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Explaining Neighborhood Preservation for Multidimensional Projections
University of São Paulo, Brazil ; University of Groningen, The Netherlands.ORCID iD: 0000-0002-2901-935X
University of São Paulo, Brazil.
University of Groningen, The Netherlands.
2015 (English)In: EG UK Computer Graphics & Visual Computing (2015) / [ed] Rita Borgo, Cagatay Turkay, Eurographics - European Association for Computer Graphics, 2015, p. 7-14Conference paper, Published paper (Refereed)
Abstract [en]

Dimensionality reduction techniques are the tools of choice for exploring high-dimensional datasets by means of low-dimensional projections. However, even state-of-the-art projection methods fail, up to various degrees, in perfectly preserving the structure of the data, expressed in terms of inter-point distances and point neighborhoods. To support better interpretation of a projection, we propose several metrics for quantifying errors related to neighborhood preservation. Next, we propose a number of visualizations that allow users to explore and explain the quality of neighborhood preservation at different scales, captured by the aforementioned error metrics. We demonstrate our exploratory views on three real-world datasets and two state-of-the-art multidimensional projection techniques.

Place, publisher, year, edition, pages
Eurographics - European Association for Computer Graphics, 2015. p. 7-14
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-73243DOI: 10.2312/cgvc.20151234OAI: oai:DiVA.org:lnu-73243DiVA, id: diva2:1199790
Conference
Computer Graphics and Visual Computing (CGVC)
Available from: 2018-04-22 Created: 2018-04-22 Last updated: 2018-04-26Bibliographically approved

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Martins, Rafael Messias

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  • apa
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  • en-US
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  • Other locale
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Output format
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  • asciidoc
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