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https://doi.org/10.21256/zhaw-3156| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Automated machine learning in practice : state of the art and recent results |
| Autor/-in: | Tuggener, Lukas Amirian, Mohammadreza Rombach, Katharina Lörwald, Stefan Varlet, Anastasia Westermann, Christian Stadelmann, Thilo |
| et. al: | No |
| DOI: | 10.1109/SDS.2019.00-11 10.21256/zhaw-3156 |
| Tagungsband: | 2019 6th Swiss Conference on Data Science (SDS) |
| Seite(n): | 31 |
| Seiten bis: | 36 |
| Angaben zur Konferenz: | 6th Swiss Conference on Data Science (SDS), Bern, 14. Juni 2019 |
| Erscheinungsdatum: | 14-Jun-2019 |
| Verlag / Hrsg. Institution: | IEEE |
| ISBN: | 978-1-7281-3105-4 |
| Sprache: | Englisch |
| Schlagwörter: | AutoML; Meta learning; CASH; Portfolio hyperband; Learning to learn; Reinforcement learning |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren |
| Zusammenfassung: | A main driver behind the digitization of industry and society is the belief that data-driven model building and decision making can contribute to higher degrees of automation and more informed decisions. Building such models from data often involves the application of some form of machine learning. Thus, there is an ever growing demand in work force with the necessary skill set to do so. This demand has given rise to a new research topic concerned with fitting machine learning models fully automatically – AutoML. This paper gives an overview of the state of the art in AutoML with a focus on practical applicability in a business context, and provides recent benchmark results of the most important AutoML algorithms. |
| Weitere Angaben: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/17502 |
| Volltext Version: | Akzeptierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) |
| Publiziert im Rahmen des ZHAW-Projekts: | Ada – Advanced Algorithms for an Artificial Data Analyst |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| SDS_2019.pdf | 144.43 kB | Adobe PDF |  Öffnen/Anzeigen |
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Tuggener, L., Amirian, M., Rombach, K., Lörwald, S., Varlet, A., Westermann, C., & Stadelmann, T. (2019). Automated machine learning in practice : state of the art and recent results [Conference paper]. 2019 6th Swiss Conference on Data Science (SDS), 31–36. https://doi.org/10.1109/SDS.2019.00-11
Tuggener, L. et al. (2019) ‘Automated machine learning in practice : state of the art and recent results’, in 2019 6th Swiss Conference on Data Science (SDS). IEEE, pp. 31–36. Available at: https://doi.org/10.1109/SDS.2019.00-11.
L. Tuggener et al., “Automated machine learning in practice : state of the art and recent results,” in 2019 6th Swiss Conference on Data Science (SDS), Jun. 2019, pp. 31–36. doi: 10.1109/SDS.2019.00-11.
TUGGENER, Lukas, Mohammadreza AMIRIAN, Katharina ROMBACH, Stefan LÖRWALD, Anastasia VARLET, Christian WESTERMANN und Thilo STADELMANN, 2019. Automated machine learning in practice : state of the art and recent results. In: 2019 6th Swiss Conference on Data Science (SDS). Conference paper. IEEE. 14 Juni 2019. S. 31–36. ISBN 978-1-7281-3105-4
Tuggener, Lukas, Mohammadreza Amirian, Katharina Rombach, Stefan Lörwald, Anastasia Varlet, Christian Westermann, and Thilo Stadelmann. 2019. “Automated Machine Learning in Practice : State of the Art and Recent Results.” Conference paper. In 2019 6th Swiss Conference on Data Science (SDS), 31–36. IEEE. https://doi.org/10.1109/SDS.2019.00-11.
Tuggener, Lukas, et al. “Automated Machine Learning in Practice : State of the Art and Recent Results.” 2019 6th Swiss Conference on Data Science (SDS), IEEE, 2019, pp. 31–36, https://doi.org/10.1109/SDS.2019.00-11.
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