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Visual analysis based on algorithmic classification
2003 (English)In: IEEE INFOR VIS P, 2003, 86-93 p.Conference paper, Published paper (Refereed)
Abstract [en]

Extracting actionable insight from large high dimensional data sets, and its use for more effective decision-making, has become a pervasive problem across many fields in research and industry. This paper describes an investigation of the application of tightly coupled statistical and visual analysis techniques to this task. The approach we choose in this study is "unsupervised learning" where we investigate the advantages offered by close coupling of the self-organizing map algorithm with new combinations of visualization components and techniques for interactivity.

Place, publisher, year, edition, pages
2003. 86-93 p.
Series
IEEE conference on information visualization - proceedings, ISSN 1093-9547
Keyword [en]
unsupervised learning, self-organizing map, visual analysis, tightly coupled visualizations, knowledge discovery, visual user interface
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-35001ISI: 000184737800015OAI: oai:DiVA.org:kth-35001DiVA: diva2:424863
Note
QC 20110620Available from: 2011-06-20 Created: 2011-06-17 Last updated: 2011-11-08Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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