Data Quality Assessment for ML based Decision-Making Systems

Moloiu Alexandra-Ètefania, Albeanu Grigore, Madsen Henrik, PopenÈiu VlÄdicescu Florin

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Data quality has a strong effect on decision-making systems design, validation and testing. This paper presents three case studies from different fields where models are built using machine learning strategies. The projects on text recognition, electrocardiogram based identification, and data analyses are described related to input data quality and the system performance.
Original languageEnglish
Title of host publicationProceedings of 26th Issat International Conference on Reliability and Quality in Design
PublisherIEEE
Publication date2021
Pages39-43
ISBN (Print)9780991057696
Publication statusPublished - 2021
Event26th Issat International Conference on Reliability and Quality in Design - Miami, United States
Duration: 5 Aug 20217 Aug 2021

Conference

Conference26th Issat International Conference on Reliability and Quality in Design
Country/TerritoryUnited States
CityMiami
Period05/08/202107/08/2021

Keywords

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

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