Contribution to a conference collection: Interactive Visualization and Feature Transformation for Multidimensional Data Projection
Interactive Visualization and Feature Transformation for Multidimensional Data Projection
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2013
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Abstract
Projecting multidimensional data to a lower-dimensional visual display as a scatter-plot-like visualization is a common approach for analyzing multidimensional data. Many dimension reduction techniques exist for performing such a task, but the quality of projections varies in terms of both preserving the original data structure and avoiding cluttered visual displays. In this paper, we propose an interactive feature transformation approach that allows the analyst to monitor and improve the projection quality by transforming feature space and assessing/ comparing the quality of different projection results. The method integrates feature selection and transformation as well as a variety of projection quality measures to help analyst generate uncluttered projections that preserve the structural properties of the data. These projections enhance the visual analysis process and provide a better understanding of data.
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004 Computer Science
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EuroVis Workshop on Visual Analytics using Multidimensional Projections / Aupetit, M.; van der Maaten, L. (ed.). - Goslar : Eurographics, 2013. - pp. 21-25. - ISBN 978-3-905674-53-8
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EuroVis, Jun 19, 2013, Leipzig, Germany
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PÉREZ, Daniel, Leishi ZHANG, Matthias SCHÄFER, Tobias SCHRECK, Daniel A. KEIM, Ignacio DÍAZ, 2013. Interactive Visualization and Feature Transformation for Multidimensional Data Projection. EuroVis. Leipzig, Germany, Jun 19, 2013. In: AUPETIT, M., ed., L. VAN DER MAATEN, ed.. EuroVis Workshop on Visual Analytics using Multidimensional Projections. Goslar:Eurographics, pp. 21-25. ISBN 978-3-905674-53-8. Available under: doi: 10.2312/PE.VAMP.VAMP2013.021-025BibTex
@inproceedings{Perez2013Inter-24914,
year={2013},
doi={10.2312/PE.VAMP.VAMP2013.021-025},
title={Interactive Visualization and Feature Transformation for Multidimensional Data Projection},
isbn={978-3-905674-53-8},
publisher={Eurographics},
address={Goslar},
booktitle={EuroVis Workshop on Visual Analytics using Multidimensional Projections},
pages={21--25},
editor={Aupetit, M. and van der Maaten, L.},
author={Pérez, Daniel and Zhang, Leishi and Schäfer, Matthias and Schreck, Tobias and Keim, Daniel A. and Díaz, Ignacio}
}
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<dcterms:abstract xml:lang="eng">Projecting multidimensional data to a lower-dimensional visual display as a scatter-plot-like visualization is a common approach for analyzing multidimensional data. Many dimension reduction techniques exist for performing such a task, but the quality of projections varies in terms of both preserving the original data structure and avoiding cluttered visual displays. In this paper, we propose an interactive feature transformation approach that allows the analyst to monitor and improve the projection quality by transforming feature space and assessing/ comparing the quality of different projection results. The method integrates feature selection and transformation as well as a variety of projection quality measures to help analyst generate uncluttered projections that preserve the structural properties of the data. These projections enhance the visual analysis process and provide a better understanding of data.</dcterms:abstract>
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