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QI2 -- an Interactive Tool for Data Quality Assurance

  • The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well known MNIST data set based an handwritten digits.

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Metadaten
Author:Simon GeerkensORCiD, Christian SieberichsORCiD, Alexander BraunORCiD, Thomas Waschulzik
open access (DINI-Set):open_access
open access :Green - Zweitveröffentlichung
Fachbereich/Einrichtung:Hochschule Düsseldorf / Fachbereich - Elektro- & Informationstechnik
Document Type:Preprint
Year of Completion:2023
Language of Publication:English
Place of publication:arXiv
ArXiv Id:http://arxiv.org/abs/2307.03419
Tag:Artificial Intelligence; Computers and Society; Data Structures and Algorithms; Machine Learning
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Licence (German):Es gilt das deutsche Urheberrecht
Release Date:2023/08/28
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