SAX Navigator: Time Series Exploration through Hierarchical Clustering

Ruta, Nicholas; Sawada, Naruhiko; McKeough, Katy; Behrisch, Michael; Beyer, Johanna

doi:10.48550/arxiv.1908.05505

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2020

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“…However, such visualizations are challenging to scale for long time series or many time series samples. An approach to overcome these challenges uses SAX Navigator [36] by applying SAX [5] to transform time series into an abstract symbolic representation and cluster the results to explore the data on various levels. Other proposals use dimension reduction techniques to visualize time series as paths such as Time Curves [37] to cope with long time series and hard-toread, as well as compare line plots.…”

Section: Related Workmentioning

confidence: 99%

Towards visual debugging for multi-target time series classification

Schlegel

Cakmak

Arnout³

et al. 2020

Proceedings of the 25th International Conference on Intelligent User Interfaces

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Figure 1: Multi-Target Visual Debugging Workflow.(1) A user selects a model from a set of multi-target classifiers to inspect its performance. (2) Through filtering of parl ially correcl results and the visual investigation between the relationships of the n-target, the user can focus on a certain single-target. (3) By inspecting the filtered single-target confusion of multi-classes, a dri ll down onto the unde rlying time series classification data is possible that aims to give meaningful insights into the dass confusions.

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Section: Related Workmentioning

confidence: 99%