Data Quality Assessment for ML Decision-Making

Alexandra-Ştefania Moloiu, Grigore Albeanu, Henrik Madsen, Florin Popenţiu-Vlădicescu

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review


Data quality has a strong effect on the design, validation and testing of decision-making systems. New paradigms of future models in the knowledge society need to analyze clean, complete, consistent, and high-quality data. This paper presents three case studies from different fields in which models are constructed using machine learning strategies. Projects on text recognition, electrocardiogram-based identification and data analysis are described in relation to input data quality and system performance.
Original languageEnglish
Title of host publicationApplications in Reliability and Statistical Computing
Publication date2023
ISBN (Print)978-3-031-21231-4, 978-3-031-21234-5
ISBN (Electronic)978-3-031-21232-1
Publication statusPublished - 2023


  • Quality factors
  • Time series
  • Neural networks
  • Text recognition
  • Electrocardiogram based identification
  • Data analysis


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