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On the phenomenon of flattening “flexible prediction” concept hierarchy

  • Mieczyslaw A. Klopotek
Part II Selected Contributions
Part of the Lecture Notes in Computer Science book series (LNCS, volume 535)

Abstract

The Incremental Concept Formation method, as described in [19] is claimed therein to be “able to formulate diagnostically useful categories even without class information”, “given real world data on heart disease”. We suggest in this paper that the method does not derive categories from the data but from primary and derived attribute selection by showing that equal treatment of all attributes leads to a flat (one level) concept hierarchy.

Keywords

Real World Data Class Information Atomic Formula Separate Class Concept Hierarchy 
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 1991

Authors and Affiliations

  • Mieczyslaw A. Klopotek
    • 1
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarsawPoland

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