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Authors: Bruno Schneider ; Daniel A. Keim and Mennatallah El-Assady

Affiliation: University of Konstanz, Germany

Keyword(s): Dataset Shift, Information Visualization, Classification.

Abstract: In supervised learning, to ensure the model's validity, it is essential to identify dataset shifts, i.e., when the data distribution changes from the one the model encountered at the time of training. To detect such changes, a comparative analysis of the multidimensional data distributions of the training data and new, unseen datasets is required. In this paper, we span the design space of visualizations for multidimensional comparative data analytics. Based on this design space, we present DataShiftExplorer, a technique tailored to identify and analyze the change in multidimensional data distributions. Throughout examples, we show how DataShiftExplorer facilitates the identification and analysis of data changes, supporting supervised learning.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Schneider, B.; Keim, D. and El-Assady, M. (2020). DataShiftExplorer: Visualizing and Comparing Change in Multidimensional Data for Supervised Learning. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - IVAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 141-148. DOI: 10.5220/0008940801410148

@conference{ivapp20,
author={Bruno Schneider. and Daniel A. Keim. and Mennatallah El{-}Assady.},
title={DataShiftExplorer: Visualizing and Comparing Change in Multidimensional Data for Supervised Learning},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - IVAPP},
year={2020},
pages={141-148},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008940801410148},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - IVAPP
TI - DataShiftExplorer: Visualizing and Comparing Change in Multidimensional Data for Supervised Learning
SN - 978-989-758-402-2
IS - 2184-4321
AU - Schneider, B.
AU - Keim, D.
AU - El-Assady, M.
PY - 2020
SP - 141
EP - 148
DO - 10.5220/0008940801410148
PB - SciTePress