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Visual Verification of Hypotheses

  • Thorsten May
  • Joern Kohlhammer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5359)

Abstract

The analytical derivation of a hypothesis is a process, that requires a transformation of information between raw data and an analytical model. Even though much effort has been spent to support the creation of hypotheses both by algorithmic and visual means, much less research has been done on how the process can be reversed for the verification of existing hypotheses. An evaluation of empirical hypotheses must be grounded in raw data and may require many tedious drill-downs, especially for complex data. We present a concept combining an analytical technique for the representation of hypotheses and their transformation into the data-space. We also show visualization techniques for the formalization of the hypothesis in the analytical space and its visual evaluation in the data space. The evaluation is supported by a visual-matchmaking between original raw data and a modification of this data based upon the assumptions implied by the hypothesis.

Keywords

Decision Tree Leaf Node Data Item Visualization Technique Simulated Dataset 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Thorsten May
    • 1
    • 2
  • Joern Kohlhammer
    • 1
    • 2
  1. 1.Fraunhofer Institute for Computer GraphicsDarmstadtGermany
  2. 2.Interactive Graphics Systems GroupTU-DarmstadtGermany

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