Towards visual debugging for multi-target time series classification

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PATERNÒ, Fabio, ed., Nuria OLIVER, ed.. IUI '20 : Proceedings of the 25th International Conference on Intelligent User Interfaces. New York, NY: ACM, 2020, pp. 202-206. ISBN 978-1-4503-7118-6. Available under: doi: 10.1145/3377325.3377528
Zusammenfassung

Multi-target classification of multivariate time series data poses a challenge in many real-world applications (e.g., predictive maintenance). Machine learning methods, such as random forests and neural networks, support training these classifiers. However, the debugging and analysis of possible misclassifications remain challenging due to the often complex relations between targets, classes, and the multivariate time series data. We propose a model-agnostic visual debugging workflow for multi-target time series classification that enables the examination of relations between targets, partially correct predictions, potential confusions, and the classified time series data. The workflow, as well as the prototype, aims to foster an in-depth analysis of multi-target classification results to identify potential causes of mispredictions visually. We demonstrate the usefulness of the workflow in the field of predictive maintenance in a usage scenario to show how users can iteratively explore and identify critical classes, as well as, relationships between targets.

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004 Informatik
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IUI '20: 25th International Conference on Intelligent User Interfaces, 17. März 2020 - 20. März 2020, Cagliari, Italy
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ISO 690SCHLEGEL, Udo, Eren CAKMAK, Hiba ARNOUT, Mennatallah EL-ASSADY, Daniela OELKE, Daniel A. KEIM, 2020. Towards visual debugging for multi-target time series classification. IUI '20: 25th International Conference on Intelligent User Interfaces. Cagliari, Italy, 17. März 2020 - 20. März 2020. In: PATERNÒ, Fabio, ed., Nuria OLIVER, ed.. IUI '20 : Proceedings of the 25th International Conference on Intelligent User Interfaces. New York, NY: ACM, 2020, pp. 202-206. ISBN 978-1-4503-7118-6. Available under: doi: 10.1145/3377325.3377528
BibTex
@inproceedings{Schlegel2020Towar-53085,
  year={2020},
  doi={10.1145/3377325.3377528},
  title={Towards visual debugging for multi-target time series classification},
  isbn={978-1-4503-7118-6},
  publisher={ACM},
  address={New York, NY},
  booktitle={IUI '20 : Proceedings of the 25th International Conference on Intelligent User Interfaces},
  pages={202--206},
  editor={Paternò, Fabio and Oliver, Nuria},
  author={Schlegel, Udo and Cakmak, Eren and Arnout, Hiba and El-Assady, Mennatallah and Oelke, Daniela and Keim, Daniel A.}
}
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