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Standard Errors of Indices in Rough Set Data Analysis

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Transactions on Rough Sets XVII

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 8375))

Abstract

The sample variation of indices for approximation of sets in the context of rough sets data analysis is considered. We consider the γ and α indices and some other ones – lower and upper bound approximation of decision classes. We derive confidence bounds for these indices as well as a two group comparison procedure. Finally we present procedures to compare the approximation quality of two sets within one sample.

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Author information

Authors and Affiliations

  1. Department of Psychology, Institut IV, Universität Münster, Fliednerstr. 21, Münster, Germany

    Günther Gediga

  2. Brock University, St. Catharines, Ontario, Canada, L2S 3A1

    Ivo Düntsch

Authors
  1. Günther Gediga
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  2. Ivo Düntsch
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Editor information

Editors and Affiliations

  1. Computational Intelligence Laboratory, ECE Department, University of Manitoba, MB R3T 5V6, Winnipeg, Canada

    James F. Peters

  2. Institute of Mathematics, University of Warsaw, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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Gediga, G., Düntsch, I. (2014). Standard Errors of Indices in Rough Set Data Analysis. In: Peters, J.F., Skowron, A. (eds) Transactions on Rough Sets XVII. Lecture Notes in Computer Science, vol 8375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54756-0_2

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  • DOI: https://doi.org/10.1007/978-3-642-54756-0_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54755-3

  • Online ISBN: 978-3-642-54756-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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