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Main Reductions

  • Mikhail MoshkovEmail author
Chapter
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Part of the Intelligent Systems Reference Library book series (ISRL, volume 179)

Abstract

In this chapter, we consider some reductions which will be used later in the investigations of decision trees for problems. We show that, in the frameworks of the local approach, the study of decision trees for problems can be reduced to the study of decision trees for decision tables. We prove that, instead of arbitrary classes of information systems, we can consider classes containing only one information system. We also show that the matrix of upper local bounds for a sccf-triple completely defines its matrix of lower local bounds and vice versa. In particular, the local upper type of a sccf-triple completely defines its local lower type and vice versa.

References

  1. 1.
    Moshkov, M.: Comparative analysis of deterministic and nondeterministic decision tree complexity, Global approach. Fundam. Inform. 25(2), 201–214 (1996)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Moshkov, M.: Comparative analysis of deterministic and nondeterministic decision tree complexity, Local approach. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets IV, Lecture Notes in Computer Science, vol. 3700, pp. 125–143. Springer, Berlin (2005)Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer, Electrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and TechnologyThuwalSaudi Arabia

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