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Author (up) Ramsey, A.; Kale, A.; Kassa, Y.; Gandhi, R.; Ricks, B. pdf  doi
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  Title Toward Interactive Visualizations for Explaining Machine Learning Models Type Conference Article
  Year 2023 Publication Proceedings of the 20th International ISCRAM Conference Abbreviated Journal Iscram 2023  
  Volume Issue Pages 837-852  
  Keywords Explainable Ai; Data Visualization; Bridge Health; Decision Trees  
  Abstract Researchers and end users generally demand more trust and transparency from Machine learning (ML) models due to the complexity of their learned rule spaces. The field of eXplainable Artificial Intelligence (XAI) seeks to rectify this problem by developing methods of explaining ML models and the attributes used in making inferences. In the area of structural health monitoring of bridges, machine learning can offer insight into the relation between a bridge’s conditions and its environment over time. In this paper, we describe three visualization techniques that explain decision tree (DT) ML models that identify which features of a bridge make it more likely to receive repairs. Each of these visualizations enable interpretation, exploration, and clarification of complex DT models. We outline the development of these visualizations, along with their validity by experts in AI and in bridge design and engineering. This work has inherent benefits in the field of XAI as a direction for future research and as a tool for interactive visual explanation of ML models.  
  Address University of Nebraska at Omaha; University of Nebraska at Omaha; University of Nebraska at Omaha; University of Nebraska at Omaha  
  Corporate Author Thesis  
  Publisher University of Nebraska at Omaha Place of Publication Omaha, USA Editor Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi  
  Language English Summary Language Original Title  
  Series Editor Hosssein Baharmand Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition 1  
  ISSN ISBN Medium  
  Track Infrastructure Health Monitoring During Crises and Disaster Expedition Conference  
  Notes http://dx.doi.org/10.59297/ENJI5258 Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2570  
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