline composition and optimisation AutoML Machine learning pipeline evaluation
ISSN:	0957-4174, 1873-6793
On-line přístup:	Získat plný text
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