Random Probes in Computation and Assessment of Approximate Reducts

  • Andrzej Janusz
  • Dominik Ślęzak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8537)


We discuss applications of random probes in a process of computation and assessment of approximate reducts. By random probes we mean artificial attributes, generated independently from a decision vector but having similar value distributions to the attributes in the original data. We introduce a concept of a randomized reduct which is a reduct constructed solely from random probes and we show how to use it for unsupervised evaluation of attribute sets. We also propose a modification of the greedy heuristic for a computation of approximate reducts, which reduces a chance of including irrelevant attributes into a reduct. To support our claims we present results of experiments on high dimensional data. Analysis of obtained results confirms usefulness of random probes in a search for informative attribute sets.


attribute selection attribute reduction high dimensional data approximate reducts 


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© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Andrzej Janusz
    • 1
  • Dominik Ślęzak
    • 1
    • 2
  1. 1.Institute of MathematicsUniversity of WarsawWarsawPoland
  2. 2.Infobright Inc., PolandWarsawPoland

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