ECS -- an Interactive Tool for Data Quality Assurance
- With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper we present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems.
Author: | Christian SieberichsORCiD, Simon GeerkensORCiD, Alexander BraunORCiD, Thomas Waschulzik |
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open access (DINI-Set): | open_access |
Fachbereich/Einrichtung: | Hochschule Düsseldorf / Fachbereich - Elektro- & Informationstechnik |
Document Type: | Preprint |
Year of Completion: | 2023 |
Language of Publication: | English |
Publisher: | arXiv |
DOI: | https://doi.org/10.48550/arXiv.2307.04368 |
ArXiv Id: | http://arxiv.org/abs/2307.04368 |
Tag: | Artificial Intelligence; Machine Learning; PrePrint; Systems and Control |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten |
Licence (German): | keine Lizenz - nur Metadaten |
Release Date: | 2023/08/25 |