Kurz erklärt: Measuring Data Changes in Data Engineering and their Impact on Explainability and Algorithm Fairness

URN to cite this document:: urn:nbn:de:bvb:355-epub-772900
DOI to cite this document:: 10.5283/epub.77290

Klettke, Meike

; Lutsch, Adrian ; Störl, Uta

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 13 Aug 2025 06:57

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Abstract

Data engineering is an integral part of any data science and ML process. It consists of several subtasks that are performed to improve data quality and to transform data into a target format suitable for analysis. The quality and correctness of the data engineering steps is therefore important to ensure the quality of the overall process. In machine learning processes requirements such as ...