VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance
Not on the map. Why?
Abstract (arXiv)
The use of machine learning rapidly increases in high-risk scenarios where decisions are required, for example in healthcare or industrial monitoring equipment. In crucial situations, a model that can offer meaningful explanations of its decision-making is essential. In industrial facilities, the equipment's well-timed maintenance is vital to ensure continuous operation to prevent money loss. Using machine learning, predictive and prescriptive maintenance attempt to anticipate and prevent eventual system failures. This paper introduces a visualisation tool incorporating interpretations to display information derived from predictive maintenance models, trained on time-series data.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 31 Mar 2021.
Builds on
6 of 20 references.
References · 6
- 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,040
- 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecastingcited by 744
- 2020A Survey of Visual Analytics Techniques for Machine Learningcited by 56
- 2018Explainable time series tweaking via irreversible and reversible temporal transformationscited by 8
- 2020Altruist: Argumentative Explanations through Local Interpretations of Predictive Modelscited by 5
- 2019LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decodingcited by 3
Built on by
Citing papers per year: 2021: 1; 2022: 1.
2 papers.