Rough Mereology in Classification of Data: Voting by Means of Residual Rough Inclusions

  • Lech Polkowski
  • Piotr Artiemjew
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5306)

Abstract

In this work, we pursue the theme of applications of rough mereology, presenting a scheme for classifier construction by voting of training objects, exhaustive set of rules, and granules of training objects according to weights assigned by residual rough inclusions. The results show a high effectiveness of this approach as witnessed by the reported tests with some well–known data sets from UCI repository whose results are compared against the standard rough set exhaustive classifier.

Keywords

granulation of knowledge rough inclusions residual implications granular decision systems 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Lech Polkowski
    • 1
  • Piotr Artiemjew
    • 2
  1. 1.Polish–Japanese Institute of ITWarsawPoland
  2. 2.Department of Mathematics and Computer ScienceUniversity of Warmia and MazuryOlsztynPoland

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