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Supervised and unsupervised classification — The case of IRAS point sources

  • H. -M. Adorf
  • E. J. A. Meurs
VII Methods and Tools
Part of the Lecture Notes in Physics book series (LNP, volume 310)

Abstract

Progress is reported on a project which aims at mapping the extragalactic sky in order to derive the large scale distribution of luminous matter. Our approach consists in selecting from the IRAS Point Source Catalog a set of galaxies which is as clean and as complete as possible. The decision and discrimination problems involved lend themselves to a treatment using methods from multivariate statistics, in particular statistical pattern recognition. Two different approaches - one based on supervised Bayesian classification, the other on unsupervised data-driven classification - are presented and some preliminary results are reported.

Keywords

Galactic Centre Galactic Plane Unsupervised Classification Gould Belt European Southern Observatory 
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 1988

Authors and Affiliations

  • H. -M. Adorf
    • 1
  • E. J. A. Meurs
    • 2
  1. 1.Space Telescope - European Coordinating Facility European Southern ObservatoryGarching b. MünchenGermany
  2. 2.European Southern ObservatoryGarching b. MünchenGermany

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