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Titel:

Model-Driven Engineering Method to Support the Formalization of Machine Learning using SysML

Dokumenttyp:
Verschiedenes
Autor(en):
Raedler, Simon; Mangler, Juergen; Rinderle-Ma, Stefanie
Abstract:
Methods: This work introduces a method supporting the collaborative definition of machine learning tasks by leveraging model-based engineering in the formalization of the systems modeling language SysML. The method supports the identification and integration of various data sources, the required definition of semantic connections between data attributes, and the definition of data processing steps within the machine learning support. Results: By consolidating the knowledge of domain and machine...     »
Stichworte:
Computer Science - Artificial Intelligence, Computer Science - Software Engineering, I.2.4, H.1.0
Verlag/Institution:
arXiv
Monat:
July
Jahr:
2023
Hinweis:
arXiv:2307.04495 [cs]
URL:
http://arxiv.org/abs/2307.04495
DOI-Link:
doi:10.48550/arXiv.2307.04495
Sprache:
de
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