Publication: ProSeCo: Visual analysis of class separation measures and dataset characteristics
ProSeCo: Visual analysis of class separation measures and dataset characteristics
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Bernard, J., Hutter, M., Zeppelzauer, M., Sedlmair, M., & Munzner, T. (2021). ProSeCo: Visual analysis of class separation measures and dataset characteristics. Computers & Graphics, 96, 48–60. https://doi.org/10.1016/j.cag.2021.03.004
Abstract
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Abstract
Class separation is an important concept in machine learning and visual analytics. We address the visual analysis of class separation measures for both high-dimensional data and its corresponding projections into 2D through dimensionality reduction (DR) methods. Although a plethora of separation measures have been proposed, it is difficult to compare class separation between multiple datasets with different characteristics, multiple separation measures, and multiple DR methods. We present ProSeCo, an interactive visualization approach
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Creators (Authors)
- Bernard, Jürgen
- Hutter, Marco
- Zeppelzauer, Matthias
- Sedlmair, Michael
- Munzner, Tamara
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Citations
Bernard, J., Hutter, M., Zeppelzauer, M., Sedlmair, M., & Munzner, T. (2021). ProSeCo: Visual analysis of class separation measures and dataset characteristics. Computers & Graphics, 96, 48–60. https://doi.org/10.1016/j.cag.2021.03.004
