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  4. Combining cluster and outlier analysis with visual analytics
 
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2017
Conference Paper
Titel

Combining cluster and outlier analysis with visual analytics

Abstract
Cluster and outlier analysis are two important tasks. Due to their nature these tasks seem to be opposed to each other, i.e., data objects either belong to a cluster structure or a sparsely populated outlier region. In this work, we present a visual analytics tool that allows the combined analysis of clusters and outliers. Users can add multiple clustering and outlier analysis algorithms, compare results visually, and combine the algorithms' results. The usefulness of the combined analysis is demonstrated using the example of labeling unknown data sets. The usage scenario also shows that identified clusters and outliers can share joint areas of the data space.
Author(s)
Bernard, Jürgen
TU Darmstadt GRIS
Dobermann, Eduard
TU Darmstadt GRIS
Sedlmair, Michael
Univ. Wien
Fellner, Dieter W.
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Hauptwerk
8th International EuroVis Workshop on Visual Analytics, EuroVA 2017
Konferenz
International Workshop on Visual Analytics (EuroVA) 2017
Conference on Visualization (EuroVis) 2017
Thumbnail Image
DOI
10.2312/eurova.20171114
Language
English
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Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Tags
  • information system

  • data mining

  • human-centered comput...

  • visual analytic

  • information visualiza...

  • machine learning

  • Lead Topic: Digitized...

  • Research Line: Human ...

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